{"id":1264,"date":"2024-08-23T10:40:07","date_gmt":"2024-08-23T10:40:07","guid":{"rendered":"https:\/\/www.gecad.isep.ipp.pt\/ERM-competitions\/?page_id=1264"},"modified":"2025-09-08T14:33:05","modified_gmt":"2025-09-08T14:33:05","slug":"2025-energy-forecast","status":"publish","type":"page","link":"https:\/\/www.gecad.isep.ipp.pt\/ERM-competitions\/2025-energy-forecast\/","title":{"rendered":"Call for Competition on Electric Energy Consumption Forecast Adopting Multi-criteria Performance Metrics"},"content":{"rendered":"\n

Organized<\/strong> by Polytechnic of Porto (ISEP)<\/p>\n\n\n\n

Polytechnic of Porto (ISEP): <\/strong> Luis Gomes, Zita Vale, Pedro Faria, Jo\u00e3o Soares<\/p>\n\n\n\n

Winners<\/h2>\n\n\n\n

1st place – Michael Ibrahim<\/strong> (Cairo University)<\/p>\n\n\n\n

2nd place – Wided Hammedi, and David Excoffier<\/strong> (Orange)<\/p>\n\n\n\n

3rd place – Amin Hassanzadehmoghaddam<\/strong> (LUT University)<\/p>\n\n\n\n

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Registration<\/h2>\n\n\n\n

The registration of participants is mandatory<\/strong> and must be made online.<\/p>\n\n\n\n

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Competition Outline <\/h2>\n\n\n\n

Forecasting of electric energy consumption can be a very difficult tasks when handling building-level data. However, an accurate forecast is needed to boost the potential of energy management systems. The need to forecast energy consumption grows as our reliance on renewable energy sources, such as solar and wind power, grows. This means that to meet consumer demand with renewable energy generation, energy management systems must operate based on accurate energy forecasting models for both short and long-term periods. Energy consumption forecasting techniques that can manage a variety of scenarios, including varying prediction timeframes, accessible data, data frequency, and even data quality, have been the subject of intense research. There is no one-size-fits-all approach, where certain situations call for different approaches. The goal of this competition is to compile and evaluate the most recent advances in energy consumption forecasting techniques.<\/p>\n\n\n\n

Guidelines<\/a><\/div>\n\n\n\n
(webinar) Competition presentation<\/a><\/div>\n\n\n\n
(webinar) Dataset presentation<\/a><\/div>\n\n\n\n
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Competition goals<\/h2>\n\n\n\n

Obtain accurate electric energy consumption forecast for a smart building based on historic data regarding overall and area electric energy consumption, weather information, external temperature, rooftop photovoltaic panels generation, other sensors data (e.g. movement, CO2). The competition targets both forecasting methods and data pre-processing methods aiming at providing a good environment for discussion and comparison of results of the different approaches used by the applicants.<\/p>\n\n\n\n

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Submissions<\/h2>\n\n\n\n

Each submission must provide an hourly 24-hour forecast of energy consumption, meaning that each submission is required to have 24 values. In total, the participants must submit results for 5 days.<\/p>\n\n\n\n

The submission will be made by email until 22:59 (GMT) of each competition date. <\/strong>The email must be sent to: log@isep.ipp.pt, zav@isep.ipp.pt, pnf@isep.ipp.pt, and jan@isep.ipp.pt.<\/p>\n\n\n\n

In your submissions, please add the subject as: Application for the <\/em>2025 Competition on Electric Energy Consumption Forecast<\/em><\/p>\n\n\n\n

In each submission, the <\/strong>participants must attach the following:<\/strong><\/p>\n\n\n\n