af0192 lucian toma itec2016
DESCRIPTION
optimal scheduling in a microgridTRANSCRIPT
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Optimal generation scheduling
in a microgrid
Lucian Toma, Ion Triştiu,
Constantin Bulac, Andreea ŞtefanaDepartment of Electrical Power Systems
University POLITEHNICA of Bucharest
2016 ITEC ASIA, Busan, June 1-4
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Transmission network
Distribution network
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The future of power systems
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AMI
AMI
AMI AMI
AMI
AMI AMI
Substation
Dispatching and Strategy
PV
OPTIMIZATION
& CONTROL
Gas Engine
RTU RTU
RTU
Communication
Main
electrical
network
Microgrid
Wind
The future of power systems
Battery
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Microgrid
Substation
Militari
Distrib. St.
Cotroceni
Distrib. St.
Gas Engine P.P
PV power plant
Microgrid – University “Politehnica” of Bucharest
Cable 1
Cable 2
Pinst = 30 kW
CF = 20%
2 x 800 kWel
ηel = 38%
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PolyGrid
Substation
Militari
Distrib. St.
Cotroceni
Distrib. St.
Gas Engine P.P
PV power plant
Microgrid – University “Politehnica” of Bucharest
Cable 1
Cable 2
0
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The optimization objective:
The mathematical model
subject to load-generation balance:
60x24
1
( )GE
t
P t
MIN
( ) ( ) ( ) ( ) ( ) ( )load pv w GE bat surplusP t P t P t P t P t P t
Ppv – power generation from PV power plantPw – power generation from wind power plantPGE – power generation from gas enginePbat – power from battery (positive = generation; negative = load)Psurplus – power unbalance
and capability limits
maxgenP P
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Characteristics of the wind and solar power plants
The mathematical model
- have the highest priority and are given by generation profiles
Characteristics of the gas engine
- installed power from hundreds of kW to few MW- very fast; can change the generation within few seconds- it has the lowest priority, thus they produce power when
( ) ( ) ( ) ( )load pv w batP t P t P t P t
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The mathematical model
Characteristics of the battery
- is characterized by the total installed energy Ebat,inst, in MWh, and the maximum instantaneous power Pbat,max, in MW.
- battery charges when there is a surplus of energy from the renewable energyunits only
( ) ( ) ( )pv w loadP t P t P t
- in order to increase the lifetime of the battery, a minimum and a maximum state of charge, SOCmin and SOCmax, are considered
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The mathematical model
Algorithm 1 assumes that the battery’s operating mode ischanged when it completes a full charging / discharging;no charging is allowed when in discharging mode, and nodischarging is allowed when in charging mode;
Algorithm 2 assumes that the battery is charging any time thereis a surplus from renewables, and discharging when theload is greater than the available generation fromrenewables.
Two algorithms are used:
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Main data gas engine installed power, PGE,inst = 1.4 MW; battery’s size is decided battery minimum state o charge, SOCmin = 25%; battery maximum state of charge, SOCmax = 75%; load, wind generation and solar generation profiles are given
Microgrid – case studies
WindPhotovoltaicGas Engine
Uncontrolled: Load, Wind, Solar
Controlled: Gas engine, Battery
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Microgrid – case studies
• installed power Pbat,max = 0.6 MW;
• installed energy, Ebat,inst = 1 MWh;
• rule: full charging/discharging is required until the battery changes its operating mode: Algorithm 1 is applied
Case 1
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Microgrid – case studies
0 500 1000 1500-0.5
0
0.5
1
1.5
2
2.5
Time [minutes]
Genera
tion-L
oad p
rofile
[M
W]
Ppv
Pw
Pgas
Pbat
Pload
Surplus
0 500 1000 15000.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Time [minutes]
Batt
ery
- s
tate
of
charg
e [
-]
0 500 1000 15000
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Time [minutes]
Charg
ing m
ode
Case 1 Battery state of charge
Battery operating mode
PGE = 5.65 MWh
Psurplus = 0.523 MWh
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Microgrid – case studies
• installed power Pbat,max = 0.6 MW;
• installed energy, Ebat,inst = 1 MWh;
• rule: full charging/discharging is required until the battery changes itsoperating mode: Algorithm 1 is applied
Case 2
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Microgrid – case studies
Case 2
0 500 1000 1500-0.5
0
0.5
1
1.5
2
2.5
Time [minutes]
Genera
tion-L
oad p
rofile
[M
W]
Ppv
Pw
Pgas
Pbat
Pload
Surplus0 500 1000 1500
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Time [minutes]
Batt
ery
- s
tate
of
charg
e [
-]
0 500 1000 15000
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Time [minutes]
Charg
ing m
ode
Battery state of charge
Battery operating mode
PGE = 5.37 MWh
Psurplus = 0.437 MWh
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Microgrid – case studies
• installed power Pbat,max = 0.6 MW;
• installed energy, Ebat,inst = 1 MWh;
• rule: the battery charges any time there is a surplus of generation fromrenewables: Algorithm 2 is applied
Case 3
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Case 3
Microgrid – case studies
0 500 1000 1500-0.5
0
0.5
1
1.5
2
2.5
Time [minutes]
Genera
tion-L
oad p
rofile
[M
W]
Ppv
Pw
Pgas
Pbat
Pload
Surplus
0 500 1000 15000.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Time [minutes]
Batt
ery
- s
tate
of
charg
e [
-]
0 500 1000 15000
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Time [minutes]
Charg
ing m
ode
Battery state of charge
Battery operating mode
PGE = 4.98 MWh
Psurplus = 0 MWh
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the first algorithm involves a smaller number ofcharging/discharging cycles
Conclusions
the microgrid allows a local generation-load balancingthus reducing the negative effects of the intermittencyshown by RES
the second algorithm achieves minimum generation fromthe gas engine unit and thus less fuel
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Thank you