A multi-objective scheduling method for smart grid loads based on improved GSO algorithm

Abstract

When the traditional scheduling method is applied to the smart grid, it is difficult to adapt to the characteristics of fast changing grid load and multiple scheduling objectives, which leads to problems such as low economy and slow scheduling response rate. In order to improve the above problems, a multi-objective scheduling method for smart grid loads based on the improved GSO algorithm is studied. After predicting the short-term load changes of the smart grid using the maximum Lyapounov exponent method, a grid load scheduling model is established with the objectives of economy, environmental protection and reliability. The GSO algorithm is improved by using simulated annealing algorithm to solve the grid load scheduling model to achieve multi-objective scheduling of grid loads. The comparison experiment verifies that the scheduling method improves the scheduling response rate by at least 37.5%, and effectively reduces the scheduling cost with reliability.