Study on Probability Distribution of Photovoltaic Power Fluctuations at Multi-time Scales

dc.contributor.affiliationEPRI, State Grid Shanghai Municipal Electric Power Company
dc.contributor.affiliationEPRI, State Grid Shanghai Municipal Electric Power Company
dc.contributor.affiliationShanghai university of electric power
dc.contributor.affiliationShanghai university of electric power
dc.contributor.affiliationShanghai university of electric power
dc.contributor.affiliationEPRI, State Grid Shanghai Municipal Electric Power Company
dc.contributor.authorLuo, Ling
dc.contributor.authorfang, chen
dc.contributor.authorYang, Yong
dc.contributor.authorLi, Chunyang
dc.contributor.authorLi, Fen
dc.contributor.authorZhang, Peng
dc.contributor.countryChina
dc.contributor.countryChina
dc.contributor.countryChina
dc.contributor.countryChina
dc.contributor.countryChina
dc.contributor.countryChina
dc.contributor.detailedauthorLuo, Ling, EPRI, State Grid Shanghai Municipal Electric Power Company, China
dc.contributor.detailedauthorfang, chen, EPRI, State Grid Shanghai Municipal Electric Power Company, China
dc.contributor.detailedauthorYang, Yong, Shanghai university of electric power, China
dc.contributor.detailedauthorLi, Chunyang, Shanghai university of electric power, China
dc.contributor.detailedauthorLi, Fen, Shanghai university of electric power, China
dc.contributor.detailedauthorZhang, Peng, EPRI, State Grid Shanghai Municipal Electric Power Company, China
dc.date.accessioned2019-12-19T18:21:05Z
dc.date.available2019-12-19T18:21:05Z
dc.date.conferencedate7 - 8 June 2018
dc.date.issued2018-06-07
dc.description.abstractBy analyzing the probability distribution function (p.d.f) of photovoltaic (PV) power, the influence of randomness and uncertainty of PV power fluctuation on the operation of power system can be effectively reduced. It will be beneficial to improve the PV grid-connected penetration. In this paper, the generalized Gaussian distribution, the finite student t-mixture model and other models are utilized to analyze the power fluctuation characteristics under multiple time scales, based on a large amount of data gathered from a distributed PV station. Firstly, the study shows that generalized Gaussian distribution performs best to describe the probability distribution of PV power variation and the average power variation under 10~15-min time scales while Gaussian mixture model performs best under 30~60-min time scales. Further, a model based on the relationship between the variability of hourly PV energy production and global solar radiation is proposed, which can be used for quantitative analysis of the energy production variability of PV stations.
dc.description.conferencelocationLjubljana, Slovenia
dc.description.conferencenameCIRED 2018 Ljubljana Workshop
dc.description.openaccessYes
dc.description.peerreviewedYes
dc.description.sessionNetwork integration, control concepts and operations
dc.description.sessionid3
dc.identifier.isbn978-2-9602415-1-8
dc.identifier.issn2032-9628
dc.identifier.urihttps://www.cired-repository.org/handle/20.500.12455/1263
dc.identifier.urihttp://dx.doi.org/10.34890/441
dc.language.isoen
dc.publisherAIM
dc.relation.ispartProc. of CIRED 2018 Ljubljana Workshop
dc.relation.ispartofseriesCIRED Workshop Proceedings
dc.titleStudy on Probability Distribution of Photovoltaic Power Fluctuations at Multi-time Scales
dc.title.number0266
dc.typeConference Proceedings
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
CIRED 2018 Ljubljana WS - 0266 - 20862.pdf
Size:
792.86 KB
Format:
Adobe Portable Document Format