Meteorological Benchmark Forecasts for Energy Management Systems

    Research output: Chapter in Book or Conference ProceedingsConference Proceedings with Poster Presentationpeer-review


    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.
    Original languageEnglish
    Title of host publicationCIRED Conference Proceedings
    Number of pages5
    ISBN (Electronic)978-1-83953-855-1
    Publication statusPublished - 12 Jun 2023
    Event27th International Conference on Electricity Distribution (CIRED) - Italy, Rome, Italy
    Duration: 12 Jun 202315 Jun 2023

    Publication series

    Name27th International Conference on Electricity Distribution (CIRED 2023)


    Exhibition27th International Conference on Electricity Distribution (CIRED)

    Research Field

    • Power System Digitalisation


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