Optimal Congestion Management by Load Curtailment in Electricity Market

Abstract

Abstract A novel bi-level framework is developed for congestion management in electric power market by load curtailment and generator rescheduling. Interruptible load auction schemes are performed to detect the load buses which require corrective measures to relieve congestion. The proposed congestion management problem is solved in two different levels. The objective functions formulated as non-linear equation is solved using swarm intelligence techniques. In first level, the load curtailment problem is solved, while in second level the generator rescheduling problem is solved. Generator rescheduling through swarm based optimization techniques minimizes the curtailment of contracted power in a deregulated market. A comparative study has been carried out on the swarm intelligence techniques such as Cauchy Gaussian infused PSO (CGI-PSO) and Particle Swarm Optimization with Time Varying Acceleration Coefficient (PSO-TVAC) to solve the proposed problem. The formulated methodology is simulated on standard IEEE 30 bus system and verified through Indian utility-69 bus system.