Analysis of voltage profile to determine energy demand using Monte Carlo algorithms and Markov Chains (MCMC)

Edwin M. García, Alexander Águila, Idi Isaac, Jorge W. González, Gabriel López

Research output: Contribution to conferencePaper

Abstract

© 2016 IEEE. At present, energy distribution companies seek to improve service and implement alternatives to determine the capability of distribution system devices that allow to cover electric demand. This paper proposes a stochastic analysis to manage the demand response energy, depending on the voltage curve profiles established by historical measurements. The proposal is based on the stochastic prediction of energetic demand using Monte Carlo algorithms with Markov Chains (MCMC), from the analysis of the voltage profile as a deterministic variable. The analysis is associated with the prediction of the maximum power required to satisfy the peak demand period in distribution systems with predominance of residential load, also seeking the planning of the networks to increase efficiency, quality and reliability of power supply in peak hours, in order to reduce the contingencies in the operation of distribution networks in periods of peak demand, especially in systems where the residential load is predominant, which has been taking considerable growth, due to the insertion of electric cookers.
Translated title of the contributionAnálisis del perfil de tensión para determinar la demanda de energía utilizando los algoritmos de Monte Carlo y las cadenas de Markov (MCMC)
Original languageEnglish (US)
Pages1-6
Number of pages6
DOIs
StatePublished - 2 Jul 2016
EventProceedings - 2016 51st International Universities Power Engineering Conference, UPEC 2016 - Coimbra, Portugal
Duration: 6 Sep 20169 Sep 2016

Conference

ConferenceProceedings - 2016 51st International Universities Power Engineering Conference, UPEC 2016
Abbreviated titleUPEC 2016
CountryPortugal
CityCoimbra
Period6/09/169/09/16

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