A hybrid robust-interval optimization approach for integrated energy systems planning under uncertainties. (1st July 2023) - Dong, Yingchao; Zhang, Hongli; Ma, Ping; Wang, Cong; Zhou, Xiaojun
Abstract: The presence of multiple uncertainties in demand response and renewable energy generation significantly impeded the planning of integrated energy systems (IES). To address this challenge, a novel hybrid robust-interval optimization (HRIO) framework was proposed in this study to facilitate flexible and robust uncertainty planning while reducing IES operation costs. The framework integrated robust optimization and interval analysis to account for the uncertainties associated with renewable energy generation output and demand response. To model IES planning as a deterministic bi-objective optimization problem with investment operation cost and robustness as the optimization objectives, a constrained multi-objective transition algorithm was developed to solve the problem. Simulation results obtained from a typical IES planning case demonstrated the efficacy of the proposed HRIO method in effectively coordinating the relationship between the system's economy, robustness, and operation reliability. This study provided a theoretical guideline for IES operators and exhibited significant potential for engineering applications. Highlights: A hybrid robust-interval optimization approach for IES planning is proposed. A constrained multi-objective state transition algorithm is developed. The effectiveness of the proposed approach is verified by a typical case.