A fuzzy approach for Khorasan Razavi short-term load forecasting
Publish place: 24nd International Power System Conference
Publish Year: 1388
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
PSC24_031
تاریخ نمایه سازی: 28 اسفند 1388
Abstract:
This paper is concerned with the short-term load forecasting (STLF) in power system operations. It provides load prediction for generation scheduling, unit commitment decisions and security assessment. Precise load forecasting plays an important role in reducing the generation cost and spinning reserve capacity. The inaccuracy in the forecast means that load matching is not optimized and consequently the generation and transmission systems are not being operated in an efficient manner. In the present study, a proposed methodology has been introduced to decrease the forecasted error and the processing time by using fuzzy logic controller on an hourly base. It predicts the effect of temperature and historical data on load forecasting in terms of fuzzy sets during the generation process. Case studies have been carried out for the Khorasan Razavi consumption. The forecasted values obtained by fuzzy method were compared with the conventionally forecasted ones. The simulation results show that the STLF of the fuzzy implementation have more accuracy and better outcomes than conventional approach.
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Authors
N Fakhreshamloo
East power transmission and communication engineering co. (MOHAM Group) Shahrood university of technology
M Kaheni
Shahrood university of technology Noyan Behineh energy service co
M Haddad Zarif
Shahrood university of technology
L Ghazizadeh
Noyan Behineh energy service co.
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