Optimal Sizing Of Building Integrated Hybrid PV/Diesel Generator System For Zero Load Rejection For Malaysia

Marwan Mahmoud's picture
Journal Title, Volume, Page: 
Energy and Buildings Volume 43, Issue 12, December 2011, Pages 3430–3435
Year of Publication: 
2011
Authors: 
Tamer Khatib
Department of Electrical, Electronic & System Engineering, Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia
A. Mohamed
Department of Electrical, Electronic & System Engineering, Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia
K. Sopian
Solar Energy Research Institute, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia
M. Mahmoud
Department of Electrical Engineering, Engineering Faculty, An-Najah National University, Nablus, Palestine
Current Affiliation: 
Department of Electrical Engineering, Engineering Faculty, An-Najah National University, Nablus, Palestine
Preferred Abstract (Original): 
In this research, an optimisation for building integrated hybrid PV/diesel generator system for zero load rejection for Malaysia is performed. The optimisation is performed considering a loss-of-load probability (LLP) less than 0.01. However, the daily averages of solar energy for Malaysia and a mathematical model of a hybrid PV/diesel generator system are used in this optimisation. The optimisation presented in this paper aims to calculate the optimum capacities of a PV array and diesel generator, which investigate the minimum system cost. An optimisation problem in terms of system units’ cost is solved graphically in this study. Moreover, the optimised system is compared to other energy source choices to highlight its feasibility. The recommended configuration of a PV/diesel system located in Malaysia is CA = 1.2, CDG = 0.3, while the optimum CB is 0.1. The results of the optimisation show that a PV/diesel generator choice is more feasible compared to a standalone PV system or diesel generator system because it reduces the system cost by 35%.
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