Genetic algorithm based optimization of economic load dispatch constrained by stochastic wind power

Abstract

Economic load dispatch problem becomes complex, when renewable energy sources are also considered with thermal power plant. Therefore, it is challenging to find the optimal solution at lower fuel cost, such that generation meets the load demand. This paper is mainly aimed to design economic load dispatch model for thermal and wind power plants. Due to the varying nature of wind speed, probabilistic approach is used to solve the economic load dispatch problem and wind power is considered as a constraint. The genetic algorithm based optimization approach is used to solve the developed economic load dispatch problem. The main idea behind genetic algorithm is that, all generators should optimally supply the required electricity load demand at minimum fuel cost, while satisfying all the system constraints. Through GA, the feasible range of optimal solutions can be found, and the output power of thermal units can be restricted. The simulations are performed on test system, one with six thermal generators and a wind farm, using Matlab.