Multi-objective stochastic-robust based selection-allocation-operation cooperative optimization of rural integrated energy systems considering supply-demand multiple uncertainties

• Published in: Renewable energy 2024-10, Vol.233, p.121159, Article 121159
• Main Authors: Wang, Jiangjiang, Zhao, Lei, Lu, Hao, Wei, Changqi
• Format: Article
• Language: English
• Subjects: Multi-objective optimization; Rural integrated energy system (IES); Stochastic-robust optimization; Uncertainty budget
• ISSN: 0960-1481
• DOI: 10.1016/j.renene.2024.121159

The carbon neutrality goal places greater demands on integrated energy system (IES) in rural areas. In line with this trend, a multi-objective stochastic-robust based selection-allocation-operation cooperative optimization model is established for planning of rural IES in this paper. Firstly, this paper construct three typical IESs at three levels (user, township and user-township interaction) and make economic selection. Secondly, in order to coordinate the objectives of technology-economy-environment and solve the multiple uncertainties existing in the system, a multi-objective stochastic-robust planning model is proposed. In the model, the objective function introduces indicators such as total cost, primary energy resource efficiency and renewable energy consumption rate. Then constructing stochastic hierarchical scenarios to characterize the stochastic uncertainty of parameters in the time dimension. And introducing typical scenarios into the box sets which characterize the supply-demand sides uncertainty. Finally, a sensitivity analysis is performed to discuss the influence of robustness parameters and biogas prices. The annual total cost of the user-township interaction system is 53.8 % and 8.4 % lower than that of the other two systems, respectively. And from the allocation results of selected system, primary energy resource efficiency is 0.57, total cost is 1.81 × 106 USD and renewable energy consumption rate is 99.46 %. In addition, from the operation results, it is analyzed that the output of the equipment is perfectly balanced with the user's load. Finally, it is obtained by sensitivity analysis that uncertainty budget and biogas price have an impact on the selection of discrete equipment, the capacity of continuous equipment and the total cost. And the optimal capacity of the system under different situations is given.