Implementation of Hybrid-Fuzzy Neural Network Approach for Short Term Hourly and Peak Load Forecasting Using Weather Parameters.

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F01%3APU21090" target="_blank" >RIV/00216305:26210/01:PU21090 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Implementation of Hybrid-Fuzzy Neural Network Approach for Short Term Hourly and Peak Load Forecasting Using Weather Parameters.
Original language description
This paper presents the development and practical implementation of a hybrid fuzzy-neural network (FNN) technique, which combines neural network modeling, and techniques from fuzzy logic and fuzzy set theory for short-term hourly and peak load forecasting for the Czech Power Company (ČEZ), Czech Republic. The load has two distinct patterns: weekday and weekend-day patterns. The weekend-day pattern include Saturday, Sunday, and special days/holidays loads. Inputs to the FNN are past loads and past weatheer parameters i.e., temperature, humidity, wind-speed, and wind-chill and the output of the FNN is the load forecast for a given day. Simulation results are presented to illustrate the performance and applicability of this hybrid approach. This approachavoids complex mathematical calculations and training on many years of data, and is very simple to implement on a personal computer.
Czech name
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Czech description
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Publication year
2001
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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