7.Conclusion
Over the past decades has been observed a high growth in the use of
micro-grid and energy management procedures. This paper deals with
optimal planning of a renewable micro-grid, connected to the main grid
using mixed-integer linear programming. This micro-grid consists of
renewable energy resources including wind, solar, battery and fuel cell.
A simulation on a real sample is carried out and optimal schedule of
units are obtained with operational cost minimization. The virtual power
producer uses a central control system dealing with the management of
optimal generation and load control in the micro-grid. The simulation
procedure is implemented using GAMS software with CPLEX solver and
Genetic algorithm. Operational cost for a 24-hour-period, taking into
account the proposed scenarios, is $3183 saving $169 in comparison
with Genetic algorithm. By analyzing the optimal planning of scenarios,
the following results can be considered:
1- Optimal power generation in each scenario is carried out properly
according to each manufacturer price comprising diesel, wind,
photovoltaic, battery and fuel cell.
2- Photovoltaic power, with respect to the presence of sun, is
forecasted to be between hours 6th to
19th. At the outset and end of the day, power
generation is minimal; and, the maximum power generation is observed at
hour 13th.
3- Scheduling of wind power is implemented proportional with forecasted
power.
4- The charging of battery is occurred in low load of grid for all
scenarios (nights: at hours 2nd to
5th; days: at hours 13th to
15th). With respect to low price of selling energy to
the main grid in these hours, charging of battery is preferred.
5- Selling the energy to the main grid is performed at times that the
sale price is in its peak value (at hours 8th to
12th and 19th to
22th).
6 - Maximum discharge of battery to provide the peak load lasted a
couple of hours; and, it occurred at hours 19th to
22th and at hours 8th to
11th for selling to the main grid.
7 - All constraints of micro grid are fulfilled.
References
- M. Elsied, A.Oukaour, H.Gualous, R.Hassan, A.Amin, “An advanced
energy management of microgrid system based on genetic algorithm”,IEEE 23rd International Symposium on
Industrial Electronics(ISIE) , 2541-2547(2014).
- N.W.A. Lidula, A.D. Rajapakse, “Microgrids research: A review of
experimental microgrids and test systems”, Renewable and
Sustainable Energy Reviews , 15 , 186-202(2011).
- H.Jiayi, J.Chuanwen, X.Rong, “A
review on distributed energy resources and MicroGrid”,Renewable and sustainable Energy Reviwes , 12 ,
2472-2483( 2008).
- J.J.Justo, F.Mwasilu, J.Lee, J.W. Jung, “AC-microgrids versus
DC-microgrids with distributed energy resources: A review”,Renewable and Sustainable Energy Reviws , 24 ,
387-405(2013).
- M. Izadbakhsh, M. Gandomkar, A. Rezvani, A. Ahmadi, “Short-term
resource scheduling of a renewable energy based micro grid”,Renewable Energy , 75 , 598-606(2015).
- M.Dali, J.Belhadj, X.Roboam, “Hybrid solar–wind system with battery
storage operating in grid-connected and standalone mode: Control and
energy management- Experimental investigation”, Energy ,35 , 2587-2595(2010).
- N. Mendis, K. M. Muttaqi, S. perera, S. Kamalasadan,“An effective
power management strategy for a wind-disel-hydrogen-based remote area
power supply system to meet fluctuating demands under generation
uncertainty”, IEEE Transactions on Industry Applications ,51 , 1228-1238(2015).
- S.J.Ahn, S.R.Nam., J.H.Choi ,S.I.Moon, “Power scheduling of
distributed generators for economic and stable operation of a
microgrid”, IEEE Transactions on Smart Grid , 4 ,
398-405(2013).
- K.K.Mehmood, S.U.Khan, S.J.Lee ,Z.M.Haider, “Optimal sizing and
allocation of battery energy storage systems with wind and solar power
DGs in a distribution network for voltage regulation considering the
lifespan of batteries”, IET Renewable Power Generation,11, 1305-1315(2017).
- G.Liu, M.Starke, B.Xiao, K.Tomsovic, “Robust optimisation-based
microgrid scheduling with islanding constraints”, IET
Generation, Transmission and Distribution , 11 ,
1820-1828(2017).
- A. A. Eajal, E. F. EI-Saadany,Y. Elrayani, K. Ponnambalam, “Two-stage
stochastic power generation scheduling in microgrids”, IEEE
27rd Canadian Conference on Electrical and Computer
Engineering(CCECE) , 1-6 (2014).
