Techno-economic analysis and optimal sizing of a battery-based and hydrogen-based standalone photovoltaic/wind hybrid system for rural electrification in Cameroon based on meta-heuristic techniques

• Published in: Energy conversion and management Vol. 280; p. 116794
• Main Authors: Wankouo Ngouleu, Clint Ameri, Koholé, Yemeli Wenceslas, Fohagui, Fodoup Cyrille Vincelas, Tchuen, Ghislain
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15-03-2023
• Subjects: Hybrid systems; Meta-heuristic algorithms; Optimal sizing; Photovoltaic/wind/battery; Photovoltaic/wind/fuel cell; Rural electrification; Hybrid systems; Photovoltaic/wind/battery; Optimal sizing; Meta-heuristic algorithms; Photovoltaic/wind/fuel cell; Rural electrification
• ISSN: 0196-8904; 1879-2227
• DOI: 10.1016/j.enconman.2023.116794

•Optimal sizing of six distinct hybrid systems based on PV, Wind and FC energy.•PV/wind/battery is best option for Kousseri, Cameroon based on real data.•Four meta-heuristics optimization algorithms are compared.•The lowest cost of energy (0.1959$/kWh) was obtained for heavy activity.
In developing nations, particularly in African countries, where difficulties with rural electrification are highly severe, hybrid power systems appeared as a suitable method of distributing power to rural and off-grid locations. Cameroon, like other African countries, is facing a serious challenge of access to basic energy services for its population. The country's constraints present a global situation of less than 48% of the population having access to electrical energy. This situation is more frequent in rural areas. In this paper, a comparative assessment of meta-heuristics optimization techniques is conducted for optimal design of photovoltaic/wind/fuel cell and photovoltaic/wind/battery hybrid systems to constantly supply-three typical loads demand in Kousseri, Cameroun. For this purpose, four well-known meta-heuristics techniques namely artificial bee colony algorithm, cuckoo search algorithm, imperialist competitive algorithm and big bang-big crunch algorithm are implemented to solve the optimization problem, consisting of minimizing the net present cost while increasing the system reliability characterized by loss of power supply probability. Four others configurations namely photovoltaic/battery, wind/battery, photovoltaic/fuel cell and wind/fuel cell are also evaluated and the outcomes are compared with the results of the photovoltaic/wind/fuel cell and photovoltaic/wind/battery systems with regards to the life-cycle cost and cost of energy. To determine the most affordable configurations, simulations and optimizations studies are conducted. Our findings revealed that, the cuckoo search algorithm performs better than other algorithms. The results also show that, photovoltaic/wind/battery standalone hybrid system is the more reliable and cost-effective configuration for satisfying the three typical electrical loads demand encountered at Kousseri, Cameroon. The obtained optimal number of component and cost of energy of the photovoltaic/wind/battery hybrid systems are as follows: for heavy activity the optimal system integrates 27 PV panels, 1 wind turbine, 38 batteries banks, 1 inverter and the obtained cost of energy corresponds to 0.1959$/kWh; for medium activity, 13 PV panels, 1 wind turbine, 26 batteries banks and 1 inverter which resulted to a cost of energy of 0.2386$/kWh and for small activity, the best configuration includes 19 PV panels, 5 wind turbines, 18 batteries banks and 1 inverter with a cost of energy of 0.2641$/kWh.