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Fuzzy Logic Control and Coordination of Battery
Energy Storage System with Standalone Wind Powered DC
Micro Grid
M.Suresh1, B.Viswanath2, Ajit Kumar
Mohanty3.
1,2,3Vignan’s Institute of Information
Technology, Duvvada 1msushe56@gmail.com
2bviswanath_108@yahoo.com 3ajitchinu@gmail.com
May17,2017
Abstract
This paper proposes a Fuzzy Logic Controlled Battery
Energy Storage System (BESS) for standalone wind
powered DC Microgrid and coordination between them
to meet the load. Due to the depletion of conventional
energy resources and increased environmental
pollution, there is a need for harnessing green energy
to meet the ever increasing load demand. Some of them
are wind, solar, geothermal, biomass, tidal, etc. The
standalone wind powered DC microgrid consists ofa
wind turbine generator with battery back-up connected
to the load.As the wind speed is not constant.Wind
generator outputpower and voltage are always varying.
To get regulated voltage, wind energy system is
connected to AC/DC converter. The voltage available
from AC/DC converter is low and unregulated. Hence a
DC/DC boost converter is used to boost and regulate
the voltage at point of common coupling. A Fuzzy Logic
Controller is used to make comparison between
International Journal of Pure and Applied MathematicsVolume 114 No. 8 2017, 167-177ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version)url: http://www.ijpam.euSpecial Issue ijpam.eu
167
varying load of DC Microgrid system and available
energy from wind systemSimulation study is carried
out by using MATLAB/SIMULINK software. Results
show that Fuzzy Logic Controller effectively controls
the charging and discharging of BESS output power in
co-ordination with wind energy system as per load
demand.
Key Words: DC Microgrid, Fuzzy Logic Controller,
Battery Energy Storage System, BESS DC/DC Bi-
Directional Converter, AC/DC Converter, Interior
Permanent Magnet Synchronous(IPMS) Generator,
Wind Energy System (WES).
1 Introduction
Renewable energy is non- polluting clean energy from natural
resources like wind, tides, geo thermal heat and sun light etc. As
such, it has no limit. The renewability of these energies can be
replenished by natural actions. The current situation of globe
demands the increasing use of renewable energy to meet the energy
demand. To reduce pollution and to meet ever increasing demand it
is the only way. The combustion of fossil fuel based non renewable
energy sources fossil fuel is polluting environment which contributes
to global warming. The increasing usage of renewable energy
sources controls global warming as well as global energy crisis In
renewable energy sources solar is dominating one, but it more
expensive than wind energy system of same size [1]. DC Micro grid
systems are more popular and they have shown advantages in terms
of cost and efficiency compared to AC Micro grids by eliminating
power conversion stages for grid integration [2]. Wind energy system
and energy storage systems offer environmental friendly solution,
but having challenges of appropriate control and coordination
between different components of the system [1]-[3]. Due to the
variable nature of wind, it is difficult to match instantaneous load
demand with instantaneous power extracted from wind. To
overcome this difficulty energy storage systems are important for
continuous operation and reliability of the system[5]-[11]. Energy
storage systems offer good transient stability for sudden load
variation ns [5]-[7]. The Fuzzy Logic Control controller has more
advantages than conventional controllers i.e. cost effective robust
control, and offers good transient stability by reducing oscillations
[3].
International Journal of Pure and Applied Mathematics Special Issue
168
2 Proposed Microgrid System
The proposed standalone DC Microgrid system consists of wind
energy system in conjunction with fuzzy controlled battery
energy storage system and DC load, as shown in Fig.1. The
principle of operation of a wind energy system is characterized
by two key transfer steps. In the first step, the wind turbine
extracts kinetic energy from the wind and it is converted to
mechanical torque in the shaft which is connected to
generator. In the second step, i.e. involves the generation
system which converts mechanical torque into electrical
energy. The generation system, which gives an AC output
power and voltage which depend on the available base wind
speed. The AC power output from wind energy system is
converted to DC power by using AC/DC converter. The output
voltage from AC/DC converter is not at required level for load
3 Modeling of Proposed Microgrid System
LA. Modeling of Wind Energy System (Wes)
The Wind Energy System is having two major parts: 1.Wind
Turbine coupled with 2. Interior Permanent Synchronous
Generator(IPSG). The modeling of both parts is discussed
below[1].
