Dual-objective optimization of solar-driven energy system for rural households in solar-rich areas

Xinyin Xu, Liu Yang, Yan Liu, Qimeng Cao and Hengli Feng

Energy, 2025, vol. 318, issue C

Abstract: Poverty in terms of conventional energy but abundant renewable energy resources coincide in solar-rich areas, so the on-site supply of solar energy is essential for alleviating energy poverty and decarbonizing buildings. We propose a novel energy structure based on a solar-driven energy system combining battery and thermal storage under the power-to-heat concept. Dual-objective optimization models were developed for PV–PT hybrid system and PV–dominant system to identify the optimal technological portfolio and design parameters with the aim of minimizing both the annual total cost (ATC) and carbon emission intensity (CEI), and the models were solved using the biologically–inspired algorithms. Considering a rural household in Lhasa as an example, the optimum design consists of 1.7 kW of photovoltaic (PV), 28.2 m2 of photothermal (PT), 4.8 kWh of battery, 1.7 m3 of thermal storage, and 3.2 kW of auxiliary heat source. The ATC is 44.5 % lower than that using conventional energy and CEI can be reduced by 94.8 %. Furthermore, the proposed system could achieve a CO2 reduction cost of 0.3 CNY·kg−1, compared with the two PV–dominant systems, i.e., 2.8 and 0.5 CNY·kg−1 CO2, respectively. The proposed methodology can identify the optimal technology portfolio and balance environmental with economic.

Keywords: Solar-driven energy system; Dual-objective optimization; Biologically–inspired algorithms; Carbon reduction cost; Economy (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:318:y:2025:i:c:s0360544225003871

DOI: 10.1016/j.energy.2025.134745

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