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Mahesh, A. and Sandhu, K.S. (2017) A Genetic Algorithm Based Improved Optimal Sizing Strategy for Solar-Wind-Battery Hybrid System Using Energy Filter Algorithm. Frontiers in Energy, 1-13.
https://doi.org/10.1007/s11708-017-0484-4

has been cited by the following article:

• TITLE: Optimal Sizing of Solar/Wind Hybrid Off-Grid Microgrids Using an Enhanced Genetic Algorithm

  AUTHORS: Abdrahamane Traoré, Hatem Elgothamy, Mohamed A. Zohdy

  KEYWORDS: Optimization, Off-Grid Microgrid, Renewable Energy, Energy Storage Systems (ESS), Solar Photovoltaic (PV), Wind, Battery, Hybrid, Genetic Algorithm (GA)

  JOURNAL NAME: Journal of Power and Energy Engineering, Vol.6 No.5, May 31, 2018

  ABSTRACT: This paper presents a method for optimal sizing of an off-grid hybrid microgrid (MG) system in order to achieve a certain load demand. The hybrid MG is made of a solar photovoltaic (PV) system, wind turbine (TW) and energy storage system (ESS). The reliability of the MG system is modeled based on the loss of power supply probability (SPSP). For optimization, an enhanced Genetic Algorithm (GA) is used to minimize the total cost of the system over a 20-year period, while satisfying some reliability and operation constraints. A case study addressing optimal sizing of an off-grid hybrid microgrid in Nigeria is discussed. The result is compared with results obtained from the Brute Force and standard GA methods.