lucian toma upb intellicis
TRANSCRIPT
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Power Market Strategiesof Synchronized Microgrids
Lucian Toma, PhDDepartment of Electrical Power SystemsUniversity POLITEHNICA of Bucharest
IntelliCIS 7th Action Workshop, 10-11 September 2012, Riga
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~AMRAMR AMR
AMR AMR~~
AMR
GEN 10
GEN 1
CBUS- 8
BUS- 2
BUS- 30
BUS- 39
BUS- 1
BUS- 8
BUS- 9
CBUS- 8
BUS- 16
BUS- 12
CBUS- 12
GEN 9
CBUS- 12
GEN 3
BUS- 28
BUS- 37
CBUS- 18
BUS- 26
CBUS- 26
GEN 8
CBUS- 26
BUS- 29
BUS- 5
BUS- 25
CBUS- 25
CBUS- 25
BUS- 17
BUS- 3
CBUS- 39
CBUS- 39BUS- 18
BUS- 4
CBUS- 3
CBUS- 4
CBUS- 3
CBUS- 16
CBUS- 18
BUS- 27
CBUS- 27
CBUS- 28
CBUS- 27
CBUS- 28
CBUS- 29
CBUS- 29
CBUS- 16
BUS- 15
CBUS- 15
CBUS- 15
BUS- 19
CBUS- 24
BUS- 38
CBUS- 24
CBUS- 21
BUS- 22
CBUS- 21
BUS- 21
GEN 4
BUS- 24
BUS- 20
BUS- 33
BUS- 23
BUS- 35
GEN 6
BUS- 14
CBUS- 7CBUS- 31
GEN 2
BUS- 6 BUS- 7
BUS- 31
CBUS- 4
CBUS- 31
CBUS- 7BUS- 13
BUS- 11
BUS- 10
BUS- 32
BUS- 34
BUS- 36 CBUS- 23
CBUS- 20
GEN 5
GEN 7 CBUS- 23
CBUS- 20
Transmission network
Distribution network
~AMRAMR AMR
AMR AMR~~
AMR
The future of power systems
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http://www.transelectrica.ro/4OperareSEN/functionare.php
Are we ready for renewables?
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Balancing vs. frequency control
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Bilateral Contracts Market
Day Ahead Market
Ancillary Services
Balancing Market
Green Certificates Market
CO2 Market
The electricity market
months to years
one day
months
one day
awarded for produced energy
… this is an intricate story
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BalancingMarket
15:00
Open BM
17:00
Close BM
11:00
Close DAM
DAM
D-1
h-1 h
BC
DAM
D
Time [h]
P [MW]
Powerreserves
Short term auctions
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Eligibility for Electricity Market
if
Pgen > 10 MW The ENTITY can be licensed to independently participate on the electricity market
elseThe entity must sign a contract with Balancing Responsible Party
!!! The condition is valid for both energy and balancing
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Results of the Day Ahead Market
Day Ahead Market 10.09.2012, sources: www.opcom.ro
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The Green Certificates
- Awarded for the energy produced from renewable energy sources
Pricemin = 24 EUR/GC
Pricemin = 55 EUR/GC
- A quota based mechanism
Wind
Hydro
Solar
2 GCs
1 GC
6 GCs ???
Cogeneration 1 GC
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PolitehnicaD.S. 10 kV
MilitariDistrib. St.
CotroceniDistrib. St.
