Electric Power Load Forecasting using Fuzzy Prediction System
نویسندگان
چکیده
منابع مشابه
Fuzzy Load Forecasting of Electric Power System
In order to efficiently improve the prediction accuracy, two load forecasting model based on fuzzy theory are presented, which are fuzzy clustering model and improved fuzzy regression analysis model .The method of fuzzy clustering is used to divide the area by the similar feature of load increasing. The new division is promising to improve the result of evident degree of clustering index to pow...
متن کاملWind Power and Electric Load Forecasting
As renewable energy increasingly integrates into the electric power system, electric load forecasting and renewable energy power generation forecasting become more important. In this project, ARIMA and NARX are applied to build load forecasting model focusing on improving statistical and computational efficiency without losing accuracy. ARIMA turns out to be better for short term forecasting wh...
متن کاملFuzzy and Neuro-fuzzy Computing Models for Electric Load Forecasting
Two new computing models, namely a fuzzy expert system and a hybrid neural network-fuzzy expert system for time series forecasting of electric load, are presented in this paper. The fuzzy-logic-based expert system utilizes the historical relationship between load and dry-bulb temperature, and predicts electric loads fairly accurately, 1-24 h ahead. In the case of the hybrid neural network-fuzzy...
متن کاملShort term electric load prediction using Fuzzy BP
The privatization of electricity industry in various parts of the world has increased the significance of the load prediction problem and in particular there is a need to understand and predict the demand for power with greater accuracy, even in case of imprecise input data. Prediction of power demand is essential for an efficient operation of any utility company. In this paper, a fuzzy version...
متن کاملBuilding a Fuzzy Expert System for Electric Load Forecasting Using a Hybrid Neural Network
This paper presents the development of a hybrid neural network to model a fuzzy expert system for time series forecasting of electricc load. The hybrid neural network is trained to develop fuzzy logic rules andjind optimal inputloutput membership values of load and weather parameters. A hybrid learning algorithm consisting of unsupervised and supervised learning phases is used for training the ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Transactions of The Korean Institute of Electrical Engineers
سال: 2013
ISSN: 1975-8359
DOI: 10.5370/kiee.2013.62.11.1590