|
Title
|
A fuzzy inference model for short-term load forecasting
|
|
Type
|
Presentation
|
|
Keywords
|
ندارد
|
|
Abstract
|
This paper is concerned with the short-term load forecasting (STLF) in power system operations. It provides load prediction for generation scheduling and unit commitment decisions, and therefore precise load forecasting plays an important role in reducing the generation cost and the spinning reserve capacity./[1] Forecasting is a significant element in economic system performance and its impact on network power control. Load forecasting with the uses of fuzzy implementation is faster and more accurate than conventional load forecasting methods that deal with huge amount of data and the long time needed to be processed.
|
|
Researchers
|
Hassan Bevrani (Second Researcher), Saleh Ahmadi (First Researcher), Hana Jannati (Third Researcher)
|