Optimal sizing of standalone hybrid renewable energy system based on reliability indicator: A case study

•Techno-economic analysis of hybrid solar-wind-biomass-battery system is proposed.•Numerical modelling and varied operational scenarios for the system are formulated.•Evaluating system feasibility across various power loss probabilities is conducted.•Giza Pyramids construction outperformed by $177 s...

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Bibliographic Details
Published inEnergy conversion and management Vol. 310; p. 118490
Main Authors Gusain, Chetan, Nangia, Uma, Tripathi, Madan Mohan
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 15.06.2024
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ISSN0196-8904
1879-2227
DOI10.1016/j.enconman.2024.118490

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Summary:•Techno-economic analysis of hybrid solar-wind-biomass-battery system is proposed.•Numerical modelling and varied operational scenarios for the system are formulated.•Evaluating system feasibility across various power loss probabilities is conducted.•Giza Pyramids construction outperformed by $177 saving and 8% less simulation time. The economical electrification of rural settlements extensively utilizes renewable energy sources. In recent years, the deployment of solar photovoltaic, wind turbine, and biomass gasifier-based power generation technologies for electricity accessibility in remote regions has received greater prominence. This paper presents an optimal component design of a hybrid solar PV-wind and battery system along with a biomass gasifier to provide continuous electricity for rural communities of Uttarakhand, India. In this study, a recently developed population-based giza pyramids construction (GPC) methodology is applied to determine the optimal component sizing. The findings of the GPC method are contrasted with the particle swarm optimization (PSO) methodology to assess the effectiveness of the proposed method. The annualized system cost and levelized cost of energy of the hybrid renewable energy system have been minimized subject to technical reliability indicators such as loss of power supply probability and renewable fraction. Moreover, a systematic exploration of the system has been conducted to assess its optimal feasibility across different values of power loss probability ranging from (0% to 4%). The simulation indicates that the proposed method adeptly identifies globally optimal values, leading to a $177 decrease in annual cost and 8% reduction in average simulation time compared to PSO. The research reveals that the balanced point (relative attainment), where system reliability and cost-effectiveness intersect optimally, is achieved at a 3% power loss level, resulting in the most significant cost reduction of $199 compared to other probability levels.
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ISSN:0196-8904
1879-2227
DOI:10.1016/j.enconman.2024.118490