Optimal Allocation of a Hybrid Photovoltaic Biogas Energy System Using Multi-Objective Feasibility Enhanced Particle Swarm Algorithm

Hussein M. K. Al-Masri, Abed A. Al-Sharqi, Sharaf K. Magableh, Ali Q. Al-Shetwi, Maher G. M. Abdolrasol and Taha Selim Ustun
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Hussein M. K. Al-Masri: Department of Electrical Power Engineering, Yarmouk University, Irbid 21163, Jordan
Abed A. Al-Sharqi: Department of Electrical Power Engineering, Yarmouk University, Irbid 21163, Jordan
Sharaf K. Magableh: Department of Electrical Power Engineering, Yarmouk University, Irbid 21163, Jordan
Ali Q. Al-Shetwi: Electrical Engineering Department, Fahad Bin Sultan University, Tabuk 47721, Saudi Arabia
Maher G. M. Abdolrasol: Department of Electric, Electronics and System Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia
Taha Selim Ustun: Fukushima Renewable Energy Institute, AIST (FREA), National Institute of Advanced Industrial Science and Technology (AIST), Koriyama 963-0298, Japan

Sustainability, 2022, vol. 14, issue 2, 1-20

Abstract: This paper aims to investigate a hybrid photovoltaic (PV) biogas on-grid energy system in Al-Ghabawi territory, Amman, Jordan. The system is accomplished by assessing the system’s reliability and economic viability. Realistic hourly measurements of solar irradiance, ambient temperature, municipal solid waste, and load demand in 2020 were obtained from Jordanian governmental entities. This helps in investigating the proposed system on a real megawatt-scale retrofitting power system. Three case scenarios were performed: loss of power supply probability (LPSP) with total net present cost (TNPC), LPSP with an annualized cost of the system (ACS), and TNPC with the index of reliability (IR). Pareto frontiers were obtained using multi-objective feasibility enhanced particle swarm optimization (MOFEPSO) algorithm. The system’s decision variables were the number of PV panels ( N pv ) and the number of biogas plant working hours per day ( t biogas ). Moreover, three non-dominant Pareto frontier solutions are discussed, including reliable, affordable, and best solutions obtained by fuzzy logic. Double-diode (DD) solar PV model was implemented to obtain an accurate sizing of the proposed system. For instance, the best solution of the third case is held at TNPC of 64.504 million USD/yr and IR of 96.048%. These findings were revealed at 33,459 panels and 12.498 h/day. Further, system emissions for each scenario have been tested. Finally, decision makers are invited to adopt to the findings and energy management strategy of this paper to find reliable and cost-effective best solutions.

Keywords: photovoltaic; biogas; hybrid systems; double-diode; multi-objective feasibility enhanced particle swarm optimization (MOFEPSO) algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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