Optimal sizing design and integrated cost-benefit assessment of stand-alone microgrid system with different energy storage employing chameleon swarm algorithm: A rural case in Northeast China

Jianguo Zhou and Zhongtian Xu

Renewable Energy, 2023, vol. 202, issue C, 1110-1137

Abstract: This paper proposes an optimal sizing design and cost-benefit evaluation framework for stand-alone renewable microgrid system to serve rural community load usage in Northeast China. The microgrid system combines Photovoltaic arrays (PV), Wind turbines (WT), Tidal turbines (Tid), Battery (Bat) storage and hydrogen storage, respectively. The optimal component sizing is determined based on the actual local hourly meteorological data and load demand during a year using Chameleon swarm algorithm (CSA), with minimum Total net present cost (TNPC) of the microgrid system as the optimization objective and the reliability constraint is considered as Loss of power supply probability (LPSP). Meanwhile, a cost-benefit index is further introduced for conveniently evaluating the overall effectiveness of the microgrid systems. The results of the simulation experiments under the benchmark scenario reveal that the PV/WT/Tid/Bat system is the most viable approach for local load supply among different versions of the microgrid. Additionally, a thorough sensitivity investigation of the optimal sizing of two exemplary microgrid systems based on different energy storage is carried out under different techno-economic scenarios. This study can provide a more efficient and clean electrification scheme and insightful reference for investment in the power-starved Northeast China.

Keywords: Power shortage; Stand-alone renewable microgrid system; Optimal sizing design; Energy storage; Chameleon swarm algorithm; Integrated cost-benefit assessment (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:202:y:2023:i:c:p:1110-1137

DOI: 10.1016/j.renene.2022.12.005

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