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Abstract
The energy crisis in 2022 resulted in heightened electricity price awareness among customers. Moreover, increased loading of the distribution grid and changes in the tariff structure required that Distribution System Operators make more precise forecasts for the consumption. For this purpose, a consumption model based on regression was developed, which modeled the consumption with a cyclical base load and a weather dependent component. During the energy crisis, the model detected changes in the consumption, which revealed a new price dependency and resulted in the development of a revised model. In the results, it is shown how the model is used to infer the aggregated consumption of 250,000 customers and that it can explain the variations in consumption before the crisis, while a growing model error was observed subsequently. When considering price sensitive consumption in a revised model, the results show that consumption variations can again be explained. The findings show that with the ongoing electrification, which introduces more flexible consumers, and digitalization, which enables consumers to utilize flexibility, forecasting consumption becomes more complex and requires development of more advanced methods.
Original language | English |
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Title of host publication | Proceedings of Edit 2025 IEEE PES Power Tech Conference |
Number of pages | 6 |
Publisher | IEEE |
Publication status | Accepted/In press - 2025 |
Event | 2025 IEEE PES Power Tech Conference - Kiel, Germany Duration: 29 Jun 2025 → 3 Jul 2025 |
Conference
Conference | 2025 IEEE PES Power Tech Conference |
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Country/Territory | Germany |
City | Kiel |
Period | 29/06/2025 → 03/07/2025 |
Keywords
- Distribution grid
- Electric demand forecasting
- Demand response
- Elasticity
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Dive into the research topics of 'Energy Crisis in 2022: When consumers discovered their flexibility and the consequences for modeling consumption'. Together they form a unique fingerprint.Projects
- 1 Active
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Data driven investments in electrical infrastructure
Bak, B. S. (PhD Student), Bindner, H. W. (Main Supervisor), Weckesser, T. (Supervisor), Langvad, J. P. (Supervisor) & Eriksen, M. L. (Supervisor)
01/05/2024 → 30/04/2027
Project: PhD