Improved hybrid algorithm-based optimization for Integrated Energy Distribution Network System: minimizing voltage deviation, line losses, and costs

Abstract

To address the siting and sizing of an integrated energy distribution network system incorporating PV, WT, EV, SVC, and BES, as well as the operational planning of SVC and BES, this paper proposes an improved hybrid algorithm. In the first stage, a multi-objective genetic algorithm is adopted to plan the siting and sizing of each device in the integrated energy distribution network. In the second stage, based on the siting and sizing results, an adaptive particle swarm optimization algorithm is utilized to schedule the daily energy storage dispatch and reactive power output. Through this two-stage optimization, the issues of unbalanced load distribution and voltage quality in the distribution network are resolved, while minimizing investment costs. The IEEE 69-node simulation results demonstrate that under the optimal scenario, the average voltage deviation of the distribution system remains stable at 1.0 p.u., the line loss rate decreases to 2.90 %, and the initial construction cost and operational cost reach 120,220,000 CNY and 16,923.88 CNY, respectively. Compared with similar algorithms, the proposed hybrid algorithm achieves a 34.5% improvement in loss reduction, significantly enhances voltage stability, and reduces daily operational costs by 9.91 %, demonstrating its effectiveness and superiority.