Optimization of Power System Scheduling Based on Shuffled Complex Evolution Metropolis Algorithm

Abstract

Due to the world’s increasingly serious energy crisis, shortage of resources, and environmental degradation, traditional power system analysis and scheduling optimization methods have faced new challenges. This article examines the features of optimal scheduling of power system containing cascade hydropower, and establishes a scheduling model based on the Shuffled Complex Evolution Metropolis (SCEM-UA) algorithm. This model takes the cost of power generation, emission of gaseous pollutants, and the characteristics of the generators fully into account. Constraints on the changes in thermoelectric generator power output were added to the set of constraint conditions, reducing the impact of thermal power fluctuations on the power system. Here, the SCEM-UA algorithm was used to solve the problem of optimal power system scheduling and render the model capable of global optimization searches. Analyses of simulated cases have demonstrated that the SCEM-UA algorithm can resolve the conflict between convergence speed and global search capability, increasing the global search capability of the model.