Nespoli, Lorenzo and Medici, Vasco and Lopatichki, Kristijan and Sossan, Fabrizio (2019) Hierarchical Demand Forecasting Benchmark for the Distribution Grid. In: PSCC2020. (Submitted)
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Abstract
We present a comparative study of different probabilistic forecasting techniques on the task of predicting the electrical load of secondary substations and cabinets located in a low voltage distribution grid, as well as their aggregated power profile. The methods are evaluated using standard KPIs for deterministic and probabilistic forecasts. We also compare the ability of different hierarchical techniques in improving the bottom level forecasters' performances. Both the raw and cleaned datasets, including meteorological data, are made publicly available to provide a standard benchmark for evaluating forecasting algorithms for demand-side management applications.
Item Type: | Article in conference proceedings or Presentation at a conference (Paper) |
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Subjects: | Engineering > Others in engineering > Engineering not elsewhere classified Computer sciences > Artificial intelligence > Machine learning |
Department/unit: | Dipartimento ambiente costruzioni e design > Istituto sostenibilità applicata all'ambiente costruito |
Depositing User: | Lorenzo Nespoli |
Date Deposited: | 14 Feb 2020 12:36 |
Last Modified: | 14 Feb 2020 12:36 |
URI: | http://repository.supsi.ch/id/eprint/11512 |
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