Forecasting peak loads with neural networks

This paper presents a new approach to power load forecasting using artificial neural networks (ANN). Based on weather conditions and past history of load consumption, a load forecast is made by the utility companies to deliver the appropriate load to its customers. Power systems operation and planning functions such as unit commitment, security analysis, state estimation, etc. are benefited with an accurate load forecast. Improving the accuracy of the load forecast can save a significant amount of money. Artificial neural networks permit adaptability to climate changes compared to other forecasting methods in use. The results obtained by using ANN have been found to give better results than other conventional techniques.<>