Data Analytics and Stochastic Simulation Methods for Risk-Controlled Network Planning: Validation Case Study

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dc.contributor.affiliationEDP Distribuição
dc.contributor.affiliationEDP Distribuição
dc.contributor.affiliationEDP Distribuição
dc.contributor.affiliationEDP Distribuição
dc.contributor.affiliationEDP Distribuição
dc.contributor.affiliationAmberTREE
dc.contributor.affiliationAmberTREE
dc.contributor.affiliationAmbertree
dc.contributor.authorÁguas, André
dc.contributor.authorPereira, Vera
dc.contributor.authorRoça, Inês
dc.contributor.authorJorge, Luísa
dc.contributor.authorPrata, Ricardo
dc.contributor.authorMachado, João
dc.contributor.authorCarvalho, Pedro
dc.contributor.authorFerreira, Luís Marcelino
dc.contributor.countryPortugal
dc.contributor.countryPortugal
dc.contributor.countryPortugal
dc.contributor.countryPortugal
dc.contributor.countryPortugal
dc.contributor.countryPortugal
dc.contributor.countryPortugal
dc.contributor.countryPortugal
dc.contributor.detailedauthorÁguas, André, EDP Distribuição, Portugal
dc.contributor.detailedauthorPereira, Vera, EDP Distribuição, Portugal
dc.contributor.detailedauthorRoça, Inês, EDP Distribuição, Portugal
dc.contributor.detailedauthorJorge, Luísa, EDP Distribuição, Portugal
dc.contributor.detailedauthorPrata, Ricardo , EDP Distribuição, Portugal
dc.contributor.detailedauthorMachado, João, AmberTREE, Portugal
dc.contributor.detailedauthorCarvalho, Pedro, AmberTREE, Portugal
dc.contributor.detailedauthorFerreira, Luís Marcelino, Ambertree, Portugal
dc.date.accessioned2019-07-24T12:37:53Z
dc.date.available2019-07-24T12:37:53Z
dc.date.conferencedate3-6 June 2019
dc.date.issued2019-06-03
dc.description.abstractEDPD is developing initiatives taking advantage of the continued technological investments being made in AMI. Themain focusof these initiatives is on how data analytics can be used to enhance the current simulation methods in order to allow a risk-controlled network planning approach.Thus, we have developedspecific data analytics methodologiesto explore the large volume of metering data aiming at clustering customer profiles into typical load/generation profiles.Within each cluster, load has been modelled by a discrete-time non-stationary Markov process that realistically reproduces high resolution daily load volatility and time-dependency. This process was then integrated and used inDPlan, the decision-making support tool used by EDPD, to perform thousands of power-flows and estimate the current and voltage distributions of each branch and node.As this novel approach to network planning is significantly different from the traditional methods and involves a series of steps of data analysis, it is exceedingly important to validate the results of the simulations by comparing them to real data. This paper intends to assess those results, by presenting a comparison between the calculated synthetic profiles and the metered profiles, for a specific case study.An in-depth analysis of load distribution will allow us to validate the developed methodologies to facilitate and improve the performance of probabilistic solutions, assuring to planners that the resulting errors are not significant and so, the solution framework can be applied to a realistic smart grid context and prospect its applicabilityfor real situational awareness.
dc.description.conferencelocationMadrid, Spain
dc.description.conferencenameCIRED 2019
dc.description.openaccessYes
dc.description.peerreviewedYes
dc.description.sessionPlanning of power distribution systems
dc.description.sessionidSession 5
dc.identifier.isbn978-2-9602415-0-1
dc.identifier.issn2032-9644
dc.identifier.urihttps://cired-repository.org/handle/20.500.12455/186
dc.identifier.urihttp://dx.doi.org/10.34890/366
dc.language.isoen
dc.publisherAIM
dc.relation.ispartProc. of the 25th International Conference on Electricity Distribution (CIRED 2019)
dc.relation.ispartofseriesCIRED Conference Proceedings
dc.titleData Analytics and Stochastic Simulation Methods for Risk-Controlled Network Planning: Validation Case Study
dc.title.number891
dc.typeConference Proceedings
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