The Research On Ethnic Group Evolution Algorithm For Global Numerical Optimization And Economic Load Dispatch

The economic load dispatch (ELD) problem is one of the important optimization problems in power systems that has the objective of dividing the power demand among the online generators economically while satisfying various constraints. Since ELD problem belongs to a kind of multidimensioned, discrete, nonlinear constrained numerical optimization problem, so the key of solving ELD problem is to find an effective numerical optimization algorithm. The practices prove that evolutionary algorithms (EAs) are good at global numerical optimization, which are simulated by the evolution process of nature. But some defects of EAs, such as premature convergence or converging slowly, have a heavily negative impact on the application of EAs for global numerical optimization. Enlightened by the conception of ethnic group in social science and making use of ethnic group as a view to analyze the structure and evolutionary tendency of population, a novel evolution algorithm, ethnic group evolution algorithm (EGEA), is proposed. The simulation tests prove EGEA is good at global numerical optimization. So we apply EGEA to solve ELD problem and get a good effort. The main achievements are so follows:Firstly, a kind of ethnic group evolution algorithm (EGEA/Binary), with a dual track co-evolution process and special ethnic group operators, is designed for binary coding. Race exponent, a new evaluation criterion, is designed to measure the competitive capacity of individual, which develops from the idea of keeping population balance between fitness growth and individual diversity. The simulation tests of classical function and challenging composition test function show that the EGEA/Binary can restrain premature convergence phenomenon effectively during the evolutionary process while increasing the search efficiency greatly.For the evaluation indicator and searching mechanism is different to conventional evolutionary algorithm, so it is necessary to research the selection mechanism of EGEA/Binary. We compare and analyze the performance of EGEA/Binary with several conventional selection operators for high dimensions numerical optimization problem, which make use of population and ethnic group as the selection unit and make use of fitness and race exponent as the selection indicator parameter separately, and find the capabilities of selection operator to adjust ethnic group convergence pressure are influence on the performance of EGEA/Binary heavily. Then, a novel selection operator, race exponent based annealing rank selection, is proposed, and the simulations show this selection operator can improve the search efficiency of EGEA/Binary greatly.Based on the analysis of relationship between crossover scale and reachable subspace of crossover operator, we find the crossover scale should be dynamically adjusted to population structure. Three control mechanisms, the well-phased control strategy, the random distribution strategy and the adaptation evolution strategy, are built up to adjust the crossover scale. The simulation tests of classical function show these optimization mechanisms are availably, and a kind of valuable control knowledge of crossover scale for multi-dimension functions have been generated by the adaptation evolution strategy.For binary code has some defects, so we transplant the ethnic group evolution mechanism into real code population and design another kind of ethnic group evolution algorithm--EGEA/Hierarchic. In EGEA/Hierarchic, a kind of ethnic group clusting methond based on hierarchy clustering process is used to create ethnic group organization. The comparisons between EGEA/Hierarchic and other typical algorithm for 10 typical UCOPs,6 composition functions and 13 typical COPs show EGEA/Hierarchic is a competent algorithm for solving global numerical optimization problem.Finally, we use EGEA/Binary and EGEA/Hierarchic to solve ELD problem. Five IEEE simulation system, including 3 thermal units and 6 buses system,3 thermal units system,6 thermal units system,15 thermal units system,20 thermal units system whose incremental fuel cost function took into account the valve-point effects, transmission loss and other constrains, which have been used to test the performance of EGEA/Binary and EGEA/Hierarchic. The simulation results show that EGEA/Binary and EGEA/Hierarchic have more superior performance when compared with other algorithms in the newest literatures.