Research on Multi-Objective Optimization Strategy of Active Distribution Network Based on Network Reconfiguration and Demand Response

The widespread integration of distributed generation (DG), primarily based on renewable energy source (RES), poses challenges to distribution networks, including supply-demand imbalance, large voltage fluctuations, increased network losses, and heightened scheduling complexity. Despite network reconfiguration and demand response (DR) being effective tools for optimal scheduling, joint research on their application remains limited and their comprehensive potential has yet to be fully explored. To tackle these issues, this paper proposes a multi-objective optimization strategy for active distribution network (ADN) based on network reconfiguration and DR. Firstly, mathematical models for loads and DG are established, considering their time-varying characteristics. Then, aiming to minimize system voltage deviations, enhance operational economy, and promote daily load balancing, a multi-objective regulation model for distributed energy resources (DER) in ADN is constructed, taking into account the time-of-use (TOU) tariff mechanism and network switch configuration. To solve the optimization problem, second-order cone relaxation (SOCR) technology is applied to transform the optimization problem into a mixed integer second-order cone programming (MISOCP) model that can be solved efficiently, rapidly and accurately. Finally, the effectiveness of the proposed strategy in improving operational efficiency and economy is demonstrated through testing on the IEEE 33-bus system.