An Analysis of Stochastic Wind Power Approach for Economic Load Dispatch Optimization Using Genetic Algorithm

Abstract

Due to the continuous development of electrical and electronic products in the market, the need for power is growing quickly. Also, as the population increases, the need for electricity rises and this creates a task for load management. This primary task has been moved to enhance performance, cost reduction of the solution to make it optimal and development of a dependable and effective system in order to meet the need for electricity. Both the conventional and non-conventional generation methods are required to supply the growing demand for electricity. With passage of time rapid changes incur in energy systems, because conventional sources are depleting as the time goes on and becoming expensive whereas the demand for electricity and generation must be balanced to ensure the stability of the power system. The most effective solution is chosen using the economical load dispatch strategy for generation units in terms of power output and operational fuel costs. The main goal of this article is to create a cost-effective solution for wind power plants. Genetic algorithm (GA) is proposed to ensure optimization strategy. This method is mostly focused on the use of state-of-the-art tool MATLAB but by introducing genetic operators. The basic principle of the Genetic Algorithm (GA) is that all generators can provide the required electric power supply at the lowest possible fuel cost while maintaining system limits in range. Two separate test systems, first one with separate thermal generators which are six in numbers while other is wind power unit; were used for the simulation purpose. The concept and layout of the methodology that employs the genetic algorithm as an optimization tool are discussed in this work.