proceedings of the 11 international conference on...

”VASILE ALECSANDRI” UNIVERSITY OF BACAU

FACULTY OF ENGINEERING

PROCEEDINGS OF THE 11th INTERNATIONAL CONFERENCE ON INDUSTRIAL POWER

ENGINEERING

The 11th Edition

BACĂU, ROMÂNIA

June 27 – 29, 2018

Editura Alma Mater Bacău

2018

1 1 T H I N T E R N A T I O N A L C O N F E R E N C E O N I N D U S T R I A L P O W E R E N G I N E E R I N G

2

EDITORS-IN CHIEF

Roxana GRIGORE

Aneta HAZI George CULEA

TECHNICAL EDITORIAL STAFF: Sorin-Gabriel Vernica

“VASILE ALECSANDRI” UNIVERSITY OF BACAU-ROMANIA

ALMA MATER Publishing House “VASILE ALECSANDRI” UNIVERSITY OF BACAU-ROMANIA

Department of Energetics and Computer Science Calea Mărăşeşti 157, RO-600115 BACAU, ROMANIA

Tel: +40 234 542 411; Fax: +40 234 580 170

Editura Alma Mater Bacău 2018

ISSN 2069 – 9905 ISSN-L 2069 – 9905


3

Scientific Committee

Jean-François BRUDNY (University of Artois, Bethune, France)

Vladimir BERZAN (Institute of Power Engineering of the Academy of Sciences of Moldova, Chişinău,

Republic of Moldova)

George CULEA (“Vasile Alecsandri” University of Bacau, Romania)

Mihai GAVRILAŞ (“Gh.Asachi” Technical University of Iaşi, Romania)

Mazen GHANDOUR (Lebanese University, Hadath-Beirut, Lebanon)

Roxana GRIGORE (“Vasile Alecsandri” University of Bacau, Romania)

Gheorghe HAZI (“Vasile Alecsandri” University of Bacau, Romania)

Aneta HAZI (“Vasile Alecsandri” University of Bacau, Romania)

Petru LIVINŢI (“Vasile Alecsandri” University of Bacau, Romania)

Sebastian MIRON (Research Center for Automatic Control of Nancy, France)

Florian MISOC (Kennesaw State University, USA)

Cristian NICHITA (University of Le Havre, France)

Florentin PALADI (State University of Moldavia, Chişinău, Republic of Moldova)

Valentina NICORICI (State University of Moldavia, Chişinău, Republic of Moldova)

Radu PENTIUC („Stefan cel Mare” University of Suceava, Romania)

Mihai PUIU-BERIZINŢU (“Vasile Alecsandri” University of Bacau, Romania)

Remus PUSCA (University of Artois, Bethune, France)

Raphaël ROMARY (University of Artois, Bethune, France)

Dan ROTAR (“Vasile Alecsandri” University of Bacau, Romania)

Joanny STEPHANT (University of Limoges, ENSIL, France)


4

CONTENT

1. GHEORGHE HAZI, ANETA HAZI, SORIN VERNICA - CONSIDERATIONS ON THE

DETERMINATION OF ENERGY LOSSES IN ENVIRONMENTAL NETWORKS 5

2. ANETA HAZI, GHEORGHE HAZI, SORIN VERNICA - IMPROVING THE OPERATING

DIAGRAM OF A SUBSTATION 14

3. BOSTAN VIOREL, BOSTAN ION, GUŢU MARIN, RABEI ION, DULGHERU VALERIU -

CFD SIMULATION OF THE MATHEMATICAL MODELS OF THE INTERACTION

BETWEEN THE BLADES AND FLUID

20

4. FLORENTIN PALADI, VLADIMIR PRIMAC - MUTUAL INFLUENCES OF THE MODERN

INFORMATION TECHNOLOGIES AND ENERGETIC INDUSTRY 25

5. MOHMED ASHGLAF, CRISTIAN NICHITA - POWER MANAGEMENT STRATEGIES

BASED ON ENERGY STORAGE TECHNOLOGIES - REVIEW FOR FUTURE

IMPLEMENTATIONS IN REAL -TIME EMULATORS

29

6. VERNICA SORIN-GABRIEL, HAZI ANETA, HAZI GHEORGHE, GRIGORE ROXANA -

PROPOSALS TO IMPROVE THE OPERATING REGIMES OF A GAS TURBINE PLANT 43

7. ROXANA GRIGORE, SORIN-GABRIEL VERNICA ,MIHAI PUIU-BERIZINȚU, SILVIU,

IFTIME - ASPECTS RELATED TO THE UTILIZATION OF GEOTHERMAL ENERGY FOR

THE PRODUCTION OF ELECTRICITY IN ROMANIA

47


5

1

CONSIDERATIONS ON THE DETERMINATION OF ENERGY LOSSES IN

ENVIRONMENTAL NETWORKS

GHEORGHE HAZI1, ANETA HAZI1, SORIN VERNICA1

1“Vasile Alecsandri” University of Bacau, Calea Marasesti 157, Bacau, 600115, Romania

Abstract: The paper presents an analysis of the methodology for calculating the energy

losses contained in the normative NTE 013/16/00, the Energy Technical Standard for

Determination of Own Technological Consumption in Public Interest Electricity Networks.

The analysis is based on calculations made for a 20 kV network in Bacau County. It is

taken account of the requirements imposed by the distribution operator in the zone,

DELGAZ GRID SA.

Keywords: power system losses, medium voltage, calculation methodology

1. INTRODUCTION

By ANRE Order no. 26 / 22.06.2016 approved the Energy Technical Standard for Determination of Own

Technological Consumption in Public Interest Electricity Networks, NTE 013/16/00 [2]. The normative is aimed

at establishing the methods of determination and analysis of the own technological consumption (OTC) in the

public electricity networks.

The methods presented are the following:

a) The statistical method, which consists in determining the predicted OTC based on statistical data recorded in

previous periods, using linear regression relations.

b) Loss method on network elements consisting of predicted OTC calculation and technical OTC based on

loadings of network elements in different operating regimes and their technical characteristics.

c) The average network element method, which consists in calculating the predicted OTC and the technical OTC

achieved in a network or network zone based on the OTC calculated in a network element considered to be its

average element.

d) The electricity balance method, which consists of the OTC forecast and OTC based on the electricity balance,

the difference between the electricity input and the electricity output from the balance outline.

e) The efficiency method, which consists of the OTC forecasting and realization for a category of network

elements based on the transported electricity and its operating efficiency, determined statistically in the previous

periods.

Also, DELGAZ GRID, the Moldovan distribution operator, has developed a methodology for the determination

of OTC in public-interest electrical networks for the supply of domestic consumers [3]. This methodology

defines the way of calculating the own technological consumption for the distribution installations related to the

electricity supply of domestic consumers and represents a particularization of the method b) presented above.

In the present paper the authors make a critical analysis of the presented methodologies, especially variant b), as

compared to the variants applicable prior to the occurrence of NTE 013.

2. PRESENTATION OF THE NETWORK ANALIZED

The analysis was carried out on a 20 kV grid in the Dărmăneşti zone, overhead electric line LEA 20 kV Poiana

Uzului. The diagram of the network is shown in Figure 1.


6

250K

VA

100K

VA

LE

A 2

0kV

20 k

V

DC 35

2 12

1120

A2Y

SY

135

35

PT

A 3

PT

A 1

ST

AT

IA 1

10/2

0/6

kV

DA

RM

AN

ES

TI

PO

IAN

A U

ZU

LU

I

L1

L2

12

B A

MO

24

MO

24

3

AL

95+

120

250m

1 2

63K

VAD

CP

TA

7S

AL

AT

RU

C

6

99m35

1

PT

CZ

10

630K

VA

1

PT

CZ

8S

AL

AT

RU

C

A2Y

SY

150

5m

22m

A2Y

SY

150

SA

LA

TR

UC

22

95

4.8

61m

912

75K

VA

PT

A 5

TV

SA

LA

TR

UC

20

15m

1

35

100K

VA

SA

LA

TR

UC

PT

A 9

GA

TE

R

78

330m

22

1

100K

VA

DC

SA

LA

TR

UC

PT

A 6

35

63K

VA

SA

LA

TR

UC

1

2

400K

VA

AL

120 SA

LA

TR

UC

PT

CZ

4

28

30

30m

68m

1

SA

LA

TR

UC

35

SA

LA

TR

UC

2

22m

45m

38

43

49

MO

24

PT

A 1

1

319

42

MO

24

L2

L1

C.H

.E.

PO

IAN

A U

ZU

LU

I

6,3

MV

A

24,2

/23,1

/22/2

0,9

/19,8

Usc

=7,2

5 %

6kV

6,3

kV

6/0

,1kV

3,4

MV

A0,7

MV

A

20/0

,1kV

50

18m

1.0

03m

4 13

MO

24

3

50

3.0

00m

PT

CZ

15k

9k

7k

8k

160m

35

98m

3

100K

VA

SA

LA

TR

UC

150

PT

A 1

2

160K

VA

8m

3A

SS

29

SS

48

SS

5S

S38

SS

41

1

40

100K

VA

PT

A 2

SA

LA

TR

UC

MO

24

9b

1

PT

A 1

3S

AL

AT

RU

C

250K

VA

48

12

A2X

(FL

)Y600m

PT

AB

14

SA

LA

TR

UC 400K

VA

SF

6

48b1235

PT

A 1

UZ

PT

A 2

UZ

PT

A 3

UZ

PT

A 4

UZ

PT

A 5

UZ

100 K

VA

100 K

VA

100 K

VA

100 K

VA

100 K

VA

20m

R

AL

150

4.1

91 m

610

28

70

165m

70

140m

70

1044 m

50

148 m

50

20 m

11

40

41

43

58

89

70

30 m

70

724 m

70

1540 m

50

20 m

RE

TE

A P

RO

IEC

TA

TA

AL

150

830 m

Fig

. 1

Th

e d

iag

ram

of

the

net

wo

rk a

nal

ized


7

The network includes an existing zone and a projected zone (surrounded by a yellow border). As a rule, for the

projected works, the distribution operator requires the influence of network expansion on network power losses.

Specific to this network is that hydroelectric power plant (CHE) Dărmăneşti has 2 different groups of different

powers that work alternately. Working with one group or another significantly changes the network regime.

The main charactheristics of the network are:

The length of 20 kV lines – 18.8 km

The active power consumed in the network in the existing situation – 2.01 MW

The reactive power consumed in the network in the existing situation – 1.25 MVAR

The active power consumed in the network in year I after commissioning (PIF) – 2.17 MW

The reactive power consumed in the network in year I after PIF – 1.34 MVAR

The active power consumed in the network in year II after PIF – 2.19 MW

The reactive power consumed in the network in year II after PIF – 1.36 MVAR

The active power consumed in the network in year III after PIF – 2.22 MW

The reactive power consumed in the network in year III after PIF – 1.37 MVAR

The maximum active power produced by CHE (with large group in operation)– 3.67 MW

The maximum reactive power produced by CHE (with large group in operation)– 1.5 MVAR

The active power produced by CHE (with small group in operation)– 0.29 MW

The active power produced by CHE (with small group in operation) – 0.12 MVAR

The power installed in transformers in the network stations, the existing situation – 2.65 MVA

The power installed in the transformers in the network stations, the projected situation – 3.15 MVA

3. LOSS METHOD ON NETWORK ELEMENTS

Among the methods listed in point 1 of the paper, the loss method on network elements is the only one widely

applicable if the electricity consumption characteristic is known (by type of consumer: domestic, industrial, etc.).

This method is based on the loss time τ, defined as the conventional time interval, in which, in a constantly

charged network element at maximum SM load, there would be losses of electric energy equal to those produced

in the case of its operation according to the curve of real load.

In old normative [1], it is calculated with one of the relationships:

T

T

TSM

SM

SM

3175 0 275

8760 0 363

.

. [h/year] (1)

SM

SMSM

T

TT

27520

10000 [h/year] (2)

Where TSM represents the duration of use of the apparent maximum load - a conventional time interval in which,

through a permanently charged network element at full load, a quantity of electrical energy equal to that

transported in the case of its operation according to the curve of real load. This amount can be determined by the

amount of energy transited:

M

2

Q

2

P

SMS

WWT

[h/an] (3)

where WP, WQ active energy [kWh/year] and reactive, respectively, [kVARh/year], transited in one year, and SM

maximum apparent power [kVA] recorded over the same period.

The annual energy loss on a variable load element is calculated with the relationship:

W P I RS

URM

M max 3 22

2 [KWh/an] (4)


8

where IM represents the maximum load current associated with the apparent SM load, for the three-phase network

element operating at the voltage between the phases U.

In the new normatives [2], [3], the method of calculating the loss time τ is changed:

*T (5)

where T is the reference duration (typically 8760 h), and τ *, the loss factor, determined by the following

formula:

* 2(1 )u up k p k (6)

where p is a statistically determined coefficient with p € (0.15÷0.3), in the absence of other information it can be

considered p = 0.2 [2], and ku the filling factor of the load curve determined by the relationship:

max SMu

med

S Tk

S T (7)

2 2

P Q

med

W WS

T

(8)

In the normative [3], the following principles are proposed for the determination of MT / JT network losses:

a) for Pmax <100 kW, the energy losses will be calculated on the network elements: LEA / LES JT and in

TRAFO MT / JT;

b) for 100kW ≤ Pmax < 400 kW the energy losses will be calculated on the network elements: LEA/LES JT,

TRAFO MT/JT, LEA/LES MT;

c) for Pmax ≥ 400 kW the energy losses will be calculated on the network elements: LEA/LES JT, TRAFO

MT/JT, LEA/LES MT, TRAFO IT/MT.

