Optimal Planning of Renewable Systems for Multi Border Garrisons Considering the Fuel Transportation System

Document Type : Original Article

Author

IHU

Abstract

The aim of optimal planning of renewable system is to maximize achieved benefits from this investment. Modelling the problem with more details will cause to achieve the results with more reality and practicality. One of the most important off-grid areas are border garrisons. Although, these spots are disconnected from each other electically, but, their energy usages are interconnected because of the presence of unique fuel transportation system. In this paper, the reduction of energy provision’s cost from a overhead organization’s aspect has been considered as objective function. To model the problem with elboration, the fuel transportation system has been considered as the one of cost source of problem. In addition, the constraints of economical evaluation have been written to guarantee the economic condition of carried out investment. The results of simulation using the test system including 4 garrisons, show that with an economical investment, the total cost of energy provision can be decreased up to 78%. 

Keywords


[1]      Bahramara, S.; Parsa Moghaddam M.; Haghifam M. R. “Optimal Planning of Hybrid Renewable Energy Systems Using HOMER: A Review”; Renewable Sustainable Energy Rev.  2016, 62, 609-620.##
[2]       Chang, K.; Grace, L. “Optimal Design of Hybrid Renewable Energy Systems Using Simulation Optimization”; Simulation Modelling Practice and Theory 2015, 52, 40-51.##
[3]      Ramli, M. A.; Hiendro, A.; Sedraoui, K.; Twaha, S. “Optimal Sizing of Grid-Connected Photovoltaic Energy System in Saudi Arabia”; Renewable Energy 2015, 75, 489-495.##
[4]      Che, L.; Zhang, X.; Shahidehpour, M.; Alabdulwahab, A.; Abusorrah, A. “Optimal Interconnection Planning of Community Microgrids With Renewable Energy Sources”; IEEE Trans. Smart Grid. 2017, 8, 1054-1063.##
[5]      Jung, J.; Villaran, M. “Optimal Planning and Design of Hybrid Renewable Energy Systems for Microgrids”; Renewable Sustainable Energy Rev. 2017, 75, 180-191.##
[6]      Mohammadi, M.; Ghasempour, R.; Astaraei, F. R.; Ahmadi, E.; Aligholian, A.; Toopshekan, A. “Optimal Planning of Renewable Energy Resource for a Residential House Considering Economic and Reliability Criteria”; Int. J. Electr. Power Energy Syst. 2018, 96, 261-273.##
[7]      Liu, Y.; Yu, S.; Zhu, Y.; Wang, D.; Liu, J. “Modeling, Planning, Application and Management of Energy Systems for Isolated Areas. A Review: Renewable Energy Systems for Microgrids”; Renewable Sustainable Energy Rev. 2018, 82, 460-470.##
[8]      Sadeghi, H.; Abodollahi, A.; Mohammadian, M.; Rashidinejad, M. “Evaluating The Effects of Renewable Energy Resources from Passive Defense and Social Welfare perspectives in the Context of Expansion Planning”; Adv. Defence Sci. Technol. 2015, 6, 71-86.##
[9]      Khanzade, M. H.; Nabati Rad, M. “Energy Supply of Sensitive Areas as an Inverter-Based Microgrid During Stiff Power System Black Out”; Adv. Defence Sci. Technol. 2017, 8, 85-95.##
[10]   Ghaffarpour, R.; Jam, A.; Ranjbar, A. “Optimal Mix of Distributed Generation Allocation to Improve the Security of Energy Supply in Defensive Sites Using Principles of Passive Defence”; Adv. Defence Sci. Technol. 2016, 7, 19-32.##
[11]   Garcés, L. P.; Conejo, A. J.; García-Bertrand, R; Romero, R. “A Bilevel Approach to Transmission Expansion Planning Within a Market Environment”; IEEE Trans. Power Syst. 2009, 24, 1513-1522.##
[12]   Soroudi, A.; Aien, M.; Ehsan, M. “A Probabilistic Modeling of Photo Voltaic Modulesand Wind Power Generation Impact on Distribution Networks”; IEEE Sys. J. 2012, 6, 254–259.##