Two-Tier Configuration Model for the Optimization of Enterprise Costs and User Satisfaction for Rural Microgrids

Yong Fang, Minghao Li, Yunli Yue and Zhonghua Liu ()
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Yong Fang: School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China
Minghao Li: School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China
Yunli Yue: Economic and Technical Research Institute, State Grid Jibei Electric Power Company Limited, Beijing 100038, China
Zhonghua Liu: School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China

Mathematics, 2024, vol. 12, issue 20, 1-19

Abstract: The construction costs and operational challenges of rural microgrids have garnered widespread attention. This study focuses on grid-connected rural microgrids incorporating wind, solar, hydro, and storage systems, and proposes a two-tier optimization configuration model that considers both enterprise costs and user satisfaction. The upper-tier model aims to minimize enterprise costs, covering construction, operation and maintenance, as well as penalties for a curtailment of wind, solar, and hydro power. The lower-tier model evaluates power reliability and cost-effectiveness to maximize user satisfaction. Using the particle swarm optimization algorithm, this study analyzes a case in Yudaokou, Hebei Province, and proposes three optimization schemes: minimizing enterprise costs, maximizing user satisfaction, and a compromise between the two. The optimal scheme, which employs 17 photovoltaic panels, 12 wind turbines, and 15 energy storage units, achieved a user satisfaction score of 0.90. This two-tier planning model provides practical insights for the rational configuration of rural microgrids and reveals the nonlinear relationship between costs and user experience.

Keywords: rural microgrid; two-tier planning; particle swarm optimization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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