Optimal Modeling and Feasibility Analysis of Grid-Interfaced Solar PV/Wind/Pumped Hydro Energy Storage Based Hybrid System

Isaac Amoussou, Emmanuel Tanyi, Ahmed Ali (), Takele Ferede Agajie, Baseem Khan (), Julien Brito Ballester and Wirnkar Basil Nsanyuy
Additional contact information
Isaac Amoussou: Department of Electrical and Electronic Engineering, Faculty of Engineering and Technology, University of Buea, Buea P.O. Box 63, Cameroon
Emmanuel Tanyi: Department of Electrical and Electronic Engineering, Faculty of Engineering and Technology, University of Buea, Buea P.O. Box 63, Cameroon
Ahmed Ali: Department of Electrical and Electronic Engineering Technology, Faculty of Engineering and the Built Environment, University of Johannesburg, Cnr Kingsway & University Roads, Auckland Park, P.O. Box 524, Johannesburg 2092, South Africa
Takele Ferede Agajie: Department of Electrical and Electronic Engineering, Faculty of Engineering and Technology, University of Buea, Buea P.O. Box 63, Cameroon
Baseem Khan: Department of Electrical and Computer Engineering, Hawassa University, Hawassa P.O. Box 05, Ethiopia
Julien Brito Ballester: Department of Project Management, Universidad Internacional Iberoamericana, Campeche 24560, Mexico
Wirnkar Basil Nsanyuy: Department of Electrical and Electronic Engineering, Faculty of Engineering and Technology, University of Buea, Buea P.O. Box 63, Cameroon

Sustainability, 2023, vol. 15, issue 2, 1-30

Abstract: Access to inexpensive, clean energy is a key factor in a country’s ability to grow sustainably The production of electricity using fossil fuels contributes significantly to global warming and is becoming less and less profitable nowadays. This work therefore proposes to study the different possible scenarios for the replacement of light fuel oil (LFO) thermal power plants connected to the electrical network in northern Cameroon by renewable energy plants. Several scenarios such as the combination of solar photovoltaic (PV) with a pumped hydro storage system (PHSS), Wind and PHSS and PV-Wind-PHSS have been studied. The selected scenarios are evaluated based on two factors such as the system’s total cost (TC) and the loss of load probability (LOLP). To achieve the results, metaheuristics such the non-dominated sorting whale optimization algorithm (NSWOA) and non-dominated sorting genetic algorithm-II (NSGA-II) have been applied under MATLAB software. The optimal sizing of the components was done using hourly meteorological data and the hourly power generated by the thermal power plants connected to the electrical grid. Both algorithms provided satisfactory results. However, the total cost in the PV-PHSS, Wind-PHSS, and PV-Wind-PHSS scenarios with NSWOA is, respectively, 1%, 6%, and 0.2% lower than with NSGA-II. According to NSWOA results, the total cost for the PV-Wind-PHSS scenario at LOLP 0% is 4.6% and 17% less than the Wind-PHS and PV-PHSS scenarios, respectively. The profitability study of all three scenarios showed that the project is profitable regardless of the scenario considered.

Keywords: thermal power plants; wind; PV; LOLP; NSWOA; NSGA-II PHS; renewable energy; total cost (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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