Implementation of Optimization Algorithms to Solve Economic Load Dispatch Problem

Optimization problems are real world problems we encounter in many areas such as mathematics, engineering, science, business, and economics, e.g. in product and process design, production, traffic control, scheduling and even strategic planning. Optimization is a discipline of dealing with those kinds of problems where one has to minimize or maximize one or more objectives that are functions of some integer or real variables without exploiting the given constraints. For decades' scientists are researching to emerge out with modified and faster techniques. In this book, history of Optimization as well as various optimization techniques like genetic algorithm, ant colony optimization, pattern search, particle swarm optimization, Artificial Bee Colony, Simulated Annealing & Hybrid Optimization techniques have been discussed for solving various optimization problems. Due to the various optimization techniques, available nowadays the solution of every complex problems can be done in acceptable times. The results confirm superior performance of the proposed algorithms in solving many real-world problems. Therefore, Optimization is a mathematical tool to find the maximum or minimum of a function in some feasible region. There is no any industry which is not involved in the solution of optimization problems. In the operational planning of power system, Economic load dispatch (ELD) is a common task which concern with the optimization problems. The objective of ELD problem is to schedule the output of the connected units of the plant so as to fulfil the load demand at minimum operating cost while satisfying all operational constraints. Here, Genetic Algorithm & Simulated Annealing have been implemented to solve ELD problem for IEEE 5, 6, 14 bus system, Standard 15- & 20-Unit thermal generating system. Economic load dispatch problem is one of the most important ones in the power system operation and planning. The main objective of the economic load dispatch problem is to determine optimal combination of power output of all generating units so as to meet the required particular load demand at minimum cost of generation while satisfying the system constraints such as equality and non-equality constraint. The two major factors to be considered while dispatching power to generating units are the cost of generation and the quantity of power supplied. The relation between the cost of generation and the power is approximated by a quadratic polynomial equation and is solved by mathematical programming techniques. In past year numbers of techniques have been utilized to solving the economic load dispatch problem, some of these techniques are the conventional optimization techniques and some are based on the intelligent technique.The objective of this book is to study different naturally inspired intelligent optimization techniques & also to solve economic load dispatch (ELD) problem by considering equality and inequality constraints to satisfy the consumers demand. In this book standard IEEE 5, 6, 14 bus system, standard 15 & 20-unit thermal generating system have been considered for ELD operation. Here Genetic Algorithm & Simulated Annealing algorithm have been implemented to solve ELD problem.The main objective of the book work is summarized as follows.Study of different naturally inspired intelligent optimization techniques & history of optimization. Finding the solution of ELD problem, so minimization of the total fuel cost by satisfying the power system constraints.Using the GA and SA techniques to find out the optimal solution for the ELD problem.Investigate the effectiveness of these methods for ELD problem with losses.Compare the results obtained from these two methods, i.e. Genetic Algorithm (GA) and Simulated Annealing (SA).This book has been arranged in six chapters.Lt. Kishan Bhushan SahayProf. S.K. SrivastavaAbhishek Kumar

• | Author: S. K. Srivastava, Abhishek Kumar, Kishan Bhushan Sahay
• | Publisher: Independently published
• | Publication Date: Dec 02, 2018
• | Number of Pages: 173 pages
• | Language: English
• | Binding: Paperback
• | ISBN-10: 1790654270
• | ISBN-13: 9781790654277