RT Conference Proceedings
T1 Optimising Load Flexibility for the Day Ahead in Distribution Networks with Photovoltaics
A1 Velasco Rodríguez, José Ángel
A1 Rigoni, Valenrin
A1 Soroudi, Alireza
A1 Keane, Andrew
A1 Amarís Duarte, Hortensia Elena
AB In this paper a methodology is proposed to calculate the load demand flexibility that could be activated within the next 24-hours for solving the technical impacts of contingencies that may come up in an unbalanced low voltage distribution networks with high penetration of intermittent DG sources. The methodology is formulated within a Demand Response program environment via load shifting as flexibility enabler mechanism. To achieve that, a non-linear optimisation problem is formulated based on an unbalanced optimal power flow, which allows the determination of the load flexibility that each Demand Response customer could provide at the request of the Distribution System Operator. The demand as well as weather conditions are forecasted for the day ahead. The optimisation problem is solved in a sequence fashion, within a daily framework, splitting the whole problem in optimisation blocks. In each block, the flexible load demand is obtained and the load demand forecasting its updated for the upcoming blocks based on the changes in the scheduled load demand. The methodology is applied to a real distribution network with the load data received from the smart metering infrastructure. The results obtained show the strength of the methodology in solving the technical problems of the network under high unbalanced operation.
PB IEEE
SN 978-1-5386-4722-6
YR 2019
FD 2019-08-26
LK https://hdl.handle.net/10016/29214
UL https://hdl.handle.net/10016/29214
LA eng
NO This paper has been presented at: 2019 IEEE Milan PowerTech
NO The work done by Valentin Rigoni and Alireza Soroudi is supported by a research grant from Science Foundation Ireland (SFI) under the SFI Strategic Partnership Programme Grant No. SF/15/SPP/E3125. The opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Science Foundation Ireland. Jose Angel Velasco and Hortensia Amaris are supported by the Spanish Ministry of Economy and Competitiveness through the National Program for Research under the project OSIRIS (RTC-2014-1556-3).
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