4. CALCULATION OF ENERGY LOSS, CLASSIC METHOD, NTE 401

For the analysis of the methodology presented by NTE 013 [2], compared to the classical method NTE 401, [1],

we will determine the energy losses for the presented network using both variants. In order to determine the

energy losses, we need the power losses in the maximum load regime. For this we used the RP V3.1 software,

[4].

Power losses in characteristic regimes are shown in Table 1.

Table 1. Power losses in characteristic regimes

Note: Zone 1 – axle 20 kV, st. Dărmaneşti – CHE

Zone 2 – derivatives + transformation posts (PT)- existing

Zone 3 – projected network (including PTs), Total/OHL 20 kV/Trans 20/0,4 kV

Year

CHE with small group CHE with large group

Total

[kW]

Zone 1

[kW]

Zone 2

[kW]

Zone 3

[kW]

Total

[kW]

Zone 1

[kW]

Zone 2

[kW]

Zone 3

[kW]

Existent 79,84 9,11 70,73 - 90 20,7 69,3 -

Year 1 82,03 9,40 70,72

1,91

90,5 19,28 69,3

1,90

0,12 0,11

1,79 1,79

Year 2 82,75 9,74 70,74

2,27

90,42 18,84 69,3

2,26

0,13 0,13

2,14 2,13

Year 3 83,41 10,02 70,75

2,64

90,43 18,48 69,3

2,61

0,16 0,15

2,48 2,46


9

Iron losses - Existing: 4,89 kW

Iron losses – projected: 4,89+0,725 kW = 5,615 kW

Determination of annual energy losses is presented in Table 2.

Table 2. Energy losses calculated using the NTE 401 method

No.

Characteristic features UM

Calculated

values

Calculation relations

0 1 2 3 4 5

1. Input data

T – reference duration

Pmax – the maximum active

power consumed in the

network, the existing situation

Qmax – the maximum reactive

power consumed in the

network, the existing situation

WP – the active energy

consumed in the network in

one year, the existing situation

WQ – the reactive energy

consumed in the network in

one year, the existing situation

h

MW

MVAR

MWh/year

MVARh/year

8760

2.01

1.25

2268

1186

1 year

wattmeters readings

warmth readings

reading counters

reading counters

2.

Calculation of loss

time for power

supply network of

domestic consumers

TSM – duration of use of the

apparent maximum load

τc – loss time for domestic

consumers

h/year

h/ year

1081.28

448.71

2 2

2 2

max max

P Q

SM

W WT

P Q

3175 0.275

8760 0.363

SMc SM

SM

TT

T

3.

Loss time for axle 20

kV

WanCHE - Energy

produced in one year by

CHE Uz

MWh/ year 9978.36 reading counters

PmaxCHE - Puterea

maxima CHE

MW 3.672 Load curve

TCHE - duration of use of

the maximum load for CHE

h/ year 2717.42

max

anCHECHE

CHE

WT

P

τCHE - loss time for axle

CHE

h/ year 1217.85

3175 0.275

8760 0.363

CHE CHE

CHE

CHE

T

T

T


10

4.

Energy losses in the

existing situation,

axle 20 kV

ΔPz1 - Power loss in zone 1

(20 kV axle) in maximum

load regime

kW 20.7 From listing regime

ΔWz1exist - Energy losses

in in 20 kV axle, existing

MWh/

year

28.38

1000

11

CHEzexitz

PW

5. Energy losses in year

I after PIF



load regime


ΔPz31 - Power losses in zone

3, projected (20 kV lines) in

maximum load regime

kW 0,11 From listing regime

ΔWz11 - Energy losses in 20

kV axle

MWh/

year

26.43

1000

1111

CHEzz

PW

ΔWz31 - Energy losses in in

zone projected (20 kV lines)

in maximum load regime

MWh/

year

0.049

1000

3131

czz

PW

ΔWz11sup - Additional

energy losses in zone 1 (20

kV axle) due to the

projected load

MWh/

year

-1.95 11sup 11

1

z z

z exist

W W

W


II after PIF



load regime




maximum load regime



kV axle

MWh/

year

25.83

1000

1212

CHEzz

PW



MWh/

year

0.058

1000

3232

czz

PW



kV axle) due to the

projected load

MWh/

year

-2.55 12sup 12

1

z z

z exist

W W

W


11

In the table above, only the change in annual energy losses due to the extension of the network with 5

transformation stations was presented, this information being requested by the distribution operator.

5. CALCULATION OF ENERGY LOSS, NTE 013 METHOD

The power losses in maximum load regime remain as shown in Table 1. Energy losses are given in Table 3.

Table 3. Energy losses calculated using the NTE 013 method

No.

Characteristic features UM

Calculated

values

Calculation relations

0 1 2 3 4 5

1.

Calculation of loss

time for power

supply network of

domestic consumers

ku – filling factor of the load curve

p - statistically determined

coefficient

τr - Loss time, relative, for domestic

consumers

τc – Loss time for domestic

consumers

-

-

-

h/year

0.123

0.2

0.037

323

SMu

Tk

T

NTE 013

2)1( uur kpkp

c r T

2.

Loss time for axle V.

Uzului 2 (evacuation

CHE)

T – reference duration h/ year 8760

ku - filling factor of the load curve - 0.31 CHE

u

Tk

T

p - statistically determined

coefficient

- 0.2 DEGR P02-02-21, Ed.1

τr - Loss time, relative, for axle CHE - 0.139 2)1( uur kpkp


III after PIF



load regime




maximum load regime



kV axle

MWh/

year

25.34

1000

1313

CHEzz

PW



MWh/

year

0.067

1000

3333

czz

PW



kV axle) due to the

projected load

MWh/

year

-3.04 13sup 13

1

z z

z exist

W W

W


12

τCHE - Loss time for axle CHE h/ year 1217.85 TrCHE

3.

Energy losses in the

existing situation,

axle 20 kV

ΔPz1 - Power loss in zone 1 (20 kV

axle) in maximum load regime


ΔWz1exist - Energy losses in in 20 kV

axle, existing

MWh/

year

25.21

1000

11

CHEzexitz

PW


I after PIF




ΔPz31 - Power losses in zone 3,

projected (20 kV lines) in maximum

load regime

kW 0,11 From listing regime

ΔWz11 - Energy losses in 20 kV axle MWh/

year

23.48

1000

1111

CHEzz

PW

ΔWz31 - Energy losses in in zone


load regime

MWh/

an

0.036

1000

3131

czz

PW

ΔWz11sup - Additional energy losses

in zone 1 (20 kV axle) due to the

projected load

MWh/

year

-1.73 11sup 11

1

z z

z exist

W W

W


II after PIF






load regime



year

22.94

1000

1212

CHEzz

PW


projected (20 kV lines)

MWh/

year

0.042

1000

3232

czz

PW



projected load

MWh/

year

-2,266 12sup 12

1

z z

z exist

W W

W


III after PIF






load regime



year

22.51

1000

1313

CHEzz

PW


projected (20 kV lines)

MWh/

year

0.048

1000

3333

czz

PW



projected load

MWh/

year

-2.704 13sup 13

1

z z

z exist

W W

W

6. CONCLUSIONS

From the data presented above, the following results:

The NTE 013 normative introduces a number of new methods for calculating network power

losses. These methods do not add extra clarity and precision.


13

The statistical method presented in the normative requires a series of accurate determinations of the

energy losses for at least 5 years. However, there is no precise method, not even through

measurements, due to the large number of measurement points that are needed.

The method of loss on network elements, the method tested in this paper, leads to lower energy

losses by about 28% for domestic consumers and by 11% lower on the 20 kV axle. The difference

is significant, but the normative shows the coefficient p determined statistically with a margin of

values, but does not show a practical method of determining it. For this reason, the user must take

the recommended value p=0.2.

In the example shown, the energy losses in the public network decrease due to the fact that the

extension of the network is near a source which reduces the losses in the evacuation line.

REFERENCES

[1] ANRE - Methodology for the determination of the economic section of the conductors in electrical

distribution installations of 1 - 110 kV, indicative NTE 401/03/00, approved by ANRE President's Decision

no.269 of 4.06.2003

[2] ANRE - Energy technical norm for the determination of the own technological consumption in the public

electricity networks, indicative NTE 013/16/00, approved by the ANRE Order no. 26 / 22.06.2016.

[3] DELGAZ GRID - Methodology for the determination of OTC in public-interest electrical networks for the

supply of domestic consumers, code DEGR P02-02-21, Ed.1, 2017.

[4] Hazi Gh., Application for the calculus regimes of the electrical power systems - RP V3.0, Romanian Tehnical

Sciences Academy, Modelling and Optimization in the Machines Building Field, Volume 2, MOCM-10, ISSN

1224-7480, pp. 45-50, 2004


14

2

IMPROVING THE OPERATING DIAGRAM OF A SUBSTATION

HAZI ANETA11, HAZI GHEORGHE1, VERNICA SORIN GABRIEL1

1“Vasile Alecsandri” University of Bacau, Calea Marasesti 156, Bacau, 600115, Romania

Abstract: The connecting diagram of a substation must ensure its safe and economical

operation. Selection of the normal operating diagram may result in minimal energy losses in

the substation in condition of compliance with nominal parameters of equipment and

continuity of supply to consumers. In the paper a mathematical model for the calculation of

energy losses in transformers according to the load curve is made. Here are presented the

energy losses and short-circuit currents for a substation. Finally, the normal operation

diagram of the substation is proposed.

Keywords: substation, operating diagram, energy losses, short-circuit current

1. INTRODUCTION

The substations are the nodes in the power system where several lines and transformers are connected together,

[2]. Most substations have double bus connecting diagram, sectioned or not [1]. The transformer substations

have one or more transformers that can operate in a radial or parallel diagram, [4]. The normal operation diagram

of the substation is set so that the safe operation of the substation is maximum, the short-circuit currents on the

bus-bars are lower than the breaking currents of the breakers in the cells of the respective bus and the energy

losses are minimal.

The operation regime of the power transformers in the substations is decisive in assessing the energy losses in

the substation, [3]. Connecting the transformer in parallel leads to increased short-circuit currents, [5]

In this paper, a multi-function substation, ie connections, transformation, evacuation and distribution, is

analyzed, in order to establish an operating diagram that ensures short-circuit currents on the bus within the

permissible limits and minimum energy losses provided maximum safety is in use.

2. CALCULATION METHODOLOGY

The method of losses on network elements [6] is used. This consists in calculating the losses based on the loads

of the elements in the substation under different operating regimes and their technical characteristics.

The electricity losses in the substations are mainly determined by the electricity losses in the transformers. In the

case of load according to the load curve of the characteristic regime these losses are determined with the

following relationship:

2n

2max

scovar

Tconst

TTS

SPTPWWW [kWh] (1)

1 Corresponding author, email [email protected]

mailto:[email protected]


15

where: constTW - the loss of active electrical energy in core that is independent of the load, in [kWh] ; var

TW -

the loss of active electrical energy in coil which is proportional to the square of the load, in [kWh]; oP - no-load

losses of the transformer, in [kW]; scP - load losses of the transformer, in [kW]; nS - the nominal apparent

power of the transformer, in [kVA]; maxS - maximum apparent power calculated for the characteristic curve

load curve, in [kVA];T – the duration of the characteristic regime, in [h]; – loss time determined for the

curve load of the characteristic regime, in [h].

Maximum apparent power is calculated with the relationship:

2max

2maxmax QPS [kVA] (2)

where: maxP - maximum active power, in [kW]; maxQ - maximum reactive power, in [kVar].

The loss time is:

*T [h] (3)

where * is the loss factor determined by the following relationship:

2uu

* kp1kp (4)

where: p=0.2 is a coefficient determined statistically; uk is the fill factor of the load curve that is determined

with the next relation:

T

T

S

Sk max

max

medu (5)

medS is the average apparent power, in [kVA]:

T

WWS

2r

2a

med

(6)

maxT is the usage time of maximum apparent power maxS , in [h]

max

2r

2a

maxS

WWT

(7)

where: aW , rW the active electrical energy in [kWh] and reactive, respectively in [kVar], passing through the

transformer during the characteristic regime.

The calculation of the short-circuit currents on the 20 kV and 0.4 kV bus is done by the absolute unit method,

[7].

3. THE NUMERICAL RESULTS

A study of a substation has been carried out to improve its operating diagram according to the calculation

methodology presented above. It is a distribution substation with two 110/20 kV transformers, fig.1. On the 110

kV side, the connecting diagram of the substation is a double bus diagram with 14 cells. On the 20 kV side there

are double bus diagram in U with 19 cells. The internal services of the substation are supplied by 2 transformers

of 20 / 0.4 kV.


