Optimal Dispatch of Generation with Valve Point Loading using Genetic Optimization Technique Shraddha Gajbhiye Assistant Professor, EED, SVITS, Indore Abstract – The economic dispatch of generation in power systems is one of the most important optimization problems for both the generating companies competing in a free electricity market and the systems operator in charge with a fair handling of transactions between electricity suppliers and their customers. The fuel cost component is still the major part of the variable cost of electricity generation, directly reflected in the electricity bills. This paper describes and introduces a solution to Economic dispatch problem with valve point loading using a nature-inspired algorithm, called Genetic algorithm. The Genetic Algorithm (GA) is a stochastic Meta heuristic approach based on the mechanics of natural selection and natural genetics. The aim is to minimize the generating unit’s combined fuel cost having quadratic cost characteristics subjected to limits on generator real power output & transmission losses. This paper presents an application of the GA to ED with valve point loading for different Test Case system. The obtained solution, quality and computation efficiency is compared to another optimization technique, called Simulated Annealing (SA). Keywords:-Economic Dispatch, Genetic Algorithm. I. INTRODUCTION Power systems analysis combines a highly nonlinear and computationally difficult environment with a need for optimality [1]. Artificial intelligence, unlike strict mathematical methods, has the apparent ability to adapt to nonlinearities and discontinuities found commonly in physical systems. The linearization and assumptions made in the economic dispatch problem present a classic example. Most industrial algorithms require the incremental cost curves to be piecewise-linear. The input-output characteristics produced by generator operation can be made to approximate this requirement. But the loss of accuracy induced by these approximations is not desirable. The genetic algorithm emulates the optimization techniques found in nature. This optimization algorithm does not require the strict continuity of classical search techniques, but allows non-linearities and discontinuities to appear in the solution space. The application of this algorithm to the economic dispatch problem uses the payoff information of an objective function to determine optimality. Therefore any type of unit characteristic cost curve may be used with adjustments only to the objective function. All metaheuristic algorithms use certain tradeoff a randomization and local search [2], [3], [4]. Most stochastic algorithms can be considered as metaheuristic and good examples are Genetic Algorithm (GA) [5], [12]. In this research paper, the genetic algorithm is used to solve the economic load dispatch with valve point loading optimization problem. This optimization problem constitutes one of the key problems in power system operation and planning in which a direct solution cannot be found and therefore metaheuristic approaches, such as the genetic algorithm, have to be used to find the optimal solutions. II. OPTIMAL DISPATCH OR ECONOMIC DISPATCH PROBLEM The classical Economic Dispatch(ED) problem is an optimization problem that determines the power output of each online generator that will result in a least cost system operating state. The objective of the economic load dispatch is to minimize the total cost of each online generators .This power allocation is done considering system balance between generation and loads, and feasible regions of operation for each generating unit. The basic economic dispatch problem can be described by the following points: a) The Fuel Cost Objective The aim is to minimize the total fuel cost (operating cost) of all committed plants can be stated as follows: International Journal of Latest Trends in Engineering and Technology (IJLTET) Vol. 5 Issue 2 March 2015 202 ISSN: 2278-621X