Meteorological Benchmark Forecasts for Energy Management Systems

Publikation: Beitrag in Buch oder TagungsbandPosterpräsentation mit Beitrag in TagungsbandBegutachtung

Abstract

Novel energy management and scheduling algorithms that tightly integrate volatile renewable energy sources often depend on external forecasts such as numerical weather predictions. Since the quality of the forecasting inputs may widely affect the system performance, detailed assessments are needed. This work addresses the need for large-scale forecasting datasets by presenting methods to refine and generate artificial benchmarking inputs. A k-NN-based localization approach and a synthetization technique generating artificial PV forecasts for benchmarking purposes are herein developed and thoughtfully assessed. It is shown that the localization approach can successfully push the accuracy of coarse long-term reforecasting datasets into the range of state-of-the-art services. The artificial forecast generation method complements the work by providing highly controllable benchmarks. Hence, new prospects in assessing algorithms under test with respect to their forecast-quality requirements are provided.
OriginalspracheEnglisch
TitelCIRED Conference Proceedings
Seitenumfang5
ISBN (elektronisch)978-1-83953-855-1
DOIs
PublikationsstatusVeröffentlicht - 12 Juni 2023
VeranstaltungCIRED 2023
International Conference
& Exhibition on Electricity Distribution
- City of Rome, La Nuvola, Rome, Italien
Dauer: 12 Juni 202315 Juni 2023
Konferenznummer: 2023
https://www.cired2023.org/#

Konferenz

KonferenzCIRED 2023
International Conference
& Exhibition on Electricity Distribution
KurztitelCIRED
Land/GebietItalien
StadtRome
Zeitraum12/06/2315/06/23
Internetadresse

Research Field

  • Power System Digitalisation

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