Socio-techno-economic-environmental sizing of hybrid renewable energy system using metaheuristic optimization approaches

被引:5
作者
Kushwaha, Pawan Kumar [1 ,2 ,3 ]
Bhattacharjee, Chayan [1 ]
机构
[1] Natl Inst Technol Silchar, Dept Elect Engn, Silchar, India
[2] Galgotias Coll Engn & Technol, Dept Elect & Elect Engn, Greator Noida, India
[3] Natl Inst Technol Silchar, Dept Elect & Elect Engn, Greator Noida, India
关键词
biogas generator; carbon emission; cost of energy; hybrid renewable energy system; loss of power supply probability; solar photovoltaic; SIZE OPTIMIZATION; TECHNOECONOMIC OPTIMIZATION; RURAL ELECTRIFICATION; MICROGRID MODEL; DESIGN; FEASIBILITY; BATTERY; STORAGE; WIND; MANAGEMENT;
D O I
10.1002/ep.14386
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Electricity supply reliability in an electricity distribution network is majorly affected due to unexpected power failures and power cuts. A hybrid renewable energy system (HRES) with the optimal size of renewable energy sources can substantially improve power reliability. Therefore, this article develops an objective function incorporating socio-techno-economic-environmental (STEE) factors for HRES optimal sizing to supply reliable power to a rural village. The factors considered in the objective function are namely social (employment generation factor, human progress index, and land cost), technical (excess energy factor, renewable energy portion, and loss of power supply probability), economical (total net present cost, cost of energy, and annualized cost of system), and environmental (emission cost). In this article, for the first time, marine predators algorithm (MPA) based metaheuristic optimizer is devised to address the sizing optimization problem of HRES. Three HRES configurations, having different arrangements of diesel generator (DG), biogas generator (BG), battery (BAT), wind turbine (WT), and photovoltaic (PV), are examined utilizing MPA, particle swarm optimization (PSO), salp swarm algorithm (SSA), and genetic algorithm (GA) for optimal configuration. Due to the lowest value of economical and environmental factors and the highest value of the social factor, the PV-WT-BAT-BG-DG configuration is optimal compared to other investigated configurations with MPA. Comparing the four optimizers, MPA has the best STEE factor values, as well as stronger convergence, greater ability to escape from local minima, and higher ability to approach the global optimum. Additionally, by contrasting it with the PSO result for the three HRES configurations, the MPA result quality is confirmed. Furthermore, the cost of energy (0.1799 $/kWh) of the optimal configuration is less than the latest addressed in the literature.
引用
收藏
页数:22
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