Gas Engine P.P
Photovoltaic PP
Microgrid – University “Politehnica” of Bucharest
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Photovoltaic Power Plant at University “Politehnica” of Bucharest
P [kW] 25
20
15
10
5
00 500 1000 1500 2000 2500 3000 t ( 10 min)
Pinst = 30 kW
Eav = 6 kWh/h
CF = 20%
Location: roof of Faculty of Electrical Engineering
Commissioned: 26 May 2006
Payback time >> Lifetime
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Commissioned: 25 March 2010
Jenbacher Engines
Hoval boilers
2 x 800 kWel
3 x 1200 kWth
ηel = 38%
ηth = 42%
ηtotal = 80%
Fuel: Natural Gas
Gas Distribution Network
Gas Engine Power Plantat University “Politehnica” of Bucharest
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February 2009
June 2009
Load – University “Politehnica” of Bucharest
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Microgrid – University “Politehnica” of Bucharest
10 kVbusbar
Distribution Network(ENEL)
- Natural Gas price- Electrical Energy price- Total load- Total available generation
POLITEHNICA
Technical data:
Power Market - License for electrical energy generation
Advantages:- Allows load increase
without strengthening the network
- Profit from selling el. energy to small consumers without paying transmission costs
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PT2 Metalurgie
PT Dedurizare
PT Mecanica A
PT Mecanica B
PT1 Metalurgie
PT1 Elth
PT2 Elth
STATIE
PT3 Elth
Biblioteca
Înv. general
D2/D5
D1/D4
D2/D5
D2/D5
D1/D4
D1/D4
D1/D4
D3/D6
Meter
Meter
Meter
Meter
Meter Meter
Meter
MeterMeter
MeterDataConcentrator
Smart Grid development
Microgrid – University “Politehnica” of Bucharest
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VPPControl
– Technical characteristics– Availability of primary resource, etc.– Fuel cost– Information from the electricity market
Power reserves Electrical EnergyBalancingmarket
Day ahead market
Developing the Virtual Power Plant concept
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VPPControl
RTU RTU RTU RTU RTU
SCADA
Set pointsSystemparameters
Developing the Virtual Power Plant concept
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Commercial Virtual Power Plant
Several generation entities are aggregated to form a single entity capable to behave on the power market similar to a classical power plant.
Maximize the profit; it takes into account both the generation costs and the power market price;
Minimize the generation costs, by coordinating the generation entities; electrical vehicles and loads can also be included;
Minimize the cost of energy bought from the power market;
Coordinate between energy sold on the power market an energy/reserve sold as ancillary service.
Developing the Virtual Power Plant concept
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Technical Virtual Power Plant
Integration to a central control system of the distributed generators, storage devices and loads located in the same distribution network, so that to provide various technical functions.
Automatic generation control;
Voltage – VAr control;
Load Management;
Load Shedding.
Developing the Virtual Power Plant concept
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The objective function:
VPP – The optimization problem
Benefit Incomes Costs
[ ]max Benefit
The optimization objective:
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EDAM,t – the energy traded by the VPP on the Day‐Ahead Market in the dispatching interval t, in kWh;
cDAM,t – the DAM clearing price in the dispatching interval t, in m.u./kWh;
EBC,t – the energy traded by the VPP through Bilateral Contracts in the dispatching interval t, in kWh;
cBC,t – the energy price negotiated on the bilateral contracts market, in m.u./kWh;
where:
, ,
24 24 24 24 24
, , , , ,1 1 1 1 1
g t g tDAM t DAM t BC t BC t L VPP t VPP R R
t t t t t
Incomes E c E c E c C C
EL‐VPP,t – the energy traded by the VPP through Bilateral Contracts in the dispatching interval t, in kWh;
cVPP,t – the energy price negotiated on the bilateral contracts market, in m.u./kWh;
,g tRC
,g tRC ‐ the hourly income for maintaining a power reserve available to be
provided by the VPP based on the arrangements on the ancillary services market for upward and downward regulation, respectively, in m.u.;
VPP – The optimization problem
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24 24 24 24
, , , ,1 1 1 1
g t g t g t L tt t t t
Costs C SU SD R
‐ the total cost of the energy generated by all generators in the dispatching interval t, in m.u., with
,g tC
, , , , ,1
n
g t g i t g i i ti
C E c I
, ,g i tE
‐ the energy produced by the generator i, in the dispatching interval t, in kWh
,g ic ‐ the marginal costs of the generator i, in m.u./kWh
,g tSU ‐ the cost involved for all generators to start‐up in the dispatching interval t, in m.u.
,g tSD ‐ the cost of all generators involved for shut‐down in the dispatching interval t, in m.u.
,L tR‐ the cost of total power reserve maintained available by all consumers for disconnection in the upward regulation during the dispatching interval t, in kWh
where:
VPP – The optimization problem
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Constraints
, , , ,gen t DAM t BC t L VPP tE E E E
, , , ,1
n
g t g i t i ti
R R I
a) Power balance: generation = load
b) Capability constraints of generators
is the minimum active power limit of the ith DG unit, in kW;
– maximum active power limit of the ith DG unit, in kW.
