This preview shows pages 1–3. Sign up to view the full content.
This preview has intentionally blurred sections. Sign up to view the full version.View Full Document
Unformatted text preview: Chapter 12 LOAD FORECASTING Eugene A. Feinberg State University of New York, Stony Brook Eugene.Feinberg@sunysb.edu Dora Genethliou State University of New York, Stony Brook firstname.lastname@example.org Abstract Load forecasting is vitally important for the electric industry in the deregulated economy. It has many applications including energy pur- chasing and generation, load switching, contract evaluation, and infras- tructure development. A large variety of mathematical methods have been developed for load forecasting. In this chapter we discuss various approaches to load forecasting. Keywords: Load, forecasting, statistics, regression, artificial intelligence. 1. Introduction Accurate models for electric power load forecasting are essential to the operation and planning of a utility company. Load forecasting helps an electric utility to make important decisions including decisions on pur- chasing and generating electric power, load switching, and infrastructure development. Load forecasts are extremely important for energy suppli- ers, ISOs, financial institutions, and other participants in electric energy generation, transmission, distribution, and markets. Load forecasts can be divided into three categories: short-term fore- casts which are usually from one hour to one week, medium forecasts which are usually from a week to a year, and long-term forecasts which are longer than a year. The forecasts for different time horizons are im- portant for different operations within a utility company. The natures 269 270 APPLIED MATHEMATICS FOR POWER SYSTEMS of these forecasts are different as well. For example, for a particular region, it is possible to predict the next day load with an accuracy of approximately 1-3%. However, it is impossible to predict the next year peak load with the similar accuracy since accurate long-term weather forecasts are not available. For the next year peak forecast, it is possible to provide the probability distribution of the load based on historical weather observations. It is also possible, according to the industry prac- tice, to predict the so-called weather normalized load, which would take place for average annual peak weather conditions or worse than average peak weather conditions for a given area. Weather normalized load is the load calculated for the so-called normal weather conditions which are the average of the weather characteristics for the peak historical loads over a certain period of time. The duration of this period varies from one utility to another. Most companies take the last 25-30 years of data. Load forecasting has always been important for planning and opera- tional decision conducted by utility companies. However, with the dereg- ulation of the energy industries, load forecasting is even more important....
View Full Document