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[HTML][HTML] Electricity price forecasting: A review of the state-of-the-art with a look into the future
A variety of methods and ideas have been tried for electricity price forecasting (EPF) over the
last 15 years, with varying degrees of success. This review article aims to explain the …
last 15 years, with varying degrees of success. This review article aims to explain the …
A moving-average filter based hybrid ARIMA–ANN model for forecasting time series data
A suitable combination of linear and nonlinear models provides a more accurate prediction
model than an individual linear or nonlinear model for forecasting time series data …
model than an individual linear or nonlinear model for forecasting time series data …
A review of the decomposition methodology for extracting and identifying the fluctuation characteristics in electricity demand forecasting
Z Shao, F Chao, SL Yang, KL Zhou - Renewable and Sustainable Energy …, 2017 - Elsevier
Electricity consumption data is regarded as nonlinear, non-stationary series, and is often
made up by a superposition of several distinct frequencies. Thus most of the conventional …
made up by a superposition of several distinct frequencies. Thus most of the conventional …
A novel combination forecasting model for wind power integrating least square support vector machine, deep belief network, singular spectrum analysis and locality …
Y Zhang, J Le, X Liao, F Zheng, Y Li - Energy, 2019 - Elsevier
Accurate wind power prediction can alleviate the negative influence on power system
caused by the integration of wind farms into grid. In this paper, a novel combination model is …
caused by the integration of wind farms into grid. In this paper, a novel combination model is …
Understanding electricity price evolution–day-ahead market competitiveness in Romania
The unexpected pandemic eruption in March 2020, the European efforts to diminish the gas
house emissions, prolonged drought, higher inflation and the war in Ukraine clearly have …
house emissions, prolonged drought, higher inflation and the war in Ukraine clearly have …
Minute-ahead stock price forecasting based on singular spectrum analysis and support vector regression
Time series modeling and forecasting is an essential and hard task in financial engineering
and optimization. Various models have been proposed in the literature and tested on daily …
and optimization. Various models have been proposed in the literature and tested on daily …
Simultaneous day-ahead forecasting of electricity price and load in smart grids
In smart grids, customers are promoted to change their energy consumption patterns by
electricity prices. In fact, in this environment, the electricity price and load consumption are …
electricity prices. In fact, in this environment, the electricity price and load consumption are …
Predicting day-ahead electricity market prices through the integration of macroeconomic factors and machine learning techniques
Several events in the last years changed to some extent the common understanding of the
electricity day-ahead market (DAM). The shape of the electricity price curve has been altered …
electricity day-ahead market (DAM). The shape of the electricity price curve has been altered …
A hybrid model for integrated day‐ahead electricity price and load forecasting in smart grid
Load and price forecasting are two key issues for market participants and system operators
in electricity markets. Most existing works predict load and price separately. However, a …
in electricity markets. Most existing works predict load and price separately. However, a …
Electricity prices forecasting by a hybrid evolutionary-adaptive methodology
With the restructuring of the electricity sector in recent years, and the increased variability
and uncertainty associated with electricity market prices, it has become necessary to …
and uncertainty associated with electricity market prices, it has become necessary to …