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

• Published in: Energy (Oxford) 2025-03, Vol.318, p.134745, Article 134745
• Main Authors: Xu, Xinyin, Yang, Liu, Liu, Yan, Cao, Qimeng, Feng, Hengli
• Format: Article
• Language: English
• Subjects: Biologically–inspired algorithms; Carbon reduction cost; Dual-objective optimization; Economy; Solar-driven energy system
• ISSN: 0360-5442
• DOI: 10.1016/j.energy.2025.134745

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. •Numerical simulation proposed for solar energy system under the power-to-heat concept.•Optimization model developed for solar energy system to identify the technological portfolio.•Optimal configuration evaluations and economic–technical and energy utilization analysis.