16

Fig.1. Single diagram of substation analyzed


17

The normal operating diagram in the summer regime is with transformer 1 (T1) in operation and transformer 2

(T2) in the reserve with automatic release of reserves (ARR). The normal operating diagram in the winter regime

is with T1 and T2 in operation, in radial diagram with ARR on transverse coupling. A transformer is used to

supply internal services, TSI1 because it has Peterson coil and TSI2 is in reserve with ARR. Monthly average

loads of the two transformers are shown in Figure 2.

To improve the operating scheme, simulations were made for the following cases:

1- Operation with only one transformer all year

2- Operation with a transformer in summer and with two transformers in winter, in radial scheme, with

different load coefficients

3- Operation with a transformer in summer and two transformers in parallel in winter

The loads of the two transformers for the three simulations are shown in Figure 3 and Figure 4.

Fig.2. Real loads of the two transformers

Fig.3. The loads of T1

Fig.4. The loads of T2


18

The annual electricity losses for different charging coefficients of the two transformers in winter period in case 2

are shown in Figure 5. It is seen that the smallest losses for the two transformers are obtained for a load

coefficient of 0.3 of the transformer T1.

The annual electricity losses for the three simulations for the optimum load factor of 0.3 of the transformer T1 in

simulation 2 are shown in Figure 6. It can be noticed that the lowest annual losses are obtained for the case of

operation with only one transformer, respectively T1 - summer and T2 - winter.

The short-circuit values, current and power, on the 110 kV, 20 kV and 0.4 kV bus for different operating regimes

are shown in Table 1. It is noted that the smallest values of short-circuit current and power are obtained for

operation with the transformer T1 and the internal service transformer TSI2. Because TSI2 is not a Peterson coil,

it cannot be used in the normal diagram but only as a reserve transformer.

Fig.5. Annual energy losses for simulation 2

Fig.6. Annual energy losses for the real situation and for simulations


19

Table 1. The short-circuit values

Point of

short-circuit Operation diagram Voltage, [kV]

Short-circuit current,

[kA]

Short-circuit power,

[MVA]

k1 110 16.4 3127.4

k2 T1 20 4.4 152.5

T2 20 7.1 246.2

T1//T2 20 10.8 376.0

k3 T1, TSI1 0.4 2.9 2.0

T2, TSI1 0.4 3.8 2.7

T1//T2, TSI1 0.4 4.7 3.3

T1, TSI2 0.4 2.7 1.8

T2, TSI2 0.4 3.5 2.4

T1//T2, TSI2 0.4 4.2 2.9

4. CONCLUSIONS

The analysis of the power station, done in this paper, in order to improve its operating diagram to obtain the

lowest electricity losses and the lowest values of the short-circuit current, highlighted the following conclusions:

- the lowest electricity losses are obtained in case of operation with only one transformer, respectively T1 in

summer and T2 in winter. It cannot be operated with T1 all year long because the winter requirement exceeds its

nominal power.

- the lowest short-circuit currents are obtained with T1 and TSI2 operation. However, since the Peterson coil is at

TSI1, it is proposed to operate with T1 and TSI1.

By using a performance improvement diagram, it can achieve annual savings of 93 MWh compared to the

normal operation diagram of the station.

REFERENCES

[1] John D. McDonald, Electric Power Engineering Handbook, Second edition, CRC Press Taylor & Francis

Group, US, 2006

[2] Hazi A., Hazi Gh., Statii electrice moderne, Editura Pim, Iasi, 2013

[3] ABB S.p.A. , Power Products Division, Technical guide The MV/LV transformer substations, 2015

[4] Dominik Pieniazek, P.E., HV Substation Design: Applications and Considerations, IEEE CED – Houston

Chapter, October 2-3, 2012

[5] Malafeev A., Iuldasheva A., Short-circuit failures simulation for evaluation of structural reliability of power

supply systems, Procedia Engineering 129, 2015, pp.433 – 439

[6] ***NTE 013/16/00, Normă tehnică energetică privind determinarea consumului propriu tehnologic în

retelele electrice de interes public

[7] ***PE 134/95, Normativ privind metodologia de calcul al curentilor de scurtcircuit în retelele electrice cu

tensiune peste 1 kV


20

3

CFD SIMULATION OF THE MATHEMATICAL MODELS OF THE INTERACTION

BETWEEN THE BLADES AND FLUID

BOSTAN VIOREL, BOSTAN ION, GUTU MARIN, RABEI ION, DULGHERU

VALERIU*

Technical University of Moldova, Chisinău, Republic of Moldova

Abstract: The effect of tip speed ratio (λ) or (TSR) has been examined for different chord

lengths. The equilibrium between TSR, chord length and type of chord is necessary to be

found in order to get a maximum coefficient of performance (Cp) for the wind turbine rotor.

Different chord lengths based on Wortman FX 63 137 and NACA 0018 are simulated for

different TSRs. This task is done using finite element analysis methods. In this scope, the

software ANSYS CFX was used. The simulation is done on the 3D CAD models of the

wind turbines. The blades of the turbines are based constructively on the chords mentioned

above. Also, by means of CFD analysis, it was evaluated the rotor’s performance equipped

with asymmetric airfoil blades (Wortman FX 63 137) when the blades are positioned with

camber in and out relative rotation axis. All CAE simulations were done using ANSYS

software. The Workbench Project schematic is presented in the appendix 1.

Keywords: wind turbine rotor, mathematical models, blades, coefficient of performance

1. INTRODUCTION

Wind energy has been used by mankind over thousands of years. For over 3000 years the windmills have been

used for pumping water or grinding (milling). And nowadays, in the century of information technologies, nuclear

energy and electricity, thousands of windmills are used for pumping water and oil, for irrigation and production

of mechanical energy to drive low-power mechanisms on different continents. Nowadays, the phrase “use of

wind energy” means, primarily non-pollutant electrical energy produced at a significant scale by modern

“windmills” called wind turbines, a term that attempts to outline their similarity to steam or gas turbines, which

are used for producing electricity, and also to make a distinction between their old and new destination.

The absolute majority of the sold turbines are with horizontal and vertical axis. In turbines with vertical axis the

wind direction is perpendicular to the axis of rotation, respectively, perpendicular to the ground surface.

Although vertical axis turbines have lost the competition, engineers come back again and again to this design

scheme, the main reason being the following two indisputable advantages [1]:

The generator, the multiplier and other functional components can be placed on the ground surface; the

gondola and massive tower are not required;

The turbine does not require a special device to track wind direction.

Unfortunately, the disadvantages of these turbines prevail compared to the advantages:

1. Wind speed in the adjacent to the surface layer is small. Thus, we save on tower construction, but lose

the power developed by the turbine.

2. Wind energy conversion factor into mechanical energy is lower.

3. Some types of turbines, such as the Darrieus or Evence turbines do not provide starting. An auxiliary

motor is required to start the turbine or a small turbine of Savonius type.

4. High power turbines need support cables, which considerably increase the occupied land area.

Replacing the main thrust bearing requires complete disassembly of the turbine.

___________________________ 1 Corresponding author, email [email protected]



21

2. 3D MODEL OF THE TURBINE AND SIMULATIONS’ SETTINGS

As determined in the previous report, the chords that are going to be used for the blades are Wortman FX 63 137

and NACA 0018. The effect of tip speed ratio (λ) or (TSR) has been examined for different chord lengths. The

equilibrium between TSR, chord length and type of chord is necessary to be found in order to get a maximum

coefficient of performance (Cp) for the wind turbine rotor. Different chord lengths based on Wortman FX 63 137

and NACA 0018 are simulated for different TSRs. This task is done using finite element analysis methods. In this

scope, the software ANSYS CFX was used. The simulation is done on the 3D CAD models of the wind turbines.

The blades of the turbines are based constructively on the chords mentioned above.

Also, by means of CFD analysis, it was evaluated the rotor’s performance equipped with asymmetric airfoil

blades (Wortman FX 63 137) when the blades are positioned with camber in and out relative rotation axis. All

CAE simulations were done using ANSYS software. The Workbench Project schematic is presented in the

appendix 1.

2.1. Fluid Domain Modeling and Meshing

The rotor geometry, designed using SolidWorks, was then imported into the ANSYS DesignModeler software.

The dimensions of the computational fluid domain were chosen taking into account the recommendations of [2]

so that the boundaries of the field do not influence the free flow of the air. The simulated fluid domain was

divided into two subdomains: the Stator (static) subdomain and the Rotor subdomain inside of it (of cylindrical

form, which rotates around its axis). Figure 1 shows the considered fluid domains.

Fig. 1. The fluid domains.

The mesh used later on for finite method analysis was generated using the ANSYS Meshing Workbench. This is

an integrated software that offers various meshing strategies. After importing the geometric model the following

regions were defined: (Inlet – the face with black arrows on the perimeter), (Outlet – the opposed face of the

Inlet), (Openings – the four side faces), and the common regions between Stator and Rotor (Fluid-Fluid). The

basic dimensions of the mesh are as follow: the minimal size of the inflation around the blade = 0.7 mm and the

maximum size of the side of one face = 220 mm (fig. 3).


22

The transition from the fine-meshed areas to the gross meshed ones was done by specifying the Growth Rate =

1.1 expansion factor. The maximum variation of the characteristic dimensions of two adjacent elements is not

bigger than 5%. The entire domain was meshed into approx. 4 200 000 finite elements.

The effects formed on the blades’ surfaces are very important because here it is where the lift and drag are

formed, boundary layer separation occurs and other important effects take place In order to obtain more accurate

results in the close proximity of the blades’ faces where the boundary layer forms, rectangular finite elements

have been generated by expanding them from the surface of the blade outwards [3]. This was done using

Inflation Layer technique around blades’ surfaces: Number of Layers = 9, the Growth Rate = 1.18 (relative

thickness between two adjacent layers), and Growth Rate Type = Geometric. Figure 2, (b) shows the mesh

details around the blade.

a

b

Fig. 2. Meshed fluid domain (a) and details of boundary layer around the blade (b).

2.2. Problem setup

Problem setup was done using CFD module of the ANSYS software. In order to verify the conversion efficiency

of the turbine, several modes have been simulated. To both airfoils are assigned different chord lengths and each

chord length is simulated under different tip speed ratios. The wind speed considered for simulations is 11 m/s.

The parameters of interest that were analyzed are presented in the table 1.

Table 1. Analyzed rotor parameters.

Airfoils Chord length, m Wind speed, m/s Tip speed ratios Rotational speed, min-1

NACA 0018

0.2; 0.3; 0.4 11

3 126

3.5 147

Wortman FX 63

137

4 168

4.5 189


23

2.3. Solutions and CFD Results for NACA

0018

The solving of discretized equations was

performed in parallel using all 16 logical cores.

The goal is to obtain 5 kW of power at a wind

speed of 11 m/s so we have to determine for

which chord length that is possible. The variable

of interest is the power output. More

specifically, the power output for each case

chosen is shown according to the table 1.

The simulations were carried. By analyzing the

results, the graphs in the figure 3 were obtained.

From here, one can notice that the maximum

power for this turbine is when the chord length

is equal to 0.3 m running at a rotational speed

of 168 rpm, which corresponds to a TSR of 4.

As mentioned, the maximum power

output of

4700 W is obtained for the chord

length of 0.3 m at 168 rpm. At the

same rotational speed, for the chord

length of 0.2 m the value of power is

1760 W and for the chord length of

0.4 m the power value is 3100 W.

One might guess that a maximum

power can be obtained for a chord

length between 0.3 and 0.4 m so we

made a simulation to find that out.

The simulation was carried for a

rotational speed of 168 rpm. The

results presented show that for the

chord length equal to 0.35 m the

power output is equal to 3700 W so it

decreases. We can conclude that the

optimal chord length for this turbine

is 0.3 m.

1. 2.4. Model development and

analysis of the downscaled

blade section

Fig. 3. The parameters of the 5 kW rotor at the wind speed

of 11 m/s for NACA 0018.

Fig 4. Downscaled blade segment


24

The downscaled blade segment

whose characteristics are analyzed in

the wind tunnel has the constructive parameters as shown in the figure 4. The segment has the same airfoil as the

blades for real wind turbine but scaled down 1:2. The segment has been obtained by 3D printing. After printing

the surfaces were smoothed so it minimizes the drag forces due to friction. Also on the two ends of the blade two

plates are mounted in order to reduce blade tip loses.

The results of the analysis of the blade segment are presented in the figure 5. One can notice that the maximum

performance of the blade, presented here in terms of Lift/Drag, is for an angle of attack 10 degrees. The

performance is not dependent on the wind speed

when their value is higher than 8 m/s. The

sensitivity of the blade is high when the wind

speed is lower than 8 m/s.

3. CONCLUSIONS

By experimental research there were determined

the performances of the downscaled blade

segment (scale 1:2) based on NACA 0018

airfoil in terms of Lift over Drag forces for

different wind speeds and for different angles of

attack.

The CFD simulation is applied on the

downscaled wind rotor in order to determine the

aerodynamic performances. The CFD model

applied here is the same as the one used for

simulating 5 kW wind rotor.

Experimental research on the built downscaled

wind rotor is to be carried out in the wind tunnel in order to determine the aerodynamic performances. The

results are to be compared with the ones obtained by CFD simulation using ANSYS CFX in order to validate the

CFD model used for simulating the 5 kW wind rotor.

