Multi-objective synergy planning for regional integrated energy stations and networks considering energy interaction and equipment selection

Abstract

Regional integrated energy system (RIES) contains multiple energy coupling equipment and differential energy demand, which demonstrates that establishing a complete source-grid-load-storage energy supply chain is conducive to renewable energy consumption, and improves RIES economy and energy utilization efficiency. This paper proposes a synergy planning approach for RIES energy stations (ESs) and pipeline networks (PNs) with energy interaction and equipment selection. First, this paper analyzes a RIES structure involving equipment selection and energy interaction, and describes the problem to be addressed in this paper. Secondly, ten equipment output models are built based on energy coupling methods, and a RIES synergy planning model is further developed to minimize the annual total costs (ATCs) and the total electricity abandonment rate (TEAR) with various constraints. Subsequently, Elitist Non-Dominated Sorting Genetic Algorithm (NSGA-II) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) are applied to solve the Pareto solution set and best compromise solution (BCS) of this mixed-integer nonlinear model (MINLP), respectively. Finally, optimal planning combinations are selected in three scenarios so as to verify the feasibility and validity of the proposed models and method. Innovations as well as further extensions of the proposed methods, are also discussed. Optimal equipment selection and output strategy help reduce 52.42% ATCs and 19.81% TEAR. Moreover, with considerations for energy interactions, RIES synergy planning achieves higher excess electricity consumption efficiency and further 1.40 M$ savings.