Multi-Objective Economic Emission Dispatch using Backtracking Search Optimization Algorithm
V. Jaya Vaishnavi1, A. Srinivasa Reddy2

1V. Jaya Vaishnavi, Department of Electrical & Electronics, Sir. C. R. Reddy College of Engineering Affiliated to Andhra University, Vatluru, Eluru, Pin-534007,West Godavari District, India.
2Dr. A. Srinivasa Reddy, Department of Electrical & Electronics, Sir. C. R. Reddy College of Engineering Affiliated to Andhra University, Vatluru Eluru, Pin-534007, West Godavari District, Andhra Pradesh, India.
Manuscript received on December 20, 2014. | Revised Manuscript received on December 22, 2014. | Manuscript published on December 25, 2014. | PP:39-46 | Volume-3, Issue-2, December 2014. | Retrieval Number: B0882123214

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Abstract: To provide reliable and uninterrupted electrical supply to consumers, electrical utilities face many economic and technical problems in operation, planning and control of power systems. Most of the power system optimization problems like economic load dispatch include complex and non-linear characteristics with heavy equality and inequality constraints. Cost minimization of power generation is one of the most important power system problems. In this project, an attempt is made to minimize the cost for generation in a power system. The aim of this project is to find the optimum set of power to be generated for a given loading conditions. Equality constraint which is the relation between power generated, losses and power demand is taken into account. In this thesis, transmission losses have not been taken. Inequality constraints such as the maximum and minimum generation values for each of the generators are also considered along with valve point loading. This paper introduces backtracking search optimization algorithm (BSA), a new evolutionary algorithm (EA) for solving real-valued numerical optimization problems .EA’s are popular stochastic search algorithms that are widely used to solve non-linear, non-differentiable and complex numerical optimization problems. Unlike many search algorithms, BSA has a single control parameter. BSA has a simple structure that is effective, fast and capable of solving multi modal problems and that enables it to easily adapt to different numerical optimization problems. BSA’s strategy for generating a trail population includes two new crossover and mutation operators.BSA strategies for generating trail populations and controlling the amplitude of the search-direction matrix and search space boundaries give it very powerful exploration and exploitation capabilities. In particular BSA possesses a memory in which it stores a population from a randomly chosen previous generation for use in generating the search-direction matrix. Thus BSA’s memory allows it to take advantage of experiences gained from previous generations when it generates a trail preparation. The proposed algorithm is applied to EED problem. The purpose of EED is to obtain the optimal amount of generated power for the generating unit in the system by simultaneously minimizing the fuel and emission costs. To demonstrate the effectiveness of this method BSA have been performed on 6-unit system with valve point loading effect to obtain lesser fuel and emission costs
Keywords: Economic Dispatch, Emission Dispatch, Multi-objective optimization, Backtracking search optimization algorithm, Trade-off curve