REFERENCES

[1] Bostan I., Gheorghe A., Dulgheru V., Sobor I., Bostan V., Sochirean A. Resilient Energy Systems.

Renewables: Wind, Solar, Hydro. - Springer, VIII, 2013. - 507 p. – ISBN 978-94-007-4188-1

[2] Mohamed M. H., Ali A.M, Hafiz A. A. CFD analysis for H-rotor Darrieus turbine as a low speed wind

energy converter. Engineering Science and Technology, an International Journal. Volume 18, Issue 1, March

2015, Pp. 1-13.

[3] Bostan V. Modele matematice în inginerie: probleme de contact. Modelări si simulări numerice în aero-

hidrodinamică. Chisinău: S.n., 2014. 470p. ISBN 978-9975-80-831-6.

Fig 5. Blade segment performance determined in the wind tunnel.

Fig 6. 3D printed downscaled blade segment and tunnel

wind tunnel


25

4

MUTUAL INFLUENCES OF THE MODERN INFORMATION TECHNOLOGIES

AND ENERGETIC INDUSTRY

FLORENTIN PALADI1, VLADIMIR PRIMAC1

1Faculty of Physics and Engineering, Moldova State University, str. Alexei Mateevici, 60,

MD-2009, Republic of Moldova

Abstract: Blockchain, autonomous vehicles, 3D printing, and robotics are coming swiftly in our

daily life. All new inventions, systems and devices of information technologies can't work

without power. Even IT researches can't be performed without energy supply. At the same time

such essential progress in IT industry has increased energy consumption and motivated Energetic

Industry also to progress and invent new technologies. Even today's energy distribution is

impossible without information systems and automatic control.

The aim of this presentation is to explore the mutual influence of IT and Energetic Industries, and

identify the impact of potential mutual influences.

Keywords: information technologies, renewable energy, blockchain, smart grid, digitalization

1. INTRODUCTION

Impetuous evolution of Information technology industry leads to significant changes in Energetic sector.

Growing number of electronic devices, invention of new technologies, such as blockchain and electrical

vehicles, introduction of robots in industry and other domains leads to permanently growing of energy

consumption. Energetic industry also is one of beneficiary of IT progress, so it can provide needed amounts of

electrical power.

The digital progress significantly affects the power industry. Previous great steps in power industry were aimed

to develop hardware, which is capable to generate cheap or costless renewable energy. Next years the main

scope will be to improve energy generation systems and to make them smarter and more efficient.

According to the World Economic Forum, it is possible to generate $1.3 trillion by digitalizing electricity

generation worldwide in only 10 years - between 2016 and 2025 [1].

This digitalization lists 5 initiatives in particular:

- better management of asset performance

- real-time platforms data

- integration of energy storage

- customer-centric solutions

Significant changes in the power industry are long overdue. Networks used in power industry permanently

become much more complex. This is caused by progress in renewable energy power generation. Another factor

of influence to the networks is the increasing number of small or even individual distributed power producers.

Demand on power is increasing worldwide, but infrastructure is old and sometimes it is difficult to meet the

demand in new conditions. Used equipment is difficult and costly to maintain. But the positive thing is that

government and international regulations are driving the power industry to be much more efficient and cleaner.

Intervention of IT in power industry is expensive, but technology's ability to improve productivity can pay

dividends.


26

2. CONSUMPTION OF HUGE AMOUNT OF ENERGY BY IT INDUSTRY AND CAUSES OF THIS

The most energy-intensive segments of the world economy since the beginning of the industrial revolution are

metallurgy and heavy engineering. They are followed by chemical and oil refining complexes. But who would

have thought that information technologies can consume more power than is spent for the smelting of metals and

energy supply for the housing and communal services of megacities? According to analysts of the world IT

market, work with bitcoins that includes mining, storage and transactions, require as much electricity as is

consumed by almost all countries in the world. At the same time, if last year global energy consumption

amounted to about 300 TWh per hour, then by 2025 this energy volume could increase by 10 times, almost 3000

TWh per hour. And IT share in this volume will be approximately one fifth - 600 TWh that is twice more than

today's annual world energy consumption [2].

This is caused by the introduction of new and expansion of traditional information technologies, for example,

online education, e-commerce, fifth generation mobile communication (5G), Internet of Things (IoT), cloud

computing and storage systems (cloud data centers), artificial intelligence and, of course, rapid increase of smart

devices - their amount has already surpassed the population of the Earth, their data are stored in server farms,

which require huge amounts of energy. Obviously, slowing down, and especially stopping the development of

innovative IT tools and services, can be equated with crimes against humanity, because, according to the UN,

Information Technologies and the Internet in particular are not just valuable resources for ensuring people's

livelihoods, but also their inalienable rights.

But how to proceed if these goals require expanding the construction of energy-generating enterprises, which are

known to be the largest pollutants of the atmosphere? According to analysts of the online edition Climate Home

News, which owns the largest global network of correspondent points, billions of mobile devices used daily over

the next decade will cause emissions of 3.5% of the total amount of pollutants emanating from energy generating

companies, working on hydrocarbon energy carriers, and by 2040 this share will increase to 14%.

The answer is obvious: the development of alternative energy source, such as solar and wind power stations

(SES and VES), and of course smart energy management.

3. BLOCKCHAIN AND ENERGY SECTOR

Blockchain is a new technology developed to enable peer-to-peer transactions without an intermediary. This

technology can change the way we process/handle the transactions. New model has the scope to move away

from a centralized structure, (markets, exchanges, trading platforms, big companies) towards decentralized

systems, (end customers can interact directly) [3].

Outside of the financial sector, the energy sector is one of the industries which can be significantly affected by

blockchain invention.

One of the pilot projects of blockchain usage in energetics is implemented in Brooklyn, New York. There was

created a microgrid which consists of 10 houses. Five of them are equipped with solar panels. All unused energy

is sold to neighboring buildings. While all the buildings are still connected to the microgrid, transactions are

managed and stored on a blockchain. Usage of smart meters and blockchain technology allows easing

transactions between neighbors [4].

About 5% of energy is lost between power plant and our home. It is caused by location of power plant, which is

situated far away of living area. Power plants can't be located closer because of ecological reasons (coal and gas

stations) or security reason (nuclear energy). But renewable energy gives us opportunity to turn into source of

energy practically every building. We can equip our house with solar panels, heat pump, and wind turbine.

Initially grids were built to function only in one way: to transport amounts of energy from the producer to our

houses. But with renewable energy we can become not only consumers. We can sale surpluses of generated

energy.

But managing of real-time optimization of consumption and trading between neighbors requires complete update

of existing grid. It requires new technologies for track energy usage and digital payments. Such inventions are

named "smart grid".


27

Smart grids are modernized power grids that use information and communication networks and technologies to

collect information on energy production and energy consumption that automatically increases efficiency,

reliability, economic benefits, and the sustainability of production and distribution of electricity.

Blockchain can help us with all listed above processes - we are able to trade it directly with other consumers in a

peer-to-peer network.

4. THE INFLUENCE OF IT ON OIL AND GAS INDUSTRY

Oil and gas are the fuels which drive our world. Even with all the talk about renewable energy, these two

hydrocarbons are still the base of massive amount of electricity power in our world, give us possibility to travel

and keep us warm. But decreasing in the demand for this fuel in some regions of the world leads company to

decrease amounts of costs and expenses and to do technological processes more efficient.

4.1 Digital oilfields

One of the main steps in order to remain efficient on the market is to cut down operational costs. And

Informational Technologies is the best place to find such possibilities. The Modern computational and

modulation methods and fast processing systems in combination with huge amounts of useful data can help in

developing of "digital oilfields". Such invention gives possibility to engineers and geologists to simulate an

entire oilfield. These simulations are used in order to find the most optimal spots for oil and gas extraction with

minimum expenses in drilling and extracting maximum amounts during service. These informational analytics

reduces number of data operators, which reduces staffing costs and improves overall efficiency of the industry

[5].

4.2 New Oil and Gas fields’ exploration

In time all readily available sources begin to end. Nowadays it is becoming increasingly difficult to find new

reservoirs. Modern computers with pool of available data are able to find new reservoirs which were impossible

to find just several years ago.

4.3Distance doesn't matter

The amount of available reservoirs in areas close to ports and cities is permanently decreasing and it leads to

moving towards the trend of offshore drilling. Informational technologies are powering these extractions. There

is no need of big bases in remote areas and engineers, management and even doctors can contact workers

through video conferencing in remote areas instead of visiting them in any situation.

4.4 New approaches

Horizontal drilling and hydraulic fracturing can't be performed without support of IT industry. The Key to

success in this approach is it supports: 3D seismic modeling, cloud computing and big data.

4.5 Fuel technology conversions

Today it is said everywhere about harms of using hydrocarbons. But development of technologies, used to find

new sources of Oil and Gas can be easily transferred to the industries - to find and discover new mineral deposits

of useful rare metals [6].

5. CONCLUSIONS

This article has covered only a couple of aspects of IT influence over the energy sector. At the same time the

development of renewable energy also causes drastically changes in energy management which is performed by

information systems. This mutual influence will be increasing over the time and both industries will gain.


28

REFERENCES

[1]http://reports.weforum.org/digital-transformation/electricity-generating-value-through-digital-

transformation/ (10.05.2018)

[2]http://www.gadgetsshop.ru/2018/01/zelenaya-energetika-v-it-ili-kak-bitkoiny-vliyayut-na-

ekologiyu.html (08.05.2018)

[3] https://www.worldenergy.org/news-and-media/news/the-potential-for-blockchain-technology-in-the-

energy-sector/ (05.05.2018)

[4] https://richtopia.com/emerging-technologies/blockchain-renewable-energy-sustainability (14.05.2018)

[5] https://www.renewableenergyworld.com/articles/2018/02/blockchain-could-change-everything-for-

energy.html (10.05.2018)

[6] https://www.linkedin.com/pulse/importance-information-technology-oil-gas-industry-today-fred-

zillman/ (09.05.2018)

http://reports.weforum.org/digital-transformation/electricity-generating-value-through-digital-transformation/

http://reports.weforum.org/digital-transformation/electricity-generating-value-through-digital-transformation/

http://www.gadgetsshop.ru/2018/01/zelenaya-energetika-v-it-ili-kak-bitkoiny-vliyayut-na-ekologiyu.html

http://www.gadgetsshop.ru/2018/01/zelenaya-energetika-v-it-ili-kak-bitkoiny-vliyayut-na-ekologiyu.html

https://www.worldenergy.org/news-and-media/news/the-potential-for-blockchain-technology-in-the-energy-sector/

https://www.worldenergy.org/news-and-media/news/the-potential-for-blockchain-technology-in-the-energy-sector/

https://richtopia.com/emerging-technologies/blockchain-renewable-energy-sustainability

https://www.renewableenergyworld.com/articles/2018/02/blockchain-could-change-everything-for-energy.html

https://www.renewableenergyworld.com/articles/2018/02/blockchain-could-change-everything-for-energy.html

https://www.linkedin.com/pulse/importance-information-technology-oil-gas-industry-today-fred-zillman/

https://www.linkedin.com/pulse/importance-information-technology-oil-gas-industry-today-fred-zillman/


29

5

Power Management Strategies Based on Energy Storage Technologies - Review for

Future Implementations in Real-Time Emulators

MOHMED ASHGLAF, CRISTIAN NICHITA

University Le Havre Normandie

Research Group in Electrical Engineering and Automatics - GREAH

75 rue Bellot, 76058, Le Havre Cedex, France

Abstract— Electrical energy storage (EES) system has been a key for enabling complex power systems such as

smart grids and intermittent renewable power resources to be reliable. This paper presents an up-to-date

technical review for different energy storage systems. It synthesizes the main working principle of some storage

technology and highlighting the key advantages, disadvantages and main applications when integrated with

power systems. A review of recently studies has been investigated in the field of energy storage systems

integrated with power system. This review provide a guideline for further technological development and new

applications in order to improve the efficiency of wind/tidal real time emulators designed for renewable energies

research integrating the power supply systems.

Keywords - Storage Energy; Power Management; Real Time Emulators;

1. INTRODUCTION

In GREAH Laboratory researchers have developed a real time emulators for wind systems, represented in

Figure 1, and for tidal hybrid systems shown in Figure 2[1-2].

In order to optimize the generated power studies, energy storage units has to be be implemented.

Figure 1 Wind emulator in GREAH

We considered that this development should be done by firstly studying the new storage technologies that could

be implemented in our emulator structures, that's why we did this state of the art.


30

Figure 2 Tidal emulator in GREAH.

“Electrical Energy Storage project team” this “White” paper [3] has been prepared by Special Working Group on

technology and market watch, in the IEC Market Strategy Board, with a contribution from the Fraunhofer Institut

für Solare Energie systeme. This paper treated the main three roles of ESS in order to improve power quality by

maintaining frequency and voltage, reduce electricity cost and improve the reliability of power supply, also this

paper discussed in brief, present and future market needs for EES technologies, reviews their technological

features. While in [4] an up-to-date technical review for different types of ESS has been presented. Operation

principle of each storage technology, advantages, disadvantages and main applications explained when integrated

with power systems.

