Research Of Intelligent Engineering System And Its Application In Power Load Forecasting

Intelligent Engineering is a computer application system with intelligent algorithms, based on knowledge automated processing and effective application. It emphasizes on human intelligence using and intelligent algorithms applications, shows good adaptability and maneuverability in the process of complex problem solving. Load forecasting is very important for power system planning and design, it changes because of many factors such as weather, economy and so on. So it's appropriate and necessary for such a complex system to use IE theory. Load forecasting technology is the processes form off-line analysis to online application and form being dependent on the experience of worker to automated and intelligent. We believe that load forecasting based on IE must bound to attract more and more attention.This paper analyzes the theory of IE theory and load forecasting system, presents IE-load forecasting system and does structure analysis and interface design for it. The IE-load forecasting system provides a new way of thinking for load forecasting going more accurate, more intelligent and more useful.For the algorithms library of the IE-load forecasting system, this paper found regression model, support vector machine model, sequential minimal optimization model and improved SMO model. Form the simulation experiments, the paper compares the prediction accuracy and convergence time of the four models and provides theoretical basis and programming basics for the IE-load forecasting system.For the large and nonlinear characteristics of historical data, this paper introduces empirical mode decomposition algorithm to data preprocessing, presents EMD-ISMO algorithm. The experimental results show that, EMD-ISMO algorithm can achieve good experimental accuracy and computation speed.In addition, for our country strong and smart grid has just begun but fast development, through study and training in the relevant sectors, this paper systematically analyzes the process of our smart grid development from the start to implementation of the grand blueprint, it can make up for the lack of references is very limited.