The paper contains the results of research on the impact of the number of factors used to build the Day-Ahead Market model at Polish Power Exchange S.A. Five models with a different number of factors influencing the model were tested. To test the quality of models according to the adopted evaluation criteria, i.e., mean square error and the coefficient of determination for the weighted average prices sold in a given hour of the day, the influence of weather factors, socio-economic factors and energy demand were adopted. The results obtained from the analysis show a relatively high correctness of the simplest of the adopted models, which differs slightly from the best model
ABSTRACT - The spot price prediction for the electric energy markets is a widely approached problem,...
The liberalization of electricity markets in Europe has led to a substantial change in the structure...
In European countries, the last decade has been characterized by a deregulation of power production ...
The paper aims at modelling the electricity generator’s expectations about price development in the ...
Nowadays, identification and neural methods are used more and more often in modeling IT forecasting ...
The work contains the results of the Day-Ahead Market modeling research at Polish Power Exchange tak...
The work contains selected results of the neural modelling for the Electric Power Exchange (EPE) for...
Electricity market: Analysis and prediction of volatility Abstract Vladimír Kunc July 30, 2015 The l...
This paper presents novel intraday session models for price forecasts (ISMPF models) for hourly pric...
In recent years, energy prices have become increasingly volatile, making it more challenging to pred...
The challenges of the modern world require transformations in the energy market towards the possible...
Abstract:- This paper is about the use of artificial neural networks on day-ahead electricity prices...
Electricity markets are complex environments with very dynamic characteristics. The large-scale pene...
With the emergence of smart power grid and distributed generation technologies in recent years, ther...
Forecasting electricity prices is one of the most important issues in the competitive environment of...
ABSTRACT - The spot price prediction for the electric energy markets is a widely approached problem,...
The liberalization of electricity markets in Europe has led to a substantial change in the structure...
In European countries, the last decade has been characterized by a deregulation of power production ...
The paper aims at modelling the electricity generator’s expectations about price development in the ...
Nowadays, identification and neural methods are used more and more often in modeling IT forecasting ...
The work contains the results of the Day-Ahead Market modeling research at Polish Power Exchange tak...
The work contains selected results of the neural modelling for the Electric Power Exchange (EPE) for...
Electricity market: Analysis and prediction of volatility Abstract Vladimír Kunc July 30, 2015 The l...
This paper presents novel intraday session models for price forecasts (ISMPF models) for hourly pric...
In recent years, energy prices have become increasingly volatile, making it more challenging to pred...
The challenges of the modern world require transformations in the energy market towards the possible...
Abstract:- This paper is about the use of artificial neural networks on day-ahead electricity prices...
Electricity markets are complex environments with very dynamic characteristics. The large-scale pene...
With the emergence of smart power grid and distributed generation technologies in recent years, ther...
Forecasting electricity prices is one of the most important issues in the competitive environment of...
ABSTRACT - The spot price prediction for the electric energy markets is a widely approached problem,...
The liberalization of electricity markets in Europe has led to a substantial change in the structure...
In European countries, the last decade has been characterized by a deregulation of power production ...