- W. Roth , J. Benz, B. Ortiz, A Steinhüser, “Fuel cells in
photovoltaic hybrid systems for stand-alone power supplies”,2nd European PV-Hybrid and Mini-Grid
Conference , Germany, 232-239(2003).
- H. Morais, P. Kadar, P. Faria, Z.A.Vale, H.M.Khodr, “Optimal
scheduling of a renewable micro-grid in an isolated load area using
mixed-integer linear programming,” Renewable Energy ,35 , 151-156(2010).
- A.A.Moghaddm, A.Seifi, T.Niknam, M.R. Alizadeh Pahlavani,
“Multi-objective operation management of a renewable MG (micro-grid)
with back-up micro-turbine/fuel cell/battery hybrid power source”,Energy , 36 , 6490-6507(2011).
- E.Dursun, O.Kilic, “Comparative evaluation of different power
management strategies of a stand-alone PV/Wind/PEMFC hybrid power
system”, International Journal of Electrical Power and Energy
System , 34 , 81-89(2012),
- Y.H.Chen, S.Y.Lu, Y.R.Chang, T.T.Lee, M.C.Hu, “Economic analysis and
optimal energy management models for microgrid systems: A case study
in Taiwan”, Applied Energy , 103 , 145-154(2013).
- G.G.Moshi, M.Pedico, C.Bavo, A.Berizzi, “Optimal generation
scheduling of small diesel generators in a microgrid”, IEEE
International Energy Conference (ENERGYCON) , 867-873(2014).
- D.E.Olivares, C.E.Canizares, M. Kazerani, “A centralized optimal
energy management system for microgrids”, IEEE Power and Energy
Society General Meeting , 1-6(2011).
- C.A.H.Aramburo, T.C Green, N.Mugniot, “Fuel consumption minimization
of microgrid”, IEEE Transactions on Industry Applications ,41 , 673-681(2005).
- U.Akram, M. Khalid, S.Shafiq, “Optimal sizing of a wind/solar/battery
hybrid grid-connected microgrid system”, IET Renewable Power
Generation , 12 , 72-80(2018).
- Y.Liu, S. Tan, C.Jiang, “Interval optimal scheduling of hydro-PV-wind
hybrid system considering firm generation coordination”, IET
Renewable Power Generation , 11 , 63-72(2017).
- L.Yang, M.He, V.Vittal, J.Zhang, “Stochastic optimization-based
economic dispatch and interruptible load management with increased
wind penetration”, IEEE Transactions on Smart Grid ,7 , 730-739 (2016) .
- T. Niknam, R. A. Abarghooee, M. R. Narimani, “An efficient
scenario-based stochastic programming framework for multi-objective
optimal micro-grid operation”, Applied Energy , 99 ,
455-470(2012).
- A.Parisio, L.Glielmo, “A mixed integer linear formulation for
microgrid economic scheduling”, IEEE International Conference
on Smart Grid Communications (SmartGridComm) , 505-510(2011).
- H.Siahkali, M.Vakilian, “Stochastic unit commitment of wind farms
instegrated in power system”, Electric Power Systems Research ,80 , 1006-1017(2010).
- A.R.Malekpour, S.Tabatabaei, T.Niknam, “Probabilistic approach to
multi-objective Volt/Var control of distribution system considering
hybrid fuel cell and wind energy sources using improved shuffled frog
leaping algorithm”, Renewable Energy , 39 ,
228-240(2012).
- W. Alharbi, K. Raahemifar, “Probabilistic coordination of microgrid
energy resources operation considering uncertainties”, Electric
Power Systems Research , 128 , 1-10 (2015).
- C. Uckun, A. Botterud, J.R.Birge, “An improved stochastic unit
commitment formulation to accommodate wind uncertainty”, IEEE
Transactions on Power Systems , 31 , 2507 – 2517(2016).
- N.Augustine, S. Suresh, P.Moghe, K.Sheik, “Economic dispatch for a
microgrid considering renewable energy cost functions”, IEEE
PES Innovative Smart Grid Technologies (ISGT) , 1-7(2012).
- R.A Abarghooee, T.Niknam, A.Roosta, A.R.Malekpour, M.Zare,
“Probabilistic multiobjective wind-thermal economic emission dispatch
based on point estimated method”, Energy , 37 ,
322-335(2012).