IJSRD - International Journal for Scientific Research & Development| Vol. 2, Issue 03, 2014 | ISSN (online): 2321-0613 All rights reserved by www.ijsrd.com 1213 Economic Load Dispatch of IEEE-26 Bus System with the use of Ant Colony Optimization Technique Pirmahamad Jamalbhai Vasovala 1 Chinmay Y. Jani 2 Vasim H. Ghanchi 3 Parth Harshad Kumar Bhavsar 4 1,3, 4 PG Student 2 Assistant Professor 1, 2, 3 Electrical Engineering Department 1, 2, 4 Parul Institute of Engg & Technology, Vadodara 3 The Maharaja Sayajirao University of Baroda, Vadodara Abstract--- Optimal System operation involves the Consideration of economy of operation, system security, emission of certain fossil-fuel plant. The main aim of this study is to minimize the fuel cost and to keep the power outputs of the generator within prescribed limit with the use of An Ant colony Optimization Techniques. It is based on the ideas of ant foraging by pheromone communication to make path. Ant Colony Optimization technique is a meta- heuristic approach for solving hard combinatorial optimization problems which can be applied for power system optimization. The work reported in this paper is carried out with the objective to make use of Ant colony Optimization for solving the economic load dispatch problem. IEEE-26 Bus 6 generator system is considered to test the Algorithm with cost functions. The proposed approach result has been compared to those which reported in the literature. Keywords: Ant Colony Optimization, Optimal power flow, meta-heuristic, IEEE Systems, power systems, optimization. I. INTRODUCTION Electric power grids are considered to be one of the most complex man-made systems mainly due to their wide geographical coverage, various transactions among different utilities, and diversity in individual electric power companies’ layouts, size, and equipment used. Engineers need special tools to optimally analyze, monitor, and control different aspects of such sophisticated system. Some of these tools are economic dispatch, unit commitment, state estimation, automatic generation control, and optimal power flow. The main objective of electrical power utility is to ensure that electrical energy requirement from the consumer is delivered. However for doing so, the power utility has also to confirm that the electrical power is generated with reduced cost. So for economic operation of the system, the total demand must be equally shared among the generating units with an objective to minimize the total generation cost for the system. Economic Dispatch is a method to find the electrical power to be generated by the committed generating units in a power system so that the total generation cost of the system is minimized, with satisfying the load demand simultaneously. To show this problem, optimization is a necessary in solving the cost minimization problems. Power system optimization is an important area in the operation, planning and control of power systems. Many advanced heuristic techniques to the solution of complex power system optimization problems have been proposed, each differing in their procedure of representation, implementation and solution procedure: Economic load dispatch is one of the basic problems in power system operation and planning. It is defined as the process of giving generation levels to the generating units so that the system load is supplied fully and most economically. It concerned on the reduction of an objective function, usually the total cost of generation, while considering both the equality and inequality constraints. Load variation depends upon the output of generators has to be changed to meet the balance between loads and generation power to make the system efficient. There are a lot of conventional optimization techniques which are applied in solving the ELD problems that are briefly listed in literature reference [8] such as Newton- based techniques , Linear Programming, Non-Linear Programming , Quadratic Programming , Interior point methods , Parametric method , Sequential and unconstrained minimization technique . However, these methods usually suffer from some disadvantages such as convergence to local solutions instead of global ones if the initial guess is in the vicinity of a local solution, applicability to a specific ELD problem based on its mathematical nature and some inherent theoretical assumptions (such as convexity, differentiability, and continuity) which are inconsistent with the actual OPF formulations [8]. Several stochastic search techniques are also listed and discussed briefly by the researchers of [8] such as genetic algorithms (GA), evolutionary programming (EP), particle swarm optimization (PSO), bacteria foraging (BF) algorithm [8] Ant colony optimization (ACO)[9] have been proposed to solve the OPF problem without any restriction on the shape of the cost curves. The results reported were promising and encouraging for further research in this direction. The remaining parts of the paper are organized as follows. In the second section, the formulation of ELD problem is briefly introduced. The ant colony optimization algorithm described in section three. The proposed ACO and its application for the solution of the ELD problem are presented in section four. Obtained numerical results from extensive testing of the proposed solution approach on different case studies are presented in section five and compared with the results of several other recently published methods. Section six concludes the paper.