Authors in [5] addressed intensively ESS through the state-of-the-art technologies available, and where they

would be most fit in a power generation and distribution system. As well as, an overview of the main operation

principles, performance features the up-to-date research and development of most interesting EES technologies,

and ESS classification based on the types of energy stored has been illustrated. Finally, a overall comparison and

an potential analysis of the reviewed application technologies are presented. Another research in [6] also discusses

the multi types of storage technology, the development trend and the different applications of storage technology

in the power system. The need to store energy, various types of storage techniques and their field of application

has been described [7]. As well as, characteristics and comparison been presented in order to determine the most

appropriate technique for each type of application. The integration of energy storage systems within renewable

resources specifically wind resource was demonstrated in [8]. It simulated 1MWh of time, 1 to 9 hours of high and

low wind energy, and the main objective of this research was to find characteristics and the most suitable type of

energy storage system that can be used with such power generation system. The final result of this work shows

that, 67.80% of energy gained in high wind energy scenario, whereas 19% stored in low wind energy scenario.

Also, another research [9] in various energy storage technologies been analyzed and compared for marine

application, emphasize was given to the role of energy storage systems for reducing power fluctuation in

renewable energy sources.

However, in this paper, the most recent up-to-date research and development of EES are comprehensively

reviewed and meanwhile variants of different applications are categories based on power management strategies.

This paper is organized as follows: first section an introduction to energy storage systems. Second section talks

about ESS history, third section describes the application of ESS and its role in the power system, fourth section

describes the basic operation principle of ESS. Fifth section about the application of ESS in power system. Sixth

section compares between different types of ESS, and finally, conclusion of this literature review.

2. HISTORY OF ENERGY STORAGE SYSTEMS

Thermal energy storage system TESS is one of the oldest forms of energy storage systems in the world where ice

is harvested for food preservation and cooling purposes, in China cold water was injected into an aquifer.

Subsequently, it was noted that water had maintained it temperature for long period of time [10] Pumped hydro

energy storage systems PHS has existed for a long time – the first pumped hydro storage plants were used in Italy

and Switzerland in the 1890s.

The Wallace Dam Pumped Hydro Project was placed in full commercial operation in December 1980. In 1999

first seawater pumped hydro plant was built in Japan (Yanbaru, 30 MW) [3].


31

First fuel cell of about 2000 years old was discovered, near Baghdad, Iraq and it was first described by German archaeologist Wilhelm Koning. Then, the first step began when Emile Alphonse Faure invented and patented the so-called sticky plates in 1880; large scale production of lead-acid batteries was developed.

The next step was to increase storage capacity and electric power in battery. The most common used types of

batteries Lead-acid battery invented by Gaston Plante in 1859 at France and it is the oldest and most widely

used. Flow Battery FB invented by Lawrence Thaller in 1976 [11]. Hereafter summarized history of batteries in

table 1, [12].

Table 1 History of batteries

The first energy storage program was an integration of batteries with photovoltaic and wind energy systems in

1978, titled “Batteries for Specific Solar Applications” [13].

3. THE ROLE OF ENERGY STORAGE IN POWER SYSTEMS

The Energy Storage Systems (ESS) is a key component in the electrical generation and stability, energy storage is

one of the features of this century, where the need of energy increasing dramatically. Electrical interruption or its

instability is one of the big challenges at all levels of life and may cause a death to a patient in Intensive Care Unit

(ICU) or big losses in business. From this point of view, the need for storing energy becomes very essential to

save lives and money. Also, using energy storage system will decrease the gas combustion hence the gas emission

and reducing the environment pollution. The following graph shows the contribution of energy storage systems in

power demand and generation for different periods of time during the day [14]. As shown in Fig. 3&4, using ESS will improve the performance of power generation system from first step of

power generation, power transmission and finally the end user, these attractive vales that can be added by the ESS such as: i) reduce generation cost during peak demand periods, (ii) maintain continuous and flexible supply, (iii) management in power generation, (iv) improving power quality/ reliability, (v) help insertion of smart power grids.

Developer /

Inventor

Countr

y

Year Invention

Luigi Galvani Italy 1786 Animal

Electricity

Alessandro Volta Italy 1800 Voltaic Pile

John F. Daniell Britain 1836 Daniell Cell

Sir William Robert

Grove

Britain 1839 Fuel Cell

Robert Bunsen German 1842 Used liquid electrodes to

supply

electricity

Gaston Plante France 1859 Lead Acid Battery

Georges Leclanche France 1868 Leclanche Cell

Thomas Alva

Edison

United

states

1901 Alkaline/Accu

mulator

T.A. Edison & Waldemar ungner

U.S.A &

Sweden

1895-1905

Nickel-cadmium /

nickel-iron

Andre 1930 Silver/oxide

zinc cell


32

Figure 3 Effect of energy storage system in power generation and consumption [15]

Figure 4 Application of ESS in power system [15]

Batteries are classified as small-scale storage systems in low distribution system. More than 64% of the utilized capacity of batteries is used is take place in the emergency units in the hospitals. Besides that, several battery systems (19%) are located in the office building as show in Fig. 3.

With regard to the energy storage market, the high percentage (99%) capacity of installed storage is provide by plants of pumped hydroelectric as in Fig.4.

Figure 5 utilization of Battery as energy storage system [16]


33

Figure 6 Installed capacity of electrical storage systems [16]

4. BASIC THEORY OF ENERGY STORAGE SYSTEMS

4.1. Thermal Energy Storage Systems TES Thermal energy storage (TES) is a process of stocking excessive energy in a form of heat, by heating or cooling a storage medium so that the stored energy can be used later for heating and cooling applications and power generation. TES systems are used particularly in buildings and industrial processes [17], energy can be stored by means of TES depends on two basic principle, sensible heat (e.g. water, rock) and latent (e.g. water/ice, salt hydrates) [18].

Figure 7 Thermal energy storage system [19]

Main thermal storage techniques (Fig. 5):

Sensible Thermal Energy Storage

Underground Thermal Energy Storage (UTES)

Phase Change Materials for TES

Thermal Energy Storage via Chemical Reactions [17]

4.2. Pumped Hydro Storage System PHESS The PHS considered as a large scale storage unite represents about 99% of worldwide storage capacity, the main idea of PHES is to pump and store water at high levels during off-peak periods, and reuse it to operate power generation turbines during peak periods as shown in Fig.6. In another ward, store electric energy in another form of energy "hydraulic potential energy". Pumping and generating generally follow a daily cycle but weekly or even seasonal cycling is also possible with larger PHES plant [20].

The overall efficiency of this type of ESS can be determined by finding out the ratio of the energy used to pump up the water and produced energy. In addition, the period of storing and production is an important factor. The following two expressions used to find out the efficiency of the system: [21]

.g.h .vpumping

p

E

(1)

. . . .generator gE g hv (2)


34

4.3. Flywheel Energy Storage System FESS

In a very simple explanation the flywheel is made of a metal in cylindrical form, supported by magnetic bearing

located in vacuum chamber to reduce friction losses and connected to a rotor of generator/motor as in Fig.7.

Kinetic energy can be stored in the flywheel in rotation form [22]. The amount of stored energy depends on the

inertia and speed rotation of the flywheel. The energy absorbed and released by a rotating flywheel rotor [23]. The

kinetic energy that can be stored in flywheel according to the following equation:

21.

2E I (3)

Where: I: inertia momentum of the flywheel

Ω: angular speed There are some factors affect the maximum energy that can be stored in flywheel system, these factors can be

expressed in the following relation:

msp sE K

(4)

Where:

Esp: maximum specific energy density

σm: Maximum tensile strength of flywheel material

ks: Shape factor

ρ: Density of the flywheel material [24]

Figure 8 Flywheel energy storage system FESS [5]

4.4. Compressed Air Energy Storage System (CAES) The intermittency of wind was a main reason to use this technology, the excessive electrical energy used to operate series of air compressors, to store electrical energy in a form of compressed air in reservoirs or over ground tanks, in order to reuse it later in peak demand (Figure 9).

Figure 9 Compressed Air Energy Storage System CAES [5]


35

4.5. Batteries A battery storage system mainly composed of electrode, anode and electrolyte (Fig. 9) which can be at solid, liquid or ropy/viscous states, electrical energy can be stored in a form of controlled chemical reaction which reproduces electricity when it is needed "bi-directional convert of energy" [5]. In this category of ESS there are main common types of Batteries namely (Lead-acid battery, Sodium Sulfur battery, Lithium ion battery, Metal air battery, Flow battery) [25].

Figure 10 battery schematic [15]

A. Superconducting Magnetic Energy System SMES An SMES device is a dc current device that stores energy in the magnetic field. The dc current flowing through a superconducting wire in a large magnet creates the magnetic field [26]. The coil is made of Niobiumtitane (NbTi) filaments and cooled below its superconducting critical temperature, one of the attractive properties of SMES that it can be fully charged and discharged in a very short of time, and high value of energy can be stored in it (Fig. 10). The energy stored in the coil, E, is given by expression [27].

21.

2E L I (5)

Where: L inductance, & I current.

Figure 11 Superconducting Magnetic Energy System SMES [27]

4.6. Fuel Cell Energy Storage System FCESS Fuel cell based on the separation of water into its original components Hydrogen and Oxygen as shown in Fig. 11. Hydrogen is used to generate electricity; also it can be transported in portable cylinders or tanks and stored for long time. [28].


36

Figure 12 hydrogen storage and fuel cell [5]

5. CLASSIFICATION OF ENERGY STORAGE SYSTEMS

Electrical energy storage systems can be classified according to the energy storage principle into five categories as

shown in the following block diagram. However, storage systems can be classified also according to different

factors such as the period of charging and discharging: long period such as (high-energy batteries like sodium

sulfur battery and flow battery), and short period such as (super-capacitors and flywheels). In addition, another

classification can be done according to their load capacity as: low, medium and high storage capacity.

FigureError! Reference source not found. Classification of electrical energy storage systems

6. APPLICATION OF ESS

6.1. Electro-chemical Energy Storage Systems Hereafter a review - papers issued in this type of energy storage systems used as storage unit or compensator in renewable power generation systems. Some of the drawbacks facing the integration of energy storage into the grid been addressed and evaluated in [29] it demonstrated the main battery technologies for energy storage, identify their challenges, and provide perspectives on future directions. Found that, battery systems can offer a number of high-value opportunities and lower costs can be obtained.

This review includes: sodium-sulfur batteries that are commercially available for grid applications, redox-flow batteries that offer low cost, and lithium-ion batteries whose development for commercial electronics.

However, author in [30] treated power compensation via energy storage system (Flow Battery Storage FBS) as main objective. The flow battery (FBS) connected with thermal and hydro power plant; the function of suggested item FB is to maintain power plant output in balance state and at the predicted value. The proposed system modeled in MATLAB, the obtained results indicates that the system well balanced.

Also, Battery Storage System BSS in [31] considered as main part for efficiency improvement of water desalination unite supplied by renewable resource PV-wind turbine power generation system to eliminate the intermittently of required electrical power by the desalination unite as Fig. 12.


37

Figure 13 Hybrid energy source with Batteries

6.2. Thermal Energy Storage Systems In [32], the study focused on thermal storage energy (storing energy in a form of heat or cold). Compared with other forms of energy storage techniques specifically "Transfer energy pumping station" (STEP), which is a form of kinetic energy. Results show that, storing energy in this form is suitable for long-term, more efficient and less expensive than the other forms of energy storage systems. Whereas, storing energy in form of heat is more complex to be implemented and expensive. In [33] & [34], these two papers a literature review emphasize on the development of thermal energy storage systems in France. To provide higher storage energy, Phase Changing Materials (PCMs) types of materials used and because of their range of state change, applications in energy storage for heating and cooling purposes and its integration with power generation systems (Fig. 13).

Figure 14 Thermal station in France

6.3. Mechanical Energy Storage Systems

6.3.1. Pumped hydro storage system

The effect of pumped hydro storage system on fuel consumption in hybrid diesel power generator and wind

turbine has been detailed in [35]. The target of this research is to maximize wind turbine penetration in the power

grid of an island in Canada where pumped hydro energy storage system and battery bank been used to overcome

the problem of power instability and fuel consumption. System has been simulated in Simulink and results

indicate that using of hydro energy system with battery bank has a positive effect on wind energy penetration,

reduces the power fluctuation and fuel consumption. Consequently, emission of greenhouse gases reduced. In

[36], pumped hydro storage (PHS) is implemented to support the standalone hybrid solar-wind system connected

to a micro-grid. This paper addressed a new solution for the challenging task about energy storage. Results

indicate that the intermittent nature of the renewable resources can be compensated by introducing the PHS

technology.

6.3.2. Flywheel energy storage system


38

Authors in [23] analyzed the maximum energy storage and energy sufficiency of flywheel, results indicates that

there is still a part of the energy even when FESS doing the effective energy output, so Lead acid-battery will be

combined with FESS to form hybrid energy storage system.

This hybrid energy storage system will be installed in a grid and non-grid wind power generation system; results

obtained indicate that using such hybrid system would be effective and efficient to store energy with high

efficiency.

