TY - JOUR
T1 - Technical and economic study of the replacement of LFO thermal power plant by hybrid PV-PHSS system in Northern Cameroon
AU - Amoussou, Isaac
AU - Agajie, Takele Ferede
AU - Tanyi, Emmanuel
AU - Khan, Baseem
N1 - Publisher Copyright:
© 2022 The Author(s)
PY - 2023/12
Y1 - 2023/12
N2 - Access to clean, cost-effective, and available energy is essential for the sustainable development of a country. Nowadays, the production of energy from fossil fuels has environmental and economic disadvantages. In this context, this work proposes to study the technical and economic aspects of the replacement of a 20 MW Light Fuel Oil (LFO) thermal power plant by a hybrid Photovoltaic Pumped Hydro Storage System (PV-PHSS) power plant in northern Cameroon. The objective is to minimize the total life cycle cost (TLCC) of the proposed hybrid system with a loss of power supply probability (LPSP) below a defined limit. To obtain optimal results, several meta-heuristics such as Artificial Bee Colony (ABC), Water Cycle Algorithm (WCA), Grey Wolf Optimizer (GWO), and African Vulture Optimization Algorithm (AVOA) have been used. Moreover, the optimal sizing of the hybrid system components was performed under MATLAB software using real-time information and meteorological data from the selected site. All the algorithms achieved good results. However, the WCA algorithm delivered a slightly better result than the other algorithms.
AB - Access to clean, cost-effective, and available energy is essential for the sustainable development of a country. Nowadays, the production of energy from fossil fuels has environmental and economic disadvantages. In this context, this work proposes to study the technical and economic aspects of the replacement of a 20 MW Light Fuel Oil (LFO) thermal power plant by a hybrid Photovoltaic Pumped Hydro Storage System (PV-PHSS) power plant in northern Cameroon. The objective is to minimize the total life cycle cost (TLCC) of the proposed hybrid system with a loss of power supply probability (LPSP) below a defined limit. To obtain optimal results, several meta-heuristics such as Artificial Bee Colony (ABC), Water Cycle Algorithm (WCA), Grey Wolf Optimizer (GWO), and African Vulture Optimization Algorithm (AVOA) have been used. Moreover, the optimal sizing of the hybrid system components was performed under MATLAB software using real-time information and meteorological data from the selected site. All the algorithms achieved good results. However, the WCA algorithm delivered a slightly better result than the other algorithms.
KW - LPSP
KW - Optimizations techniques
KW - PHSS
KW - Total life cycle cost
UR - https://www.scopus.com/pages/publications/85143873381
U2 - 10.1016/j.egyr.2022.11.181
DO - 10.1016/j.egyr.2022.11.181
M3 - Article
AN - SCOPUS:85143873381
SN - 2352-4847
VL - 9
SP - 178
EP - 194
JO - Energy Reports
JF - Energy Reports
ER -