1. Modeling of Wind Turbine
The total power extracted by wind turbine from the available
2. Modeling of IPMS Generator
The Fig.2 represents d- and q-axes circuits of IPMS generator.
The following equations are used for modeling the IPMS
generator.
)1(),(35.0 P
CAvPw
International Journal of Pure and Applied Mathematics Special Issue
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The output power of the IPMS Generator can be expressed as
follows
corecuWout PPPP )11(
c
qdfdd
qdsgoutR
iLiLiiRTP
222
22 )(
)12(
The power output from the IPMS Generator is given to the
AC/DC converter which steps up output voltage as per load
ratings. The power from wind energy system is constant at
constant voltage.
B. Modeling of Battery Energy Storage System (Bess)
In this proposed system, BESS has lead acid type battery
which is used as back up to the wind energy system. The BESS
has to supply load on DC Microgrid whenever the load becomes
more than wind power output. The controlling of BESS power
is achieved by Fuzzy Logic Controller. Output of BESS is given
to the Bi-Directional DC/DC converter to regulate voltage on
either side of Microgrid system to make power to flow from
BESS to DC-link and vice versa.
C. Modeling of Bi-Directional DC/DC Converter
Fig.3. represents Bi-Directional DC/DC converter, which
allows power in both ways from BESS to DC link and vice
versa. MOSFET has been used in this converter and the firing
pulses come from Fuzzy Logic Controller to achieve desired
control action [2].
4 Modeling of Fuzzy Logic Controller The Fuzzy Logic Controller has two input parameters and one
output parameter. It compares the output power from wind
energy system and power demanded by the load. The input
parameters to the Fuzzy Logic Controller are change in State-
of-Charge )( SoC and Change in Power )( P . The output
parameter from the Fuzzy Logic Controller is Direction Index
of Current of BESS )(DIC . SoC is the difference between the
state of charge at present (S0CNEW )and state of charge
commanded based on (S0CNEW ) the load power. P is difference
between the power demanded by load PL and power generated
by wind turbine PW. The input parameters of Fuzzy Logic
Controller )( SoC and )( P are given as follows
)13(nowSoCref
SoCSoC
)14(LPwind
PP
)7()(
)6()(
0
0
fddqqsqq
qqddsdd
iLidt
dLRiv
iLidt
dLRiv
International Journal of Pure and Applied Mathematics Special Issue
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Input Variable-1 (Change-in. State-of –Charge SoC )
(15)7...2,1 iwhereSoCSoCSoC iii
Fig.6. Membership Function of SoC
Fig. 7. Membership Function of P The above membership functions contain seven grades which
are PL (Positive Large), PM (Positive medium), PS (Positive
Small), EZ (Zero), NS (Negative Small), NM (Negative
Medium) and NL (Negative Large).
Rules inferred in the fuzzy inference
system are given by:
The output triangular membership function can
be defined as follows:
)17(
5.01.0max
5.01.0max
veDICtheveisPifw
SoCP
veDICtheveisPifw
PSoC
DICc
The above Eqn.17 represents membership function of output.
There two conditions are in the above equation
Condition-1
veDIC Means that SOC is positive, i.e. the power flows
from DC-link to BESS the battery is in charging mode. Under
this charging mode of BESS, the Direction of Current is
assumed to be Negative
Condition-2
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veDIC Means that is SOC negative, that is the power flows
from BESS to Dc-link and its current direction assumed as
positive. The battery is in discharging mode.
