Congestion Management in Modern Power System Containing Active Distribution Network Nodes

摘要

This article presents a novel methodology to determine a transmission congestion management strategy for a power system containing active distribution network nodes. Constrained scheduling, used in traditional pools, has been utilized. A bi-level optimization model is proposed to obtain the optimal congestion management strategy by rescheduling the distributed generators inside active distribution network nodes. The upper-level optimization model determines the generation rescheduling in the main grid and the load adjustment of each active distribution network node to relieve the congestion. The lower-level optimization model aims at minimizing load adjustment cost in the upper level by rescheduling the distributed generators. The proposed bi-level optimization model is transformed into an equivalent single-level optimization model through application of Karush-Kuhn-Tucker optimality conditions. Three heuristic algorithms-particle swarm optimization, cat swarm optimization, and clonal selection algorithm-have been applied to solve the equivalent single-level optimization problem. The effectiveness of the proposed methodology has been tested on a modified system using the IEEE 30-bus system as the main network and the IEEE 14-bus system as the active distribution network node. The results obtained by the particle swarm optimization algorithm have been compared with those obtained by cat swarm optimization and clonal selection algorithms.