Analysis Of Power Load Forecasting Based On Intelligent Algorithm

Power load management is one of the most important works of the power systemscheduling, electricity, planning, and management departments. Improvement of thetechnical level of load forecasting will favor the planned-use of power management,reasonable arrangements for grid operation mode and generator’s unit maintenancescheduling, coal-and fuel-saving and reduce the cost of power generation, thedevelopment of rational power construction planning as well as help to improvepower economic and social benefits of the system.The short-term load forecasting, foundation to optimalize the operation of powersystem, has significant impact on power system security, reliability and economy.Currently, smart grid technology has become a new direction for the development ofthe national grid, which has increasingly demanded the load forecasting. Therefore, itis of great significance to apply intelligent algorithm of power system short-term loadforecasting and to improve the accuracy and stability of the load forecasting. Hencethis paper’s presenting the analysis of power load forecasting based on intelligentalgorithm and application of intelligent algorithm for short-term load forecasting, andstriving to improve the accuracy and speed of load forecasting has very importantpractical meaning.Based on the analysis of the current status of short-term power load forecasting,various forecasting methods, forecasting model and the electric load characteristics,the writer has considered the date type, temperature, weather conditions and otherfactors that may affect the load forecasting and forecasted the grid short-term load inTianjin with fuzzy neural network prediction method. According to the programmingmethod described in this article, actual simulation results shows that to some extentthe neural network has improved the defects of the original algorithm, and made upfor the shortcomings of a single algorithm, and that it is of practical feasibility.