This paper focuses on the study of short term load forecasting (STELF) using interval Type-2 Fuzzy Logic (IT2FL) and feed-forward Neural Network with back-propagation (NN-BP) tuning algorithm to improve their approximation capability, flexibility and adaptiveness. IT2FL for STELF is presented which provides additional degrees of freedom for handling more uncertainties for improving prediction a...

As accurate Short Term Load Forecasting (STLF) is very important for improvement of the management performance of the electric industry, various short term loads forecasting methods have been developed. This paper addresses an issue of the optimal design of a neural network based short term load forecaster. A new hybrid evolutionary algorithm combining the Particle Swarm Optimization (PSO) algo...

The load forecasting is a tool of utmost important for the power industry as it can influence areas like power generation and trading, infrastructure development planning etc. Implementation of the load forecasting tool in the distribution utilities has a wider impact up to the power generation level. The load forecasting has been an area in power systems where the human experts are still perfo...

The accuracy of forecasting of electrical load for the electricity industry has a vital significance in the renewal of economic structure as well as various equations including: purchasing and producing energy, load fluctuation, and the development of infrastructures. Its short-term forecasting has a significant role in designing and utilizing power systems and in the distribution systems and h...

Short term load forecasting (STLF), which aims to predict system load over an internal of one day or one week, plays a crucial role in the control and scheduling operations of a power system. Most existing techniques on short term load forecasting try to improve the performance by selecting different prediction models. However, the performance also rely heavily on the quality of training data. ...

________________________________________________ AbstractPaper gives the compressed chronological work of scholars and comparison of classical and modern techniques to short term forecast the electrical load. This paper presents 10 approaches of load forecasting, their brief introduction and literature review. KeywordsLoad Forecasting, Classical Approach, Heuristic Approach, Fuzzy Logic, AI, AR...