Investigations on non convex economic load dispatch problem and solution through constrained optimization techniques

Abstract

In the modern scenario, the electric power generation is very newlineessential and is a major criterion for all power related applications. There are newlinevarious resources available for the generation of power, but in the present era, newlineit is necessary to identify the most efficient and cost effective methodology to newlinebe adopted for generating electricity. The highest priority for continuous newlinepower delivery is the effective performance of reliable power generation newlinewhich depends on several factors, one being the thermal generating station. newlineHowever, due to the increase in demand for power, the cost of generation newlineincreases, thereby making the utilization cost very high for the human newlinecommunity. Hence, the present research provides a solution to help manhood newlineget electric power in a more economical way through active scheduling of newlinegenerators. The present research focuses on the Economic Load Dispatch newline(ELD) problem. Since it is an optimization problem, the main objective of the newlineproblem is minimization of the total generation cost, while satisfying the newlinevarious linear and non-linear constraints in order to meet the required power newlinedemanded. To optimize the ELD problem six different optimization newlinetechniques has been implemented in the present thesis. Firstly, four different optimization techniques such as Simulated newlineAnnealing (SA), Particle Swarm Optimization (PSO), Differential Evolution newline(DE) and Biogeography Based Optimization (BBO) are discussed and newlineexecuted for an ELD problem. Earlier researches have not included the nonlinear newlineconstraints like valve point loading effects, ramp rate limits and newlineprohibited operating zones, while solving the ELD problem by these methods. newlineThe present research considers all linear and non-linear constraints for solving newlinethe ELD problem by the above said methods. Of the above mentioned newlinemethods, the BBO gives better results in terms of minimum total generation newlinecost and transmission loss. Secondly, a new optimization technique known as Efficient Hybrid newlineSimulated Annealing (EHSA)