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

Kód výsledku v 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>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2001

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

7th International Conference on Soft Computing.

ISBN

80-214-1894-X

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

282-287

Název nakladatele

VUT FSI

Místo vydání

Brno

Místo konání akce

Brno

Datum konání akce

6. 6. 2001

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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