Multi-objective Planning for Rural Integrated Energy System with Multi-type Energy Storage Using Interval Optimization Approach

Rural areas are abundant in renewable energy resources, such as rooftop photovoltaics, wind power, and biogas digesters, but the renewable energy utilization rate is low, resulting in renewable energy abandonment and high carbon emissions. Developing a rural integrated energy system with multi-type energy storages (RIES-MES) could promote renewable energy accommodation and reduce system carbon emissions, which could effectively address the above problems in the rural areas. This study proposes a multi-objective planning framework for RIES-MES planning decision-making and operating optimization to minimize economic costs and renewable energy utilization simultaneously. Firstly, we study comprehensive resource endowments and constructs the physical model of equipment in RIES-MES. Secondly, an optimal configuration model for RIES-MES is developed to improve economic performance and renewable energy utilization, where the uncertainties associated with renewable energy are addressed through interval optimization. Finally, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is used to solve this planning model. Numerical studies on a real-world rural energy system validate the effectiveness of the proposed planning framework.