min,iP
max.iP
min, , , , max,i g i t i t iP P I P
The power reserve
VPP – The optimization problem
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3.02000200050DG6
3.51600160050DG5
4.55000500050DG4
5.03000300050DG3
8.0…4000DG2 (PV power plant)
4.1…3000DG1 (Wind power plant)
m.u./kWhkWkWkW
CostPavailPmaxPmin
2 4 6 8 10 12 14 16 18 20 22 240
1000
2000
3000
4000
5000
time [h]
capa
city
[kW
]DG4
DG6
DG3
DG5
DG1DG2
VPP – Study Case
Available Powers of DGs
Characteristics of DGs
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2 4 6 8 10 12 14 16 18 20 22 241
2
3
4
5
6
7
Time [h]
pric
e [m
.u./k
Wh]
c
cc
DAM
VPP
BC
2 4 6 8 10 12 14 16 18 20 22 240
2000
4000
6000
8000
10000
12000
time[h]
load
[kW
h/h]
E-VPPE-BCE-DAM
E-Total
Traded energies
Energy prices
, 1000 kWh/hg tR
Traded power reserve (availability)
,0.5 m.u./kWh
g tRc
VPP – Study Case
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2 4 6 8 10 12 14 16 18 20 22 24
0
1000
2000
3000
4000
5000
time [h]
Gen
erat
ion
[kW
h]
DG4
DG1 DG3
DG2
DG6
DG5
2 4 6 8 10 12 14 16 18 20 22 240
1
2
3
4
5
6x 10
4
time [h]
Pro
fit [m
.u.]
Incomes
Profit
Costs (Expenses)
Unit commitment
The total profit
VPP – Study Case
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Diesel enginePmin = 0 kWPmax = 300 kWc = 4.2 ¢€/kWh
Wind farmPmin = 0 kWPmax = 400 kWc = 7 ¢€/kWh
Hydro plantPmin = 0 kWPmax = 1600 kWc = 2.4 ¢€/kWh
PhotovoltaicsPmin = 0 kWPmax = 60 kWc = 15 ¢€/kWh
Gas enginePmin = 0 kWPmax = 800 kWc = 3.7 ¢€/kWh
Load 1D1 = 2000 kW
Load 2D1 = 2300 kW
GEN 10
GEN 1
CBUS- 8
BUS- 2
BUS- 30
BUS- 39
BUS- 1
BUS- 8
BUS- 9
CBUS- 8
BUS- 16
BUS- 12
CBUS- 12
GEN 9
CBUS- 12
GEN 3
BUS- 28
BUS- 37
CBUS- 18
BUS- 26
CBUS- 26
GEN 8
CBUS- 26
BUS- 29
BUS- 5
BUS- 25
CBUS- 25
CBUS- 25
BUS- 17
BUS- 3
CBUS- 39
CBUS- 39BUS- 18
BUS- 4
CBUS- 3
CBUS- 4
CBUS- 3
CBUS- 16
CBUS- 18
BUS- 27
CBUS- 27
CBUS- 28
CBUS- 27
CBUS- 28
CBUS- 29
CBUS- 29
CBUS- 16
BUS- 15
CBUS- 15
CBUS- 15
BUS- 19
CBUS- 24
BUS- 38
CBUS- 24
CBUS- 21
BUS- 22
CBUS- 21
BUS- 21
GEN 4
BUS- 24
BUS- 20
BUS- 33
BUS- 23
BUS- 35
GEN 6
BUS- 14
CBUS- 7CBUS- 31
GEN 2
BUS- 6 BUS- 7
BUS- 31
CBUS- 4
CBUS- 31
CBUS- 7BUS- 13
BUS- 11
BUS- 10
BUS- 32
BUS- 34
BUS- 36 CBUS- 23
CBUS- 20
GEN 5
GEN 7 CBUS- 23
CBUS- 20
PBC = 2000 kW
PDAM = 3.69 ¢€/kWh
PDAM = 240 kW
P = 60 kW
P = 0 kWP = 1600 kW
P = 400 kWP = 0 kW
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Diesel enginePmin = 0 kWPmax = 300 kWc = 4.2 ¢€/kWh
Wind farmPmin = 0 kWPmax = 400 kWc = 7 ¢€/kWh
