Short-term Load Forecasting Using Genetic- Fuzzy Algorithm and Neural Network
محل انتشار: سومین کنفرانس ملی و اولین کنفرانس بین المللی پژوهش هایی کاربردی در مهندسی برق، مکانیک و مکاترونیک
سال انتشار: 1394
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 463
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شناسه ملی سند علمی:
ELEMECHCONF03_0197
تاریخ نمایه سازی: 9 مرداد 1395
چکیده مقاله:
Abstract: With the growth of consumption and connected load of power systems with each other the amount of incoming and outgoing data in order to plan and optimize utilization has been Increased. So that those responsible for decisions related to these in order to support operations of power system we must use more science and software such as intelligent networks to predict Intelligent networks and new computational methods to predict the output of the power grids to provide answers. Neural networks as intelligent tools that can be used to predict but cannot be used to predict various data types in any condition, So to better predict combination of systems is used. In order to predict short-term load dispatching in Tehran Regional District we combine genetic - fuzzy algorithms with neural network method. Inputs include important data of Tehran weather conditions classified by the genetic–Fuzzy algorithm. by Using software(MATLAB ) and suggested algorithms and simulations carried out, the results are more accurate forecasts.
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نویسندگان
Hassan abdolrezaei
Electrical engineering Islamic azad university saveh,iran
Mohammad hassan moradi
Electrical engineering Islamic azad university saveh,iran
Mohammad javad rastegar fatemi
Electrical engineering Islamic azad university saveh,iran