Development of evolutionary models for long-term load of power plant systems

Summary form only given. Load forecasting has become one of the major research areas in electrical engineering and computer science. Many of the traditional forecasting and artificial intelligent techniques are explored. We introduce evolutionary computation as a tool for developing new model structures to forecast power plant loads. We are exploring the use of genetic programming (GP) as a tool to build various model structures for electricity load forecasting. The developed GP models consider long-term load forecasting. The models are developed using real-measurements taken from commercial, domestic, farming, industrial and public lightning applications. The developed GP model results are very promising compared to traditional model structures.