Publications related to Forecasting price spikes in European day-ahead electricity markets using decision trees

Related publications (18)

Dataset for the article "Frequency regulation with storage: On losses and profits"

Daniel Kuhn, François Richard Vuille, Dirk Lauinger

This dataset complements the article "Frequency regulation with storage: On losses and profits" by Dirk Lauinger, François Vuille, and Daniel Kuhn, available at https://arxiv.org/abs/2306.02987. The dataset contains the following files: 1.

Zenodo2023

Enabling inter-area reserve exchange through stable benefit allocation mechanisms *

Maryam Kamgarpour

The establishment of a single European day-ahead market has accomplished the integration of the regional day-ahead markets. However, reserve provision and activation remain an exclusive responsibility of regional operators. This limited spatial coordinatio ...

PERGAMON-ELSEVIER SCIENCE LTD2022

Advanced Frameworks to Aggregate and Unlock the Power Flexibility of Distributed Energy Resources Located in Active Distribution Networks

Mohsen Kalantar Neyestanaki

Environmental concerns are leading to a fast transition in electric power systems towards replacing fossil fuel and nuclear generation with renewable generation. This transition has two significant implications for electric power systems: 1-The capacity o ...

EPFL2022

Predicting involuntary hospitalization in psychiatry: A machine learning investigation

Mehdi Gholam

Background Coercion in psychiatry is a controversial issue. Identifying its predictors and their interaction using traditional statistical methods is difficult, given the large number of variables involved. The purpose of this study was to use machine-lear ...

CAMBRIDGE UNIV PRESS2021

Optimal path to a high share of distributed PV in low-voltage distribution grids

Lionel Benjamin Bloch

To limit global warming, the energy transition from fossil fuels to renewables is one of the main challenges of this century. This transition will help decrease our CO2 emissions, create jobs, contribute to a broader revenues distribution, improve energy s ...

EPFL2020

Wasserstein Distributionally Robust Learning

Soroosh Shafieezadeh Abadeh

Many decision problems in science, engineering, and economics are affected by uncertainty, which is typically modeled by a random variable governed by an unknown probability distribution. For many practical applications, the probability distribution is onl ...

EPFL2020

Industrial flexibility as demand-side response for electrical grid stability

François Maréchal, Ivan Daniel Kantor, Alessio Santecchia

Electricity markets are currently experiencing a period of rapid change. The intermittent nature of renewable energy is disrupting the conventional methods used in operational planning of the electrical grid, causing a shift from a day-ahead forecast polic ...

ECOS 2020 Local Organizing Committee2020

Aspects of the energy transition and their effects on power systems

Laurent Vincent Pagnier

Most European countries are committed to an energy transition which consists in the substitution of conventional CO2 emitting energy sources by new renewable energy sources (RES), in particular wind and solar power. As opposed to conventional energy source ...

EPFL2019

Economic Advantages of Office Buildings Providing Ancillary Services with Intraday Participation

Colin Neil Jones, Ioannis Lymperopoulos, Faran Ahmed Qureshi, Ali Ahmadi Khatir

Controlling the consumption profile of office buildings can be used to provide balancing services to the power grid at a financial benefit without violating its thermal comfort constraints. The economic advantage of such a service is a reduction in the tot ...

2018

On the potential of ruled-based machine learning for disruption prediction on JET

Olivier Sauter, Martinus Adela Maria Gijs, Jonathan Graves, Ambrogio Fasoli, Stefano Coda, Basil Duval, Henri Weisen, Richard Pitts, Yves Martin, Javier García Hernández, Duccio Testa, Miguel Fernández Ruiz, Nicola Vianello, Robin Humphry-Baker, Sun Hee Kim, Federico Nespoli, Patrick Blanchard, Alessandro Pau, David Pfefferlé, Davide Galassi, Jonathan Marc Philippe Faustin, Cristian Sommariva, Hamish William Patten, Samuel Lanthaler, Jan Horacek, Yann Camenen, Bruno Emanuel Ferreira De Sousa Correia, José Pedro Rebelo Ferreira Marques, Mikhail Maslov, Marco Wischmeier, Dalziel Joseph Wilson, Liang Yao, Daniel Scott Alessi, Arnout Lodewijk M Beckers, Ana Francisca Leal Silva Soares, Jonnathan Cesar Hidalgo Acosta, Antonio José Pereira de Figueiredo, Partha Dutta, Pierre-Thomas Paul Brun, Pedro Camilo de Oliveira e Silva, Alberto Hernando de Castro, Julio Rodriguez, Vlad Trifa, Li Shuai, Rebecca Hill

In the last years, it has become apparent that detecting disruptions with sufficient anticipation time is an essential but not exclusive task of predictors. It is also important that the prediction is accompanied by appropriate qualifications of its reliab ...

2018

An Econometric Model of the Regulating Power Price for Interconnected Power Systems: the case of the Nord Pool Market

Mario Paolone, Fabrizio Sossan, Mokhtar Bozorg

Transmission System Operators (TSOs) deploy frequency control reserves and regulating power to maintain the load-generation balance in real-time operation of power systems. In the Nordic countries, the TSOs buy regulating power from the Nord Pool regulatin ...

IEEE2018

Provision of Ancillary Services utilizing a Network of Fast-Charging Stations for Electrical Buses

Colin Neil Jones, Ioannis Lymperopoulos, Faran Ahmed Qureshi, Altug Bitlislioglu

We demonstrate how charging infrastructure for electrical vehicles can be utilized for the provision of Ancillary Services to the Power Grid. Fast- charging stations that supply energy to vehicles at high power rates in- corporate energy storage to prevent ...

2018

Distributed Time Series Analytics

Tian Guo

In recent years time series data has become ubiquitous thanks to affordable sensors and advances in embedded technology. Large amount of time-series data are continuously produced in a wide spectrum of applications, such as sensor networks, medical monitor ...

EPFL2017

Is Being Flexible Advantageous for Demands?

Sidi-Rachid Cherkaoui, Farzaneh Abbaspourtorbati

This paper analyzes the impacts of flexible demands on day-ahead market outcomes in a system with significant wind power production. We use a two-stage stochastic market-clearing model, where the first stage represents the day-ahead market and the second s ...

IEEE Institute of Electrical and Electronics Engineers2017

Efficient Distributed Decision Trees for Robust Regression

Karl Aberer, Jean Paul Calbimonte Perez, Tian Guo

The availability of massive volumes of data and recent advances in data collection and processing platforms have motivated the development of distributed machine learning algorithms. In numerous real-world applications large datasets are inevitably noisy a ...

2016

Coupled energy economic model framework for analyzing Swiss electricity markets in changing policy environments

Sophie Maire

Energy policy needs to rely on the proper understanding of the interactions between policy instruments, consumer preferences, investment behavior, market structure, electricity supply, and the wider policy environment. This asks for appropriate modeling to ...

EPFL2016

Forecasting Uncertainty in Electricity Demand

Tri Kurniawan Wijaya

Generalized Additive Models (GAM) are a widely popular class of regression models to forecast electricity demand, due to their high accuracy, flexibility and interpretability. However, the residuals of the fitted GAM are typically heteroscedastic and lepto ...

2015

Providing ancillary service with commercial buildings: the Swiss perspective

Colin Neil Jones, Ioannis Lymperopoulos, Faran Ahmed Qureshi, Ali Ahmadi Khatir, Xuan Truong Nghiem

Ancillary services constitute the cornerstone of the power grid. They allow for an efficient system operation, provide resilience to uncertainties and establish safeguards against unprecedented events. Their importance is growing due to the rise of grid de ...

2015