The application of the fuzzy rule-based Bayesian algorithm to determine which residential appliances can be considered for the demand response program

• Autorzy: Kapler Piotr

Identyfikatory

DOI

10.24425/bpasts.2023.146106

• Języki publikacji: EN

Abstrakty

EN

This paper proposes the usage of the fuzzy rule-based Bayesian algorithm to determine which residential appliances can be considered for the Demand Response program. In contrast with other related studies, this research recognizes both randomness and fuzziness in appliance usage. Moreover, the input data for usage prediction consists of nodal price values (which represent the actual power system conditions), appliance operation time, and time of day. The case study of residential power consumer behavior modeling was implemented to show the functionality of the proposed methodology. The results of applying the suggested algorithm are presented as colored 3D control surfaces. In addition, the performance of the model was verified using R squared coefficient and root mean square error. The conducted studies show that the proposed approach can be used to predict when the selected appliances can be used under specific circumstances. Research of this type may be useful for evaluation of the demand response programs and support residential load forecasting.

Słowa kluczowe

EN

demand response; residential power consumers; uncertainty; fuzzy rule-based Bayesian

PL

reagowanie na popyt; niepewność; odbiorcy energii lokalni; algorytmy bayesowskie

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2023
• Tom: Vol. 71, nr 4
• Strony: art. no. e146106
• Opis fizyczny: Bibliogr. 37 poz., rys., tab.

Twórcy

autor

Kapler Piotr

• Warsaw University of Technology, Faculty of Electrical Engineering, Electrical Power Engineering Institute, Koszykowa 75, 00-662 Warsaw, Poland

• https://orcid.org/0000-0001-7592-2796

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).