Hydro plantPmin = 0 kWPmax = 1600 kWc = 2.4 ¢€/kWh
PhotovoltaicsPmin = 0 kWPmax = 60 kWc = 15 ¢€/kWh
Gas enginePmin = 0 kWPmax = 800 kWc = 3.7 ¢€/kWh
Load 1D1 = 2000 kW
Load 2D1 = 2300 kW
PBC = 2000 kW
PDAM = 3.71 ¢€/kWh
GEN 10
GEN 1
CBUS- 8
BUS- 2
BUS- 30
BUS- 39
BUS- 1
BUS- 8
BUS- 9
CBUS- 8
BUS- 16
BUS- 12
CBUS- 12
GEN 9
CBUS- 12
GEN 3
BUS- 28
BUS- 37
CBUS- 18
BUS- 26
CBUS- 26
GEN 8
CBUS- 26
BUS- 29
BUS- 5
BUS- 25
CBUS- 25
CBUS- 25
BUS- 17
BUS- 3
CBUS- 39
CBUS- 39BUS- 18
BUS- 4
CBUS- 3
CBUS- 4
CBUS- 3
CBUS- 16
CBUS- 18
BUS- 27
CBUS- 27
CBUS- 28
CBUS- 27
CBUS- 28
CBUS- 29
CBUS- 29
CBUS- 16
BUS- 15
CBUS- 15
CBUS- 15
BUS- 19
CBUS- 24
BUS- 38
CBUS- 24
CBUS- 21
BUS- 22
CBUS- 21
BUS- 21
GEN 4
BUS- 24
BUS- 20
BUS- 33
BUS- 23
BUS- 35
GEN 6
BUS- 14
CBUS- 7CBUS- 31
GEN 2
BUS- 6 BUS- 7
BUS- 31
CBUS- 4
CBUS- 31
CBUS- 7BUS- 13
BUS- 11
BUS- 10
BUS- 32
BUS- 34
BUS- 36 CBUS- 23
CBUS- 20
GEN 5
GEN 7 CBUS- 23
CBUS- 20
P = 60 kW
P = 270 kWP = 1600 kW
P = 400 kWP = 0 kW
PDAM = 0 kW
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Diesel enginePmin = 0 kWPmax = 300 kWc = 4.2 ¢€/kWh
Wind farmPmin = 0 kWPmax = 400 kWc = 7 ¢€/kWh
Hydro plantPmin = 0 kWPmax = 1600 kWc = 2.4 ¢€/kWh
PhotovoltaicsPmin = 0 kWPmax = 60 kWc = 15 ¢€/kWh
Gas enginePmin = 0 kWPmax = 800 kWc = 3.7 ¢€/kWh
Load 1D1 = 2000 kW
Load 2D1 = 2300 kW
PBC = 2000 kW
PDAM = 4.21 ¢€/kWh
GEN 10
GEN 1
CBUS- 8
BUS- 2
BUS- 30
BUS- 39
BUS- 1
BUS- 8
BUS- 9
CBUS- 8
BUS- 16
BUS- 12
CBUS- 12
GEN 9
CBUS- 12
GEN 3
BUS- 28
BUS- 37
CBUS- 18
BUS- 26
CBUS- 26
GEN 8
CBUS- 26
BUS- 29
BUS- 5
BUS- 25
CBUS- 25
CBUS- 25
BUS- 17
BUS- 3
CBUS- 39
CBUS- 39BUS- 18
BUS- 4
CBUS- 3
CBUS- 4
CBUS- 3
CBUS- 16
CBUS- 18
BUS- 27
CBUS- 27
CBUS- 28
CBUS- 27
CBUS- 28
CBUS- 29
CBUS- 29
CBUS- 16
BUS- 15
CBUS- 15
CBUS- 15
BUS- 19
CBUS- 24
BUS- 38
CBUS- 24
CBUS- 21
BUS- 22
CBUS- 21
BUS- 21
GEN 4
BUS- 24
BUS- 20
BUS- 33
BUS- 23
BUS- 35
GEN 6
BUS- 14
CBUS- 7CBUS- 31
GEN 2
BUS- 6 BUS- 7
BUS- 31
CBUS- 4
CBUS- 31
CBUS- 7BUS- 13
BUS- 11
BUS- 10
BUS- 32
BUS- 34
BUS- 36 CBUS- 23
CBUS- 20
GEN 5
GEN 7 CBUS- 23
CBUS- 20
P = 60 kW
P = 800 kWP = 1600 kW
P = 400 kWP = 300 kW
PDAM = -860 kW
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Balancing is required by participation from distribution networks
Conclusions
VPP might be an efficient way to use the small electricity sources
Large power plants (mainly thermal) are seriously subjected to aging
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IntelliCIS 7th Action Workshop, 10-11 September 2012, Riga
Thank you