6.3.3. Compressed Air Energy Storage System In [37]-[38], two cases of studies were carried out in Germany and Denmark 2007, 2009 respectively, to

investigate the feasibility and contribution of CAES in wind power generation. Both obtained results indicate

that, the use of such energy storage system will be efficient and feasible in case of large-scale power generation

systems only. A state-of-art addressed the working principles, current researches and developments of CAES, as

well as over view of geological study of underground cavern for CAES in [39]. Besides that, study of

characteristics and feasibility, application and challenges faced this type of energy storage system has been

carried out. The final conclusion drawn from this study shows that, CAES efficiency and performance has a

direct relationship with the scale of the production unit.

A small- compressed air energy storage system proposed as a conventional concept of an integrated induction

generator (IG) in [40]. The system consists of 3 main components: air compressor, energy storage system and

power generation. IG is used to produce electrical energy. Thus, there is no fuel will be burned and no pollution.

This research addressed the modeling and simulation to obtain the characteristics of the new concept of CAES

power plant, which can be helpful in system designing of renewable energy conversion. 6.4. Electrical Energy Storage Systems An overview of the SMES technology and their applications in electrical power and energy systems carried out in

[26]. The SMES has been classified into three main groups (Thyristor-based SMES, voltage-source converter-

based SMES, and current-source-converter-based SMES). Due to the instability of the resources of renewable

energy, ESS is needed to be used in order to mitigate power fluctuation in power systems. In [41], SMES been

used to stabilize and control power generated by wind turbine, the dynamic performance of the suggested systems

is fully validated by computer simulation. The obtained result proved the efficiency of such storage unit to

stabilize the system efficiently and quickly. While in [42] the SMES is used to improve automatic generation

control (AGC) of interconnected hydrothermal power generation system. From the dynamic performance analysis

noticed that, SMES is an effective to follow the disturbance in the system and improves the dynamic performance

of the system. Wind power farm connected to the grid and energy storage technologies (fuel cell and super

capacitor) via DC /AC inverter in [43], for mitigating the output fluctuation. The system has validated with

simulation in MATLAB 7 and the results obtained was satisfying. The use of ESS was effective to overcome the

problem of long-time and short-time power fluctuation.

6.5. Chemical Energy Storage Systems

The literature of hybrid fuel cell and micro-turbine generation system has been presented in [44], to detail all the

various issues related to their interconnection, operation and control connected to the power distribution

network. In [45], a Hydrogen Energy Storage system (HES) model and thermally compensated electrolyser

proposed to support RES integrated into power grid. The developed model simulated in MATLAB/SIMULINK,

evaluated and compared with operated real power system, found that, this model is not suitable at high pressures.

An overall survey addressed hydrogen energy storage system, from hydrogen production, electrical generation

from renewable power sources, to hydrogen storage in various conditions and states, as well as the state-of-the-

art and the future development of individual technology is also discussed in [46]. A hydrogen storage system

[47] is used to overcome the problem of power fluctuation in a micro-grid renewable power system consists of

wind turbine and photovoltaic generators, the obtained result indicates the effectiveness of such storage system

in hybrid power generation to mitigate the power fluctuation. In [48] a case study of a hydrogen energy storage

system integrated with a wind power generation system connected to operation power grid the UK. The purpose

of this study is to evaluate and assess the contribution and effect of hydrogen storage system on the performance

of intermittent renewable energy resources RES, positive impact been noted on the performance of the power

system. Also, in [49] a hydrogen storage management system integrated with offshore wind farm for

compensating when there is a power shortage due to the instability of the wind speed. System has been simulated

and verified its efficiency and feasibility; the obtained results indicate that the suggested control strategy system

more flexible to satisfy the grid operation. [50] In this study a hydrogen storage system integrated with stand-


39

alone hybrid renewable power generation system composed of PV, wind turbine and fuel cell, the aim of this

study to control design and power management. MATLAB/SIMULINK being used to simulate the proposed

system, obtained results show that efficient power management has been achieved.[51] The paper focuses on the

hybridization of a wind turbine as main power unite fuel cell (FC) and ultra-Capacitor (UC) systems as make up

power generation stand-alone system. As the wind turbine output power changes with the wind speed: an FC

storage system with a UC bank can be integrated with the wind turbine to avoid power fluctuation in the system.

A dynamic model, In MATLAB/Simulation and Sim-power software design and simulation of a wind/FC/UC

hybrid power generation system with power flow controllers proposed. This hybrid topology shows excellent

performance under variable wind speed and load power requirements.

7. GENERAL COMPARISONS BETWEEN DIFFERENT ENERGY STORAGE SYSTEMS

The comparison between energy storage systems depends on the purpose of energy storage, and frequency of use

as well as the location. Actually, it is difficult to find storage unit that meet all the power system requirements.

Therefore, it is not easy to compare between different devices. But always there are general factors that can be

considered to be used as a balance to find out most fit in a particular situation. The common factors or points are:

Costs, density of energy, specific power, recyclability, Accessibility, durability energy efficiency [52-53].

The high efficiency and long lifetime are the main advantages for thermal and electrical energy storage systems.

While mechanical is normally has high power and capacity but the initial cost is high as well.

The summery of advantages and disadvantages of energy storage technologies classification has details in Table

1. In more details, the pumped hydro energy storage system has the highest rated the longest lifetime but with

less power density. Lead acid batteries are commonly used in wind and solar energy applications. It is suitable

choice for application required high output charging efficiency and acceptable cost. The intensive technical

comparison for several EES systems has shown in Table2.

Table1 Main advantages and disadvantages of classified EES

Table2 Comparison of technical characteristics of EES systems

8. CONCLUSION

ESS Main Advantages Main Disadvantages

Electrochemical High efficiency short storage period

Mechanical High capacity and power high costs ( initial investment)

and Special site requirement

Chemical Long storage period Low efficiency

Thermal High efficiency and long

lifetime

High production cost, Requires

special charging circuit

Electrical High efficiency and long lifetime

Low Energy Density

ESS Wh/kg Power rating Discharge time Suitable storage

duration

Life time

(years)

Capital cost

$/kW

PHES 0.5–1.5 100–5000 MW 1–24 h+ Hours–months 40–60 600–2000

CAES 30–60 5–300 MW 1–24 h+ Hours–months 20–40 400–800

Lead-acid 30–50 0–20 MW Seconds –hours Minutes–days 5–15 300–600

Fuel cell 800–10,000 0–50 MW Seconds –24 h+ Hours–months 5–15 10,000+

Solar fuel 800–100,000 0–10 MW 1–24 h+ Hours–months – –

SMES 0.5–5 100 kW–10 MW 1 ms– 8 s Minutes–hours 20+ 200–300

Flywheel 10–30 0–250 kW 1 ms–15 min Seconds–minutes ∼15 250–350

Super

capacitor 2.5–15 0–300 kW 1 ms – 60 min Seconds–hours 20+ 100–300


40

Power generated by renewable resource, cannot be continuous and provide immediate response to the demand

side. Thus, the store of energy becomes much needed, in order to store excessive produced power for later use

when it is needed in the demand side, and to avoid power fluctuation in power systems. Many studies and

technical reviews has been done in this field discussing ESS advantages, disadvantages, development trend and

the different applications of storage technology in the power system are presented in this article.

This study of energy storage systems is done to improve the efficiency of power systems emulators for renewable

energies and thus to extend the research works in this area.

REFERENCES

[1] Cristian Nichita, Mohamed Ashglaf, Jerry Tekobon "Etude préliminaire d’un concept de couplage

éolien-hydrolien utilisanr des similitudes fonctionnelles d’emulation en temps réel”. International Congress on

Energy and Environment, 18-19 March 2018, Fez, Maroco.

[2] Jerry TEKOBON, « Système multi physique de simulation pour l’étude des réseaux électriques

intégrant la production distribuée de ‘énergie basée sur le couplage éolien offshore – hydrolienne », Thèse de

l'Université Le Havre Normandie, décembre 2016.

[3] Alamri B. R. and Alamri A. R., "Technical review of energy storage technologies when integrated with

intermittent renewable energy," in International Conference on Sustainable Power Generation and Supply,

Nanjing, 2009.

[4] Xing Luo,Jihong Wang, Mark Dooner, Jonathan Clarke "Overview of current development in electrical

energy storage technologies and the application potential in power system operation," Applied Energy Volume

137, no. ELSEVIER, p. 511–536, 2015.

[5] Xuesong Zhou, Yitong Lin, Youjie Ma "The overview of energy storage technology", IEEE

International Conference Mechatronics and Automation (ICMA), pp. 336-338, Aug 2014.

[6] H. Ibrahima, b, A. Ilincca, J. Perron "Energy storage systems—Characteristics and comparisons,"

Renewable and Sustainable Energy Reviews, p. 1221–1250, 2008.

[7] Andor Daniela, "Energy Storage Systems for Wind Energy Integration. Technology, Applications, and

Benefit Analysis," university DE LA RIOJA, 2015.

[8] Zhibin Zhou, Mohamed Benbouzid, Jean Frédéric Charpentier, Franck Scuiller and Tianhao

Tang"Energy Storage Technologies for Smoothing Power Fluctuations in Marine Current Turbines,"

http://ieeexplore.ieee.org/, 2012.

[9] Morofsky, Edward, Thermal Energy Storage for Sustainable Energy Consumption, Quebec: Springer,

2007.

[10] Bent Sørensen- Roskilde University, Denmark- Roskilde University, Solar Energy Storage, Academic

Press, Jun 3, 2015 .

[11] Gogus, Yalcin, ENERGY STORAGE SYSTEMS, vol. volum III, Oxford: EOLSS, 2009.

[12] «http://www.sandia.gov/ess/energy-storage-systems-history/,» [En ligne].

[13] Whittingham, M. Stanley, "History, Evolution, and Future Status of Energy Storage," vol. 100, pp.

1518-1534, 2012.

[14] Haisheng Chen, Thang Ngoc Cong, Wei Yang , Yongliang Li, Yulong Ding, "Progress in electrical

energy storage system: A critical review," Progress in Natural Science, vol. 19, no. ScienceDirect, p. 291–312,

2009.

[15] Christian Doetsch, Bert Droste-Franke, Grietus Mulde, Yvonne Scholz,Marion Perrin, «Electrical

Energy Storage Future Energy Storage Demand,» 2015.

[16] Andreas Hauer (ZAE Bayern), "Thermal Energy StorageTechnology Brief," IEA-ETSAP and IRENA©

Technology Brief, E 17, January 2013.

[17] Ibrahim Dincer and Marc A.Rosen, THERMAL ENERGY STORAGE systems and Applications, West

Sussex: JOHN WILEY & SONS, LTD, 2002.

[18] CALMAC , 2014. [Online].

[19] J.P. Deane, B.P. O´ Gallacho´ir, E.J. McKeogh "Techno-economic review of existing and new pumped

hydro energy storage plant," Renewable and Sustainable Energy Reviews, p. 1293–1302, 2010.

[20] J.I. San Martín, I. Zamora, J.J. San Martín V. Aperribay, P. Eguía, "Energy Storage Technologies for

Electric Applications," 2011.

[21] Bjorn Bolund, Hans Bernhoff, Mats Leijon, "Flywheel energy and power storage systems," Renewable

and Sustainable Energy Reviews, p. 235–258, 2007.

[22] Qianzhi Shao, Yan Zhao, Shipeng Du and Yuanzhuo Du, "A Novel Hybrid Energy Storage Strategy

Based on Flywheel and Lead-acid Battery in Wind Power Generation System," International Journal of Control

and Automation Vol. 8, No. 7, pp. 1-12, 2015.


41

[23] Malte Krack1, Marc Secanell, and Pierre Mertiny, "Rotor Design for High-Speed Flywheel Energy

Storage Systems," 2011.

[24] K.C. Divya∗, 1, Jacob Østergaard1 "Battery energy storage technology for power systems—An

overview," Electric Power Systems Research 97, p. 511–520, (2009).

[25] Mohd. Hasan Ali, Bin Wu, and Roger A. Dougal, "An Overview of SMES Applications in Power and

Energy Systems," IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, pp. 38-47, APRIL 2010.

[26] Edward, Barbour, "Superconducting Magnetic Energy Storage (SMES)," Energy Storage Sense.

[Online].

[27] Schiller, Mark, "Hydrogen Energy Storage: A New Solution To the Renewable Energy Intermittency

Problem," 2016.

[28] Bruce Dunn, Haresh Kamath,Jean-Marie Tarascon, «Electrical Energy Storage for The grid: ABattery

of Choices,» Science 334, pp. 928-935, 2011.

[29] Linas Gelažanskasa, Audrius Baranauskasb, Kelum A.A. Gamagea, Mindaugas Ažubalisb, "Hybrid

wind power balance control strategy using thermal power, hydro power and flow batteries," International Journal

of Electrical Power & Energy Systems, pp. 310-321, 2016.

[30] Gude, Veera Gnaneswar, "Energy storage for desalination processes powered by renewable energy and

waste heat sources," Applied Energy, p. 877–898, 2015.

[31] NGÔ, Christian"Stockage de l’énergie," techniques de l'ingenieur, pp. 1-27, 10 juillet 2016.

[32] Atul Sharma, V.V. Tyagi, C.R. Chen, D. Buddhi, "Review on thermal energy storage with phase change

materials and applications," Renewable and Sustainable Energy Reviews Volume 13, Issue 2, p. 318–345, 2009.

