Abstract—A novel hybrid approach, combining particle swarm optimization and adaptive-network based fuzzy inference system, is proposed in this paper for short-term electricity prices prediction in a competitive market. Results from a case study based on the electricity market of mainland Spain are presented. Finally, conclusions are duly drawn. Index Terms—Electricity market, fuzzy logic, neural networks, price forecasting, swarm optimization
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 (...
The uncertainty and variability in electricity market price (EMP) signals and players’ behavior, as ...
In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competiti...
Abstract—A novel hybrid approach, combining wavelet trans-form, particle swarm optimization, and ada...
In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competiti...
A novel hybrid approach, combining wavelet transform, particle swarm optimization, and adaptive-netw...
Abstract. The intermittence of the renewable sources due to its unpredictability increases the insta...
In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasti...
AbstractIn this paper an efficient method is proposed for electricity price forecasting. This paper ...
The day-ahead electricity market is closely related to other commodity markets such as the fuel and ...
In recent years, there have been notable commitments and obligations by the electricity sector for m...
Forecasting electricity prices is today an essential tool in the day-ahead competitive market. Predi...
Electricity price forecasting is considered as an important tool for energy-related utilities and po...
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 (...
The uncertainty and variability in electricity market price (EMP) signals and players’ behavior, as ...
In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competiti...
Abstract—A novel hybrid approach, combining wavelet trans-form, particle swarm optimization, and ada...
In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competiti...
A novel hybrid approach, combining wavelet transform, particle swarm optimization, and adaptive-netw...
Abstract. The intermittence of the renewable sources due to its unpredictability increases the insta...
In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasti...
AbstractIn this paper an efficient method is proposed for electricity price forecasting. This paper ...
The day-ahead electricity market is closely related to other commodity markets such as the fuel and ...
In recent years, there have been notable commitments and obligations by the electricity sector for m...
Forecasting electricity prices is today an essential tool in the day-ahead competitive market. Predi...
Electricity price forecasting is considered as an important tool for energy-related utilities and po...
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 (...
The uncertainty and variability in electricity market price (EMP) signals and players’ behavior, as ...