Abstract
Short-Term Load Forecasting is a very relevant aspect in managing, operating or participating an electric system. From system operators to energy producers and retailers knowing the electric demand in advance with high accuracy is a key feature for their business. The load series of a given system presents highly repetitive daily, weekly and yearly patterns. However, other factors like temperature or social events cause abnormalities in this otherwise periodic behavior. In order to develop an effective load forecasting system, it is necessary to understand and model these abnormalities because, in many cases, the higher forecasting error typical of these special days is linked to the larger part of the losses related to load forecasting. This paper focuses on the effect that several types of special days have on the load curve and how important it is to model these behaviors in detail. The paper analyzes the Spanish national system and it uses linear regression to model the effect that social events like holidays or festive periods have on the load curve. The results presented in this paper show that a large classification of events is needed in order to accurately model all the events that may occur in a 7-year period.
Highlights
IntroductionShort-term load forecasting (STLF) is a determining factor for operation of an electric system
Short-term load forecasting (STLF) is a determining factor for operation of an electric system.It is a necessary process in order to ensure the balance between generation and demand
To determine whether the classification above is adequate, simplistic or overly complex, this study proposes a series of tests to determine how the accuracy of the model varies as the complexity of the classification increases
Summary
Short-term load forecasting (STLF) is a determining factor for operation of an electric system. It is a necessary process in order to ensure the balance between generation and demand. The system operator needs to know the expected load to make decisions and to perform an optimal control of the electrical system. Many countries have liberalised electrical markets, which promotes the participation of multiple agents. This participation yields a competitive system, which leads to reduced costs to the final consumer. The accuracy of load forecasting leads to an optimization of the power generation and of operation of the system and a consequent reduction of the costs. A good STLF leads to a better share of renewable energy in the electric system, reducing
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