A hybrid dynamic and fuzzy time series model for mid-term power load forecasting

2015 ◽  
Vol 64 ◽  
pp. 1057-1062 ◽  
Author(s):  
Woo-Joo Lee ◽  
Jinkyu Hong
Keyword(s):  
Time Series ◽  
Load Forecasting ◽  
Time Series Model ◽  
Fuzzy Time Series ◽  
Power Load ◽  
Power Load Forecasting

Short-Term Reactive Power Load Forecasting Using Multiple Time-Series Model

2003 ◽  
Vol 36 (20) ◽  
pp. 985-990 ◽  
Author(s):  
Jong-Man Cho ◽  
Jin-Hack Kim ◽  
Woo-Hyun Park ◽  
Yun-ho Lee ◽  
Jin-O Kim
Keyword(s):  
Time Series ◽  
Reactive Power ◽  
Load Forecasting ◽  
Time Series Model ◽  
Multiple Time ◽  
Multiple Time Series ◽  
Short Term ◽  
Power Load ◽  
Power Load Forecasting

scholarly journals Long-Term Load Forecasting Based on a Time-Variant Ratio Multiobjective Optimization Fuzzy Time Series Model

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Xiaojuan Liu ◽  
Jian’an Fang
Keyword(s):  
Time Series ◽  
Multiobjective Optimization ◽  
Optimality Theory ◽  
Load Forecasting ◽  
Time Series Forecasting ◽  
Time Series Model ◽  
Fuzzy Time Series ◽  
Interval Length ◽  
Forecasting Models

Load forecasting problem is a complex nonlinear problem linked with economic and weather factors. Long-term load forecasting provides useful information for maintenance scheduling, adequacy assessment, and limited energy resources for electrical power systems. Fuzzy time series forecasting models can be used for long-term load forecasting. However, the interval length has been chosen arbitrarily in the implementations of known fuzzy time series forecasting models, which has an important impact on the performance of these models. In this paper, a time-variant ratio multiobjective optimization fuzzy time series model (TV-RMOP) is proposed, and its performance is tested on the prediction of enrollment at the University of Alabama. Results clearly promote the forecasting accuracy as compared to the conventional models. A genetic algorithm is used to search for the length of intervals based on the training data while Pareto optimality theory provides the necessary conditions to identify an optimal one. The TV-RMOP model is applied for the long-term load forecasting in Shanghai of China.

About One Approach to Defuzzifikation of Outputs of Fuzzy Time Series Model

2011 ◽  
Vol 3 (9) ◽  
pp. 562-566
Author(s):  
Ramin Rzayev ◽  
◽  
Musa Agamaliyev ◽  
Nijat Askerov
Keyword(s):  
Time Series ◽  
Time Series Model ◽  
Fuzzy Time Series
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