Event under the auspices of the Ministry of Economy of Slovak Republic

Medium-term Forecast of Monthly Supply of Electricity and Maximum-demand-day Power Using Adaptive Neuro-Fuzzy Inference System

Janusz Sowiński
Faculty of Electric Engineering Czestochowa University of T


     Last modified: 2017-06-16

Abstract
The statistical data used in the research were prepared by Agency of Energy Market, Inc. (ARE SA). The data constitute a database on the monthly balances of electricity and maximum-demand-day power in each month of the year in the period 2004-2015. Database offers a possibility of analysing monthly consumption of electrical energy, at the same time being able to obtain a yearly consumption. Modern forecasting methods, such as artificial neural networks, evolutionary algorithms and fuzzy logic require a large number of sets for the process of learning and then for verifying the model obtained. The presented in the paper method can yield forecasts at monthly intervals, with the forecasting process using adaptive neuro-fuzzy inference system (ANFIS). Some results of medium-term forecast of electricity supply and power demand have been presented.

 

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