[33] Francis Agyenim, Neil Hewitt, Philip Eames, Mervyn Smyth, "A review of materials, heat transfer and

phase change problem formulation for latent heat thermal energy storage systems (LHTESS)," Renewable and

Sustainable Energy Reviews volume 14, p. 615–628, 2010.

[34] M.R.H.Asif, M.T.Iqbal, "Diesel consumption in a high penetration remote hybrid power system with a

pumped hydro and battery storage," Electrical Power & Energy Conference (EPEC), 2013.

[35] Tao Ma, Hongxing Yang, Lin Lu, Jinqing Peng, "Technical feasibility study on a standalone hybrid

solar-wind system with pumped hydro storage for a remote island in Hong Kong," Renewable Energy, pp. 7-15,

2014.

[36] Swider, Derk J., "Compressed Air Energy Storage in an Electricity System With Significant Wind

Power Generation," IEEE Transactions on Energy Conversion Volume 22, pp. 95 - 102, 20 February 2007.

[37] Henrik Lund, Georges Salgi, "The role of compressed air energy storage (CAES) in future sustainable

energy systems," Energy Conversion and Management, p. 1172–1179, 5 March 2009.

[38] XING LUO, JIHONG WANG, "Overview of current development in compressed air energy," European

Energy Research Alliance EERA, COVENTRY CV4 7AL, UK, 2013.

[39] Varin Vongmanee, Veerapol Monyakul, "A new concept of small-compressed air energy storage

system integrated with induction generator," International Conference on Sustainable Energy Technologies,

2009.

[40] Marcelo Gustavo Molina, Pedro Enrique Mercado, "Power Flow Stabilization and Control of Microgrid

with Wind Generation by Superconducting Magnetic Energy Storage," IEEE Transactions on Power Electronics,

no. 3, pp. 910 - 922, 06 December 2010.

[41] Rajesh Joseph Abraham, D. Das, Amit Patra, "Automatic generation control of an interconnected

hydrothermal power system considering superconducting magnetic energy storage," International Journal of

Electrical Power & Energy Systems, vol. 29, 2007.

[42] Bhingare, D. K.; Virulkar, V. B., "Integration of energy storage technology and wind generator for

power stabilization," Power, Automation and Communication (INPAC),International Conference on, no. IEEE,

pp. 1-5, 2014.

[43] Sanjeev K Nayak, D. N. Gaonkar, "Modeling and performance analysis of hybrid fuel cell and

microturbine based distributed generation system, “A review”," International Conference on Power, Energy and

Control (ICPEC), no. IEEE Conference, pp. 760-766, 2013.

[44] Dallia Ali, Ross Gazey,Daniel Aklil, "Developing a thermally compensated electrolyser model coupled

with pressurised hydrogen storage for modelling the energy efficiency of hydrogen energy storage systems and

identifying their operation performance issues," Renewable and Sustainable Energy Reviews, pp. 27-37, 2016.

[45] Fan Zhang, Pengcheng Zhao, Meng Niu, Jon Maddy, "The survey of key technologies in hydrogen

energy storage," International Journal of Hydrogen Energy, vol. 41, p. 14535–14552, 2016.

[46] S. Tamalouzt, N. Benyahia, T. Rekioua, D. Rekioua, R. Abdessemed, "Performances analysis of WT-

DFIG with PV and fuel cell hybrid power sources system associated with hydrogen storage hybrid energy

system," International Journal of Hydrogen Energy, 2016.


42

[47] Ali, Dallia Morsi, "Energy capacity and economic viability assessment of the renewable hydrogen

energy storage as a balancing mechanism in addressing the electric system integration issues inherent with

variable renewable energy resources," in Reliability of Transmission and Distribution Networks (RTDN 2011),

IET Conference on, London, 2011.

[48] Dante Fernando Recalde Melo, Le-Ren Chang-Chien, "Synergistic Control Between Hydrogen Storage

System and Offshore Wind Farm for Grid Operation," IEEE Transactions on Sustainable Energy, no. 1, pp. 18-

27, 2014.

[49] Milana Trifkovic, Mehdi Sheikhzadeh, Khaled Nigim, Prodromos Daoutidis, "Hierarchical control of a

renewable hybrid energy system," 51st Annual Conference onDecision and Control (CDC),E, 2012.

[50] O.C. Onar, M. Uzunoglu, M.S. Alam, "Dynamic modeling, design and simulation of a wind/fuel

cell/ultra-capacitor-based hybrid power generation system," Journal of Power Sources, no. ELSEVIER, pp. 707-

722, 2006.

[51] Kuphaldt, Tony R., "Lessons In Electric Circuits Volumme I-DC," 2006. [Online].

[52] Casey, Tina, "Flow Battery Vs. Tesla Battery Smackdown Looming," 2015. [Online].

6


43

6

PROPOSALS TO IMPROVE THE OPERATING REGIMES OF

A GAS TURBINE PLANT

VERNICA SORIN-GABRIEL12, HAZI ANETA1, HAZI GHEORGHE1, GRIGORE

ROXANA1

1 “Vasile Alecsandri” University of Bacau, Calea Mărăşeşti 157, Bacau, 600115, Romania

Abstract: In this paper are shown the experimental data and results of the operating

regimes related to a gas turbine plant with heat recovery. Is present the thermal scheme and

the real parameters of the plant, underlying the experimental determinations. Both the

energetic analysis and the exergetic analysis are carried out of the whole ensemble studied.

Keywords: gas turbine, exergetic analyze, recovery boiler, cogeneration index

1. INTRODUCTION

Experimental analyze was performed on 130 gas turbine plant (GTP) Titan group of 14.3 MW and on a recovery

boiler of 22 MW [1,2-11]. To meet the proposed objectives, it was carried out the processing procedure of the

experimental data by implementing the calculate relations in the electronic program Engineering Equation Solver

(EES).

2. INTERPRETATION OF EXPERIMENTAL RESULTS AND THEIR COMPARISON WITH

THEORETICAL RESULTS

The thermal scheme of the GTP with heat recovery is presented in Figure 1. Operating regimes are characterized

by two categories of measured parameters:

- the parameters imposed by the operation of the gas turbine plant in the National Energy System and the city’s

heating network – electric power (PITG) and thermal power taken up by the water that is heated in the recovery

boiler ( aQ );

- the meteorological parameters – air temperature at the air filter inlet ( 0t ) and the atmospheric pressure specific

to Bacau ( 0p ).

In table 1 are presented the values of the calculated measures.

For the operating regime of the cogeneration plant, at electric powers between 12802 ÷ 14040 [kW] and constant

water flow (0.72 Dn [kg/s]), there is a trend towards increasing the thermal power ( aQ ) by decreasing the

atmospheric temperature ( 0t ), which does not decisively influence the stability of gas turbine operation.

Is highlighted the fact, that the cogeneration index (y) has an increasing trend at decreasing the air temperature at

the AF inlet.

2 Corresponding author, email [email protected]



44

For all intervals of exergy values corresponding to the electric power in which it operates the gas turbine plant

with heat recovery, at constant water flow, is highlight an increase of heat exergy supplied in the district heating

network ( ,P CREx ) with the decrease of the air temperature at the AF inlet ( 0t ).

Unlike the experimental results obtained for thermal power 0aQ f t , those considering the second principle

of thermodynamics concludes the scientific importance of exergy analysis.

Fig.1. Thermal scheme of GTP: AF – air filter; AK – air compressor; CC – combustion chamber; GT – gas

turbine; EG – electric generator; GB – gear box; RB – recovery boiler, GK – gas compressor, 1,2, ...,7 –

characteristic points.

Table 1.The determined parameters of GTP with heat recovery

No. crt. aQ

[kW]

PITG

[kW] y

,P CREx

[kW]

ITGPEx

[kW]

1. 20699.6278 13740 0.6638 3948 14165

2. 19548.0017 13934 0.7128 3884 14365

3. 19913.6265 14040 0.705 4062 14474

4. 19703.3941 13971 0.7091 4044 14403

5. 19675.9803 13966 0.7098 4038 14398

6. 20398.0362 13949 0.6838 4183 14380

7. 21677.4216 14017 0.6466 4457 14451

8. 21631.7305 13942 0.6445 4322 14373

9. 21348.4765 13838 0.6482 4152 14266

10. 20845.8562 13195 0.633 3697 13603


45

11. 20260.9403 12903 0.6368 3465 13302

12. 18935.5344 12802 0.6761 3138 13198

No. crt. t EL ex KA Dair

[kg/s]

1. 0.3406 0.3173 0.4268 16.639 50.06

2. 0.3669 0.3418 0.4568 15.645 47.35

3. 0.3598 0.3351 0.4515 15.958 48.2

4. 0.3622 0.3374 0.4546 15.775 47.7

5. 0.3628 0.3379 0.4552 15.75 47.63

6. 0.347 0.3232 0.4389 16.37 49.32

7. 0.3245 0.3023 0.4161 17.456 52.26

8. 0.3254 0.3031 0.4148 17.417 52.16

9. 0.3296 0.3071 0.417 17.183 51.53

10. 0.3283 0.3058 0.4092 16.776 50.44

11. 0.3336 0.3108 0.4121 16.303 49.16

12. 0.3603 0.3357 0.437 15.175 46.09

Experimental results for thermal efficiency ( t ) and electric efficiency ( EL ) of GTP, in function of air

temperature at the air filter inlet, are in accordance with theoretical results.

Experimental results for exergetic efficiency, in function of atmospheric air temperature, are in accordance with

theoretical results, which validate the calculation mathematical model (table 2).

Table 2.Comparison between theoretical and experimental results for exergetic efficiency of the GTP with heat

recovery

t0 [°C] ex [%], theoretical ex [%], experimental

10 47.071 46.63

15 46.008 45.21

20 44.944 44.05

25 43.879 43.37

Dependences ( )t KAf , ( )EL KAf with temperature (t3 [°C]) and air mass flow at the AK inlet (Dair

[kg/s]) as parameters, revels the fact that those two considered efficiencies have maximum values at optimal

compression ratios. Dependence ( )ex KAf with temperature (t3 [°C]) and air mass flow at the AK inlet (Dair

[kg/s]) as parameters, revels the fact that the exergetic efficiency of gas turbine plant with heat recovery have

maximum values at optimal compression ratios.

3. CONCLUSIONS

In the first part of this paper were presented the experimental results of the operating regimes of the GTP with

heat recovery.

For the experimental study of the cogeneration plant were represented the dependences for the thermodynamic

parameters of the working fluids in the operating characteristic regimes, for the exergetic flows and for thermal

efficiency, electric efficiency and exergetic efficiency of the GTP with heat recovery.

The experimental results for thermal efficiency, electric efficiency and exergetic efficiency are in accordance

with the theoretical results of optimization in the frame of the mathematical model propose.


46

REFERENCES

[1] Najjar, Y.S.H., Efficient Use of Energy by Utilizing Gas Turbine Combined Systems, Applied Thermal

Engineering 21, Elsevier Ltd., 2001, p.407-438.

[2] Franco, A., Casarosa, C., On Some Perspectives for Increasing the Efficiency of Combined Cycle Power

Plants, Applied Thermal Engineering 22, Elsevier Ltd., 2002, p.1501-1518.

[3] Pilavachi, P.A., Power Generation with Gas Turbine Systems and Combined Heat and Power, Applied

Thermal Engineering 20, 2000, p.1421-1429.

[4] Barbu, E., Petcu, R., Silivestru, V., Vilag, V., Centrale termoelectrice cogenerative cu turbine cu gaze,

Tehnologiile energiei, nr.4, ISSN 1842-7189, 2007.

[5] Afgan, N.H., Carvalho, M.G., Pilavachi, P.A., Tourlidakis, A., Olkhanski, G.G., Martins, N., An Expert

System Concept for Diagnosis and Monitoring of Gas Turbine Combustion Chambers, Applied Thermal

Enginnering 26, Elsevier Ltd., 2006, p.766-771.

[6] Cai, R., Jiang, L., Analysis of the Recuperative Gas Turbine Cycle with a Recuperator Located Between

Turbines, Applied Thermal Engineering 26, Elsevier Ltd., 2006, p.89-96.

[7] Kong, X.Q., Wang, R.Z., Huang, X.H., Energy Optimization Model for a CCHP System with Available Gas

Turbines, Applied Thermal Engineering 25, 2005, p.377-391.

[8] Ebadi, M.J., Gorji-Bandpy, M., Exergetic Analysis of the Turbine Plants, International Journal Exergy,

Volume 2, No.1, 2005, p.31-39.

[9] Panait, T., Exergoeconomia sistemelor termoenergetice, Editura Fundaţiei Universitare „Dunărea de Jos”,

Galaţi, 2003.

[10] Najjar, Y.S.H., Alghamdi, A.S., Al-Beirutty, M.H., Comparative Performance of Combined Gas Turbine

Systems Under Three Different Blade Cooling Schemes, Applied Thermal Engineering 24, Elsevier Ltd., 2004,

p.1919-1934.

[11] Ganesan, V., Gas Turbines, Second Edition, Tata McGraw-Hill Publishing, New Delhi, p.636, 2003.


