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Authors
Affiliations
1 Dept. of EEE, Anna University, Coimbatore, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 3, No 1 (2011), Pagination: 74-78
Abstract
Scarcity of energy resources, increasing power generation cost and ever-growing demand for electric energy necessitates optimal economic dispatch in today’s power systems. The main objective of economic dispatch is to reduce the total power generation cost, while satisfying various equality and inequality constraints. Traditionally in economic dispatch problems, the cost function for generating units has been approximated as a quadratic function which doesn’t provide accurate results. Moreover, to obtain accurate fuel cost, valve-point effect in thermal power plant has to be taken into account. The inclusion of valve-point effect makes the modeling of the fuel cost functions of generating units more practical. In this paper a new hybrid evolutionary algorithm called Hybrid PSO, has been employed to solve economic dispatch problem with the valve-point effect. The hybrid technique combines Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The proposed algorithm is modeled on the concepts of Darwin’s theory based on natural selection and evolution, and on cultural and social rules derived from the swarm intelligence. Using Hybrid PSO technique the non-linear cost function is solved for three unit system and the results are compared with the traditional PSO, DE (Differential Evolution) and GA method. These results prove that Hybrid PSO method is capable of getting higher quality solution including mathematical simplicity, fast convergence, and robustness to solve hard optimization problems.
Keywords
Economic Dispatch, Genetic Algorithm, Particle Swarm Optimization, Differential Evolution, Valve Point Effect, Hybrid PSO.
