Energy4cast challenge 2024
Welcome to the Energy4cast Challenge 2023! This competition is designed for data science enthusiasts, PhD students, and junior professionals who are passionate about energy optimization and eager to contribute to sustainable practices. By participating in this challenge, you will have the opportunity to make a meaningful impact on the improvement of the sustainability of energy communities.
As the global shift towards sustainable energy resources continues, the forecasting accuracy of electricity demand becomes increasingly important for utilities and grid operators. Accurate predictions enable better planning for power production and distribution, as well as optimization of pricing and balancing of supply and demand.
Electricity demand forecasting is a complex task that can be impacted by a wide range of factors such as weather, electricity prices, and consumer behaviors. To address this challenge, a variety of methods have been employed, including statistical methods and machine learning algorithms, with an increasing focus on deep learning models as the amount of available data and computational power has grown.
However, the increasing complexity in the energy sector with the integration of distributed energy resources and various technologies introduces new challenges for load forecasting. Furthermore, the specific purpose of the forecast, whether it be for short-term, long-term, or peak load forecasting, also presents unique challenges. Moreover, different sources of electricity load, such as private households, industries, or office buildings, require different supporting data and present additional conditions that further complicate the accuracy of an electricity load forecast.
The main goal of this competition is to develop a machine learning model that can accurately predict electricity consumption of a residential community with electricity consumption data and weather data.
Each residential community comprises multiple houses and distributed energy resources, and the model should:
• Capture the unique characteristics and energy profiles of each community
• Can be transferable across the communities.
Theme one: electricity load forecasting
1. Develop a forecasting model(s) to accurately predict electricity load of the individual residential community all year round.
2. Identify weather dependent electricity load patterns
Theme one: Transferable model
• Develop a forecasting model(s) can be applied to each of the residential communities to accurately predict electricity load all year round.
The datasets consist of various data sources. There are four types of datasets (individual households’ electricity consumption and associated weather forecasting data).
The individual households’ electricity consumption is synthetic data and generated by the energy metaverse platform developed by SDU Center for Energy Informatics. This data has been verified and validated to ensure the representation of the reality.
The detailed description of the datasets will be available soon.
Phase I (Warm-Up Round, 15 January 2024 - 15 March 2024)
Phase II (Validation Round, 15 March – 15 July 2024)
Phase III (Evaluation and Winner Round, 14 July – 20 August 2024)
Details will come soon!
To ensure that the competition is conducted in a fair and ethical manner, and that all participants should hold to a high standard of conduct:
Respect: Participants are expected to treat others with respect, regardless of their background, identity, or affiliation.
Honesty: Participants are expected to be honest and truthful in their submissions, and not to plagiarize or copy the work of others.
Integrity: Participants are expected to maintain the integrity of the competition and not engage in any activity that could compromise the fairness or accuracy of the results.
Confidentiality: Participants are expected to keep the data provided for the competition confidential and not to share it with others.
Legal Compliance: Participants are expected to comply with all applicable laws, regulations, and ethical standards.
Consequences: Violations of the Code of Conduct may result in disqualification or other sanctions, as determined by the competition organizers.