In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn
Accurate forecasting tools are essential in the operation of electric power systems, especially in d...
The development of artificial intelligence (AI) based techniques for electricity price forecasting (...
In the electricity market environment, the market clearing price has strong volatility, periodicity ...
In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competiti...
In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competiti...
Abstract—A novel hybrid approach, combining particle swarm optimization and adaptive-network based f...
A novel hybrid approach, combining wavelet transform, particle swarm optimization, and adaptive-netw...
Abstract—A novel hybrid approach, combining wavelet trans-form, particle swarm optimization, and ada...
Abstract. The intermittence of the renewable sources due to its unpredictability increases the insta...
In recent years, there have been notable commitments and obligations by the electricity sector for m...
The uncertainty and variability in electricity market price (EMP) signals and players’ behavior, as ...
AbstractIn this paper an efficient method is proposed for electricity price forecasting. This paper ...
In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasti...
In this paper, a hybrid electricity price forecasting method which is composed of two-stage feature ...
The day-ahead electricity market is closely related to other commodity markets such as the fuel and ...
Accurate forecasting tools are essential in the operation of electric power systems, especially in d...
The development of artificial intelligence (AI) based techniques for electricity price forecasting (...
In the electricity market environment, the market clearing price has strong volatility, periodicity ...
In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competiti...
In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competiti...
Abstract—A novel hybrid approach, combining particle swarm optimization and adaptive-network based f...
A novel hybrid approach, combining wavelet transform, particle swarm optimization, and adaptive-netw...
Abstract—A novel hybrid approach, combining wavelet trans-form, particle swarm optimization, and ada...
Abstract. The intermittence of the renewable sources due to its unpredictability increases the insta...
In recent years, there have been notable commitments and obligations by the electricity sector for m...
The uncertainty and variability in electricity market price (EMP) signals and players’ behavior, as ...
AbstractIn this paper an efficient method is proposed for electricity price forecasting. This paper ...
In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasti...
In this paper, a hybrid electricity price forecasting method which is composed of two-stage feature ...
The day-ahead electricity market is closely related to other commodity markets such as the fuel and ...
Accurate forecasting tools are essential in the operation of electric power systems, especially in d...
The development of artificial intelligence (AI) based techniques for electricity price forecasting (...
In the electricity market environment, the market clearing price has strong volatility, periodicity ...