The Application And Research In Economic Dispatch Using Intelligence Algorithm

Economic dispatch (ED) problem is one of the fundamental issues in power system operation and analyze, which pertains to optimum generation in an interconnected power system to minimize the cost of generation or the quantity of all the fuel subject to relevant users demand and system securities. So, the researches on ED problem can reduce the cost of generating electricity, cut down the fuel consume, mean significance to our economical community.The ED problem can be described as certain non-linear mathematics model. The research on the ED problem is based on classical power system theoretic using power flow analyzing and mathematics optimization techniques. The actual power system model is very complex, so the conversion to abstract mathematics model often ignores the non-linear, discrete, stochastic and some other characteristic in the actual system. Even so, conventional method in solving still has shown the great limitations. In recent years, the emergence of a series of intelligent algorithm brought a large number of new methods to solve this problem. This paper is on the basis of our own algorithm research results continuing to perfect, improve and explore new for the solution of this problem. Based on a number of examples in the calculation of the same calculation size (the number of particles is different and the evolutionary time is different, but the product is same) to simulate and test, the results proved that: The methods advanced in this paper can succeed these optimization problems, and has better convergence and system robustness.In this paper, the work accomplished: (1) the usage of Quantum-behaved Particle Swarm Optimization (QPSO) algorithm to solve the economic dispatch problem of the power system; (2) in the process of QPSO algorithm to optimize the operation of ED problem, use the local optimization-POWELL method to search better solutions to enhance the convergence of the particles.