5. Matlab/Simulation Results and Analysis:
Fig.9. Regulated Wind Energy System Voltage.
The working voltage of load is at 200V as shown in the fig.7.
Wind energy system backup with battery. The battery is
connected to DC-link through Bi-Directional DC/DC converter
to get regulated output voltage from battery as per load
requirements. Fig.8 shows the output voltage DC/DC converter
across DC-link.
Fig.10. Voltage across Load Terminals
Mode 1: In this mode of operation the power supplied by wind
energy system is more than the load. In Fig.6 & Fig.9 shows
power supplied by wind and variation of load respectively. The
wind supplies 1kW of constant power. In Fig.9 the load
demand below 0.2 sec is less than wind power. During this
time the BESS is in charging mode. The power flows from DC-
link to BESS which is negative assumed as negative direction.
Fig.10 & Fig.11show power output and current supplied by
BESS.
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.40
100
200
300
400
Time
Vola
tge in V
olts
WES Output Voltage
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.40
100
200
300
400
Time
Vola
tge in V
olts
Load Voltage
International Journal of Pure and Applied Mathematics Special Issue
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Fig.12. Load Demand
Fig.13. Power Delivered by BESS
Fig.15. State of Charge of BESS
Mode 2: In this mode the power supplied by the wind energy
system is less than the load demand. The power from Wind
Energy System is only 1kW and the load demands around
2kW. At this time the battery is in discharging mode. The
power flows from BESS to DC-link to meet the load. After 0.2
sec the BESS current and battery power direction was
reversed as shown in Fig.12. The sum of power from Wind
Energy System and power from BESS is exactly equal to load
demand at all instants of time. The state of charge of the
battery is in charging mode before 0.2 sec and discharging
after 0.2 sec as shown in Fig.12
Mode3: In this mode of operation the power from Wind Energy
System is exactly equal to load demand as show in Fig. 13 and
0 0.1 0.2 0.3 0.40
1000
2000
3000
Time
Pow
er
in W
att
s
Load Demand
mode 2mode 1
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4-4000
-3000
-2000
-1000
0
1000
2000
3000
4000
Time
Pow
er in
wat
ts
Power Delivery by BESS
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.439.9999
39.9999
40
40.0001
40.0001
40.0001
40.0002
Time
State of Charge of BESS
Discharging mode
charging mode
International Journal of Pure and Applied Mathematics Special Issue
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0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4-5000
-4000
-3000
-2000
-1000
0
1000
2000
3000
4000
5000
Time
Pow
er in
Wat
ts
BESS in Floating Condition
Fig.14. During this time the BESS is neither charging nor
discharging i.e. BESS is in floating state as show in Fig. 15.
Fig 16 shows constant State of Charge of BESS in Mode 3
operation.
Fig.17. Load Demand(Mode 3)
Fig.18. BESS is in Floating condition
(Mode 3)
Fig.19. State of Charge of BESS (Mode 3)
Mode 4:In this mode of operation, the load demand is zero. The
Wind Energy System is supplying 1kW power. Since the load
demand is zero, the entire power from Wind Energy System is
used for charging of BESS as shown in Fig. 16, Fig. 17 and Fig.
18. The state of Charge of BESS is in charging as shown in
Fig. 19.
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.40
500
1000
1500
2000
2500
3000
3500
4000
Time
Pow
er
in W
att
s
Load Demand
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.440
40
40
40
40
40
40
40
40
Time
State of Charge of BESS
International Journal of Pure and Applied Mathematics Special Issue
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5 Conclusions: This paper proposes an effective control and coordination
of wind energy system and BESS in DC Microgrid
system. The effective control charging/discharging of
BESS through a Bi-Directional converter isachieved by
using Fuzzy Logic Controller under different loading
conditions.The simulation results have shown that
effective performance of Fuzzy Logic Controller during
the wind power zero and load zero conditions. The
advantage of Fuzzy Logic Controller is that; It prevents
system Blackout in the event of low wind conditions
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