Load Forecasting

Electric load forecasting is the process used to forecast future electric load, given historical load, weather information along with current and forecasted weather information. There is a growing tendency towards unbundling the electricity system. This is continually confronting the different sectors of the industry (generation, transmission, and distribution) with increasing demand on planning management and operations of the network. Load forecasting plays a key role in helping an electric utility to make important decisions on power, load switching, voltage control, network reconfiguration, infrastructure development, purchasing and generating electric power, load switching, and infrastructure development. Load forecasts are extremely important for energy suppliers, ISOs, financial institutions, and other participants in electric energy generation, transmission, distribution, and markets. Load forecasting is however a difficult task because the load series is complex and exhibits several levels of seasonality

systems. Daily maximum load forecasting is used for the applications like the unit commitment, security analysis of the system and the economical scheduling of the outages and fuel supply. Artificial Neural Network (ANN) is mostly used for the prediction of the load. The reason is, ANN methodology solves the complex relationships between the independent and dependent variables by a mathematical mapping algorithm. Short-term load forecasting (one hour to one week ahead) plays a key role in economic and secure system operation. Short term load forecasting displays a great ability for economic and secure operation of power. In the rapidly growing power markets like India with the limited generation capacity, this can be the powerful tool for the demand side management. Efforts are made in this work to develop, train and test an artificial neural network model which can forecast the peak load to a reasonable accuracy of a smaller area with data knowledge.