Electricity price forecasting on the day-ahead market using machine learning
The price of electricity on the European market is very volatile. This is due both to its mode of
production by different sources, each with its own constraints (volume of production …
production by different sources, each with its own constraints (volume of production …
[HTML][HTML] Electricity market integration and impact of renewable energy sources in the Central Western Europe region: Evolution since the implementation of the Flow …
The wholesale electricity markets in Europe are undergoing major changes. The pursuit of a
major integration for the development of the Internal Energy market is the main driver of this …
major integration for the development of the Internal Energy market is the main driver of this …
A Hybrid Model for Multi-Day-Ahead Electricity Price Forecasting considering Price Spikes
This paper proposes a new hybrid model to forecast electricity market prices up to four days
ahead. The components of the proposed model are combined in two dimensions. First, on …
ahead. The components of the proposed model are combined in two dimensions. First, on …
The electricity market in Greece: Current status, identified challenges, and arranged reforms
The approach of an integrated electricity market is widespread across Europe, since such a
market structure has numerous benefits for both the grid and consumers. The current …
market structure has numerous benefits for both the grid and consumers. The current …
Enhancing water access monitoring through map** multi-source usage and disaggregated geographic inequalities with machine learning and surveys
J Geleijnse, M Rutten, D De Villiers, JT Bamwenda… - Scientific Reports, 2023 - nature.com
Monitoring safe water access in develo** countries relies primarily on household health
survey and census data. These surveys are often incomplete: they tend to focus on the …
survey and census data. These surveys are often incomplete: they tend to focus on the …
Forecasting of locational marginal price components with artificial intelligence and sensitivity analysis: A study under tropical weather and renewable power for the …
Electricity price forecasting is fundamental for energy market orientation, providing
information contributing to decision making in the short term. Electricity prices are affected by …
information contributing to decision making in the short term. Electricity prices are affected by …
Day-ahead electricity price forecasting using artificial intelligence-based algorithms
Deregulation and privatization of electricity markets has brought greater attention to
electricity price forecasting (EPF) problem in day-ahead and intraday markets since a …
electricity price forecasting (EPF) problem in day-ahead and intraday markets since a …
Prediction of Water Level in Lakes by RNN-Based Deep Learning Algorithms to Preserve Sustainability in Changing Climate and Relationship to Microcystin
S Ozdemir, S Ozkan Yildirim - Sustainability, 2023 - mdpi.com
In recent years, intensive water use combined with global climate change has increased
fluctuations in freshwater lake levels, hydrological characteristics, water quality, and water …
fluctuations in freshwater lake levels, hydrological characteristics, water quality, and water …
Calibration window selection based on change-point detection for forecasting electricity prices
We employ a recently proposed change-point detection algorithm, the Narrowest-Over-
Threshold (NOT) method, to select subperiods of past observations that are similar to the …
Threshold (NOT) method, to select subperiods of past observations that are similar to the …
Self-supervised Adaptive Learning Algorithm for Multi-Horizon Electricity Price Forecasting
Forecasting accuracy of electricity prices is crucial to the optimal operation of the electricity
market, as improper forecasting can lead to inefficiencies, increased costs, and market …
market, as improper forecasting can lead to inefficiencies, increased costs, and market …