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Article: Improve conservation voltage regulation effects by integrating more distributed renewable generations

TitleImprove conservation voltage regulation effects by integrating more distributed renewable generations
Authors
Keywordsconservation voltage regulation
multivariate Gaussian mixture model
renewable energy source planning
Issue Date1-Sep-2024
PublisherWiley Open Access
Citation
IET Generation, Transmission and Distribution, 2024, v. 18, n. 17, p. 2747-2760 How to Cite?
AbstractDue to intermittent renewable energy and fluctuating load demand, distribution networks with renewable distributed generation (DG) installations are more likely to suffer voltage issues and significant power losses. The performance of conservation voltage regulation (CVR) schemes may be adversely affected by the undesirable voltage profile at specific nodes. This paper aims to reduce power losses in CVR-implemented networks by optimally planning new renewable DGs without changing the existing ones. A scenario-based optimal renewable DG planning model is proposed with a novel scenario formation method. The uncertainties of load demand and renewables are captured jointly and formed into a finite number of scenarios based on a multivariate Gaussian mixture model (MultiGMM). The locations and capacities of different types of new renewable DGs are optimally planned for CVR performance improvements on power loss saving by aggregating the operation status and probabilities of the scenarios using mixed-integer non-linear programming (MINLP). A time-series simulation is formulated for accuracy verification. The results of case studies show that the proposed model can significantly reduce power losses, active load demand, and reactive load demand. The accuracy of the planning results can be guaranteed with fewer scenarios compared to a widely used classical scenario-based planning method.
Persistent Identifierhttp://hdl.handle.net/10722/360789
ISSN
2023 Impact Factor: 2.0
2023 SCImago Journal Rankings: 0.787

 

DC FieldValueLanguage
dc.contributor.authorLi, Ang-
dc.contributor.authorZhong, Jin-
dc.date.accessioned2025-09-14T00:30:06Z-
dc.date.available2025-09-14T00:30:06Z-
dc.date.issued2024-09-01-
dc.identifier.citationIET Generation, Transmission and Distribution, 2024, v. 18, n. 17, p. 2747-2760-
dc.identifier.issn1751-8687-
dc.identifier.urihttp://hdl.handle.net/10722/360789-
dc.description.abstractDue to intermittent renewable energy and fluctuating load demand, distribution networks with renewable distributed generation (DG) installations are more likely to suffer voltage issues and significant power losses. The performance of conservation voltage regulation (CVR) schemes may be adversely affected by the undesirable voltage profile at specific nodes. This paper aims to reduce power losses in CVR-implemented networks by optimally planning new renewable DGs without changing the existing ones. A scenario-based optimal renewable DG planning model is proposed with a novel scenario formation method. The uncertainties of load demand and renewables are captured jointly and formed into a finite number of scenarios based on a multivariate Gaussian mixture model (MultiGMM). The locations and capacities of different types of new renewable DGs are optimally planned for CVR performance improvements on power loss saving by aggregating the operation status and probabilities of the scenarios using mixed-integer non-linear programming (MINLP). A time-series simulation is formulated for accuracy verification. The results of case studies show that the proposed model can significantly reduce power losses, active load demand, and reactive load demand. The accuracy of the planning results can be guaranteed with fewer scenarios compared to a widely used classical scenario-based planning method.-
dc.languageeng-
dc.publisherWiley Open Access-
dc.relation.ispartofIET Generation, Transmission and Distribution-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectconservation voltage regulation-
dc.subjectmultivariate Gaussian mixture model-
dc.subjectrenewable energy source planning-
dc.titleImprove conservation voltage regulation effects by integrating more distributed renewable generations-
dc.typeArticle-
dc.identifier.doi10.1049/gtd2.13195-
dc.identifier.scopuseid_2-s2.0-85201308688-
dc.identifier.volume18-
dc.identifier.issue17-
dc.identifier.spage2747-
dc.identifier.epage2760-
dc.identifier.eissn1751-8695-
dc.identifier.issnl1751-8687-

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