Load forecasting has become one of the major areas of research in electrical engineering and is an important problem in operation and planning of electric power generation. Load forecasting is the technique for prediction of electrical load. STLF (Short term load forecast) is essential for Power system planning. In a deregulated market it is much need for a generating company to know about the ...

Short-term load forecasting (STLF) plays an important role in the operational planning security functions of an energy management system. The short term load forecasting is aimed at predicting electric loads for a period of minutes, hours, days or week for the purpose of providing fundamental load profiles to the system. The work presented in this paper makes use of PSO based local linear wavel...

The ability of Artificial Neural Network (ANN) for estimating the natural gas demand load for the next day and month of the populated cities has shown to be a real  concern. As the most applicable network, the ANN with multi-layer back propagation perceptrons is used to approximate functions. Throughout the current work, the daily effective temperature is determined, and then the weather data w...

With the development of economy and the progress of science, the proportion of electrified railway load in the power gird has been keeping on increasing, which impacts the short-term forecasting in load a lot, therefore, it is very important to analyze short-term load of electrified railway forecasting. This paper analyzes the power gird load-forecasting considering the influence of the electri...

This paper presents an optimization algorithm to solve the short-term load forecasting problem more quickly and accurately in progress of smart grid development. The new approach employs generalized regression neural network (GRNN) to select influence factors of short-term load, and then a least squares-support vector machine (LS-SVM) based on harmony search algorithm (HS) optimization algorith...

As an important part of power system planning and the basis of economic operation of power systems, the main work of power load forecasting is to predict the time distribution and spatial distribution of future power loads. The accuracy of load forecasting will directly influence the reliability of the power system. In this paper, a novel short-term Empirical Mode Decomposition-Grey Relational ...

Short term load forecasting can be made effective and closer to actual demand by applying the suggested multi pronged approach of genetic, fuzzy and statistical method as discussed in this paper. Taking the advantages of global search abilities of evolutionary computing as well as expert inference based on statistical aspects, load forecasting can be made nearly error free. The results were com...

This study proposes using a random forest model for short-term electricity load forecasting. This is an ensemble learning method that generates many regression trees (CART) and aggregates their results. The model operates on patterns of the time series seasonal cycles which simplifies the forecasting problem especially when a time series exhibits nonstationarity, heteroscedasticity, trend and m...

 Abstract—This article presents the review of the computing models applied for solving problems of midterm load forecasting. The load forecasting results can be used in electricity generation such as energy reservation and maintenance scheduling. Principle, strategy and results of short term, midterm, and long term load forecasting using statistic methods and artificial intelligence technology...