47

7

ASPECTS RELATED TO THE UTILIZATION OF GEOTHERMAL ENERGY FOR

THE PRODUCTION OF ELECTRICITY IN ROMANIA

ROXANA GRIGORE12, SORIN-GABRIEL VERNICA1, MIHAI PUIU-BERIZINȚU1,

SILVIU IFTIME1

1 “Vasile Alecsandri” University of Bacau, Calea Mărăşeşti 157, Bacau, 600115, Romania

Abstract: In the energy field, European Commission proposes the next targets to 2030:

40% reductions in greenhouse emissions, at least 27% improvements in energy efficiency

and at least 27% share of renewable energy. Geothermal energy is a renewable energy,

defined as “energy stored in the form of heat under the surface of the earth” (EGEC). In

2017, 3% of the total electricity generated in the world was produced based on the use of

geothermal energy. In Europe, geothermal energy is widely used in Iceland, and geothermal

plants can also be found in Turkey, Italy, France, Germany. In Romania, where geothermal

sources reach a temperature of up to 125oC, geothermal energy usage is divided into the

following categories: 37% for heating, 30% for agriculture (greenhouses), 23% for

industrial processes, 7% for other purposes. This paper presents the opportunity of using

geothermal energy for electricity production in Romania.

Keywords: geothermal energy, electricity, binary cycle geothermal power plant

1. INTRODUCTION

Starting from specialist general assumptions, geothermal energy is the Earth’s heat which can be utilized by

humankind as an energy source. The Earth is made up of crust, mantle and core, as in Fig. 1. The temperature of

the earth increases with depth, in the inner core reaching more than 4500oC [1]. Although the Earth’s thermal

energy is immense, only the thermal energy of the crust being estimated of the order of 5.4 x 1021 MJ, the

geological conditions and current technologies do not allow it to be fully exploited [2], [3].

Geothermal energy is considered a renewable resource of energy due to the ability of the earth to produce

magma, and due to the continuous heat transfer between subsurface rock and water [4]. At the same time,

geothermal energy is considered clean, because during the exploitation, it does not generate waste. The

geothermal fluid which is brought to the surface is injected back into the ground [1]. Geothermal energy

contributes to reduced global warming effects and its deployment helps reduce a country’s dependence on fossil

fuels.

The geothermal energy has been used from ancient times, for bathing or for space heating. In our time,

geothermal energy is utilized for different applications like: heat and electricity production, industrial processes,

water heating in fish farming, desalination and agricultural applications (greenhouses, drying of plants, etc.).

The Earth’s thermal energy is brought to the surface and, with the help of various technologies, is converted into

an energy-efficient resource for the people. Technologies and uses depend on the thermodynamic proprieties of

the geothermal fluids. A generally accepted classification divides geothermal resources into: low, intermediate

and high enthalpy resources. According to Muffler and Cataldi, the temperature for low enthalpy geothermal

fluid is under 90oC, the temperature for intermediate enthalpy geothermal fluid is between 90oC and 150oC, and

the temperature for high enthalpy geothermal fluid is over 150 oC [5]. High-temperature geothermal resources

are used for electricity generation. To produce thermal energy using geothermal energy, heat pumps are used.

The product, thermal energy, is used for heating, domestic hot water or for cooling the air. These systems are

more common than geothermal power plants, due to the fact that they do not requires large funds for their

building and installing. They also have a very low temperature geothermal source [6]. 2 Corresponding author, email [email protected]



48

Fig. 1. The interior of the Earth, [1]

2. THE GLOBAL SITUATION FOR ELECTRICITY GENERATION USING GEOTHERMAL

ENERGY

According to [7], in 2016, the global geothermal installed capacity was 12.7 GW. Table 1 presents the net

installed geothermal power capacity by country in 2016 [6].

Table 1. Net installed geothermal power capacity by country in 2016

Country Capacity [MW]

USA 2511

Phillippines 1916

Indonesia 1534

Kenya 1116

New Zeeland 986

Mexico 951

Italy 824

Turkey 821

Iceland 665

Japan 533

Costa Rica 207

El Salvador 204

Nicaragua 155

Russian Federation 78

Papua New Guinea 53

In 2017, the global geothermal power generation was 84.8 TWh, while the cumulative capacity reached was 14

GW. Global geothermal power capacity is expected to rise to just over 17 GW by 2023, with the biggest capacity

additions expected in Indonesia, Kenya, Philippines and Turkey, [8]. The largest group of geothermal power

plants in the word is The Geysers Complex, located in USA. The complex, and its 22 geothermal power plants

therein, have a combined installed capacity of 1520 MW.


49

3. GEOTHERMAL ENERGY IN ROMANIA

Romania has a low enthalpy geothermal potential, located along the western border with Hungary (Pannonian

Plain), in the central part and in the south-central part of the country, as presented in Fig. 2.

The main geothermal areas in Romania are:

The Panonian geothermal aquifer;

The Oradea geothermal reservoir;

The Bors geothermal reservoir;

The Beius geothermal reservoir;

The Ciumeghiu geothermal reservoir;

The Cozia-Calimanesti geothermal reservoir;

The Otopeni geothemal reservoir.

Fig. 2. Geothermal areas in Romania [9]

Since the Roman Empire, Romania has been known to use thermal springs for bathing and geothermal fluids for

heating. The search for geothermal resources utilized for production of electricity and heat began in 1960, based

on the hydrocarbon research programme [11]. With more than 250 exploration wells already having been drilled,

the geological research program still continues, with a few new wells being drilled each year. Although the total

capacity of the existing wells is about 480 MWt, only about 246 MWt is currently being used. 96 wells are used

for producing hot water at temperatures from 40oC to 115oC. 35 wells are used for balneology, with a flow rate

of more than 360 l/s and temperatures from 38oC to 65oC [11], [12].

In Romania, there are two main companies currently exploiting geothermal resources: Transgex S.A. and

Foradex S.A. The University of Oradea has established a Geothermal Research Center which provides

geothermal training and research [10]. The main uses of geothermal energy in Romania are shown in the graph

of Fig. 3.


50

Fig. 3. Geothermal energy in Romania

In 2013, in Oradea, Transgex S.A. installed the first geothermal power plant in Romania. The installed capacity

of the pilot plant is 50 kWe and the electricity production of the first year was 400 MWh [13]. The geothermal

power plant is an ORC module, manufactured by ELECTRATHERM, S 4000 model.

4. BINARY CYCLE GEOTHERMAL POWER PLANT

There are three large types of geothermal power plants: dry steam power plant, flash steam power plant and

binary cycle power plant.

For Romania, which has reservoirs with lower temperatures, binary cycle power plant is the most suitable

alternative. This plant uses two kinds of fluids: a geothermal fluid which evaporates at a low boiling point and a

fluid which drives the turbine. The binary fluid is operated through a conventional Rankine cycle. This fluid can

be an organic fluid such as Isopentane, Isobutane. Fig. 4 shows the principal elements of this type of plant.

Fig. 4. Binary cycle power plant: 1 – well production, 2 – pressure regulation valve, 3 – heat exchanger, 4 –

turbine, 5 –electric generаtor,6 – condenser, 7 – cooling water pump, 8 – cooling tower, 9 – condenser pump,

10 – Injection well.

The geothermal fluid (primary working fluid) is passed throuh at heat exchanger (4) to heat the organic fluid

(secondary working fluid) that vaporizes at a lower temperature than water. This fluid is used to drive the turbine

(4) and is then condensed into the condenser (6). The fluid from the binary plant is recycled back to the heat

exchanger and forms a closed loop [4]. The geothermal fluid is injected back to the reservoir. In this way, a

relatively low geothermal thermal potential can be used. A variant of the binary cycle is the Kalina cycle, where

a solution of ammonia is used as the working agent.

Investment costs for a such a geothermal plant depend on the cost of geothermal drilling and the cost of the

surface equipment. Higher uncertainties can be expected in respect to the drilling process and the number of

geothermal wells required for the plant. According with [14], the drilling cost of low temperature geothermal

development is about 10%-20% of the total development cost.


51

The analysis realised in the Report [15] suggests that in the area of Oradea municipality, investments in a Kalina

cycle geothermal power plant could be recovered in 7.69 years.

5. CONCLUSIONS

Geothermal energy is a renewable and clean source of energy that is not influenced by seasonal temparature

changes and that contributes to reduced global warming effects. The capacity factor is 98% which is very high

in comparison with other renewable energy sources.

In Romania, as shown in Fig. 5, there are areas with temperatures above 140°C at 3000 m depth that could be

exploited for electricity production. Although the implementation of projects for electricity generation is

possible, the relatively high investiment costs represent the main challenge.

Fig. 5. Romania- geothermal map – areas where could be possible electricity production

[IGR 2006 source]

Geothermal power plants represent one of the most advantageous solutions to supply energy for isolated

consumers. They eliminate the need of long lines to transport electricity, which generate significant costs for

investment and maintenance. The technologies used are not sophisticated, based on commercially mature

equipment, and the geothermal energy source is virtually inexhaustible. Moreover, there is a particularly high

availability compared to other categories of power plants. Geothermal installations are mainly used to cover the

basis load curve of an energy system.

REFERENCES

[1] Bologa O., Crenganis M., Geothermal Energy, Lucrarile celei de-a VIII-a Conferinte anuale a ASTR,

available at: http://www.agir.ro/buletine/2021.pdf

[2] Dickson M., Fanelli M., Geothermal energy:utilization and technology, 2003, available at:

httр://unesdoс.unesсo.org/imаges/0013/001332/133254e.рdf#nаmeddest=149593

[3] Topliceanu L., Puiu P.G., Contribution of Geothermal Resources to Energy Autonomy: Evaluation and

Management Methodology, Energies 2016, 9(8), 612; https://doi.org/10.3390/en9080612

[4] Mburu M., Geothermal Energy Utilisation, available at: https://orkustofnun.is/gogn/unu-gtp-sc/UNU-GTP-

SC-17-0204.pdf

[5] Muffler, L.P.J., and Cataldi, R., 1978, Methods for regional assessment of geothermal resources:

Geothermics, v. 7, p. 53-89.

[6] Grigore R., Hazi A., Considerations about efficient use of geothermal heat pumps, Buletinul AGIR Nr.3 An

2012, pg. 167-172, available at: http://www.agir.ro/buletine/1379.pdf

http://www.agir.ro/buletine/2021.pdf

http://unesdoc.unesco.org/images/0013/001332/133254e.pdf#nameddest=149593

https://doi.org/10.3390/en9080612

https://orkustofnun.is/gogn/unu-gtp-sc/UNU-GTP-SC-17-0204.pdf

https://orkustofnun.is/gogn/unu-gtp-sc/UNU-GTP-SC-17-0204.pdf

http://www.agir.ro/buletine/1379.pdf


52

[7]*** https://www.irena.org/-

/media/Files/IRENA/Agency/Publication/2017/Aug/IRENA_Geothermal_Power_2017.pdf

[8] *** https://www.iea.org/topics/renewables/geothermal/

[9] *** http://add-energy.ro/tehnologii-de-obtinere-a-energiei-din-surse-geotermale/

[10] *** https://www.worldenergy.org/data/resources/country/romania/geothermal/

[11] Bendea C., Antal C., Rosca M., Geothermal Energy in Romania: Country Update 2010-2014, Proceedings

World Geothermal Congress 2015, Melbourne, Australia, 19-25 April 2015, available at: https://pangea.stanford.edu/ERE/db/WGC/papers/WGC/2015/01013.pdf

[12] *** http://geothermal.ro/pdf/Energii_regenerabile_Geotermal.pdf

[13] *** http://www.transgex.ro/index.php/en/about-us/portfolio/70-iosia-en

[14] httрs://www.geothermаl-energy.org/рdf/IGАstаndаrd/INАGА/2001/2001-27.рdf

[15] http://remsis.utcluj.ro/wp-content/uploads/2016/11/Raport-2016-Oradea.pdf

https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2017/Aug/IRENA_Geothermal_Power_2017.pdf

https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2017/Aug/IRENA_Geothermal_Power_2017.pdf

https://www.iea.org/topics/renewables/geothermal/

http://add-energy.ro/tehnologii-de-obtinere-a-energiei-din-surse-geotermale/

https://www.worldenergy.org/data/resources/country/romania/geothermal/

https://pangea.stanford.edu/ERE/db/WGC/papers/WGC/2015/01013.pdf

http://geothermal.ro/pdf/Energii_regenerabile_Geotermal.pdf

http://www.transgex.ro/index.php/en/about-us/portfolio/70-iosia-en

https://www.geothermal-energy.org/pdf/IGAstandard/INAGA/2001/2001-27.pdf

http://remsis.utcluj.ro/wp-content/uploads/2016/11/Raport-2016-Oradea.pdf


53

INDEX OF AUTHORS

A

ASHGLAF MOHMED – 29

B

BOSTAN ION – 20

BOSTAN VIOREL – 20

D

DULGHERU VALERIU – 20

G

GRIGORE ROXANA – 43,47

GUȚU MARIN – 20

H

HAZI ANETA- 5,14,43

HAZI GHEORGHE – 5,14,43

I

IFITME SILVIU – 47

N

NICHITA CRISTIAN – 29

P

PALADI FLORENTIN- 25

PRIMAC VLADIMIR- 25

PUIU-BERIZUNȚU MIHAI – 47

V

VERNICA SORIN-GABRIEL – 5,14,43,47

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