Demand Response in Low Voltage Distribution Networks with High PV Penetration

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Abstract

In this paper, application of demand response to accommodate maximum PV power in a low-voltage distribution network is discussed. A centralized control based on model predictive control method is proposed for the computation of optimal demand response on an hourly basis. The proposed method uses PV generation and load forecasts, network topology and market price signals as inputs, limits of network voltages, line power flows, transformer loading and demand response dynamics as constraints to find the required demand response at each time step. The proposed method can be used by the DSOs to purchase the required flexibility from the electricity market through an aggregator. The optimum demand response enables consumption of maximum renewable energy within the network constraints. Simulation studies are conducted using Matlab and DigSilent Power factory software on a Danish low-voltage distribution system. Simulation results show that the proposed method is effective for calculating the optimum demand response. From the test scenarios, it is inferred that absorption of renewable energy from PV increased by 38% applying optimum demand response during the evaluation period in the studied distribution network.
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Details

In this paper, application of demand response to accommodate maximum PV power in a low-voltage distribution network is discussed. A centralized control based on model predictive control method is proposed for the computation of optimal demand response on an hourly basis. The proposed method uses PV generation and load forecasts, network topology and market price signals as inputs, limits of network voltages, line power flows, transformer loading and demand response dynamics as constraints to find the required demand response at each time step. The proposed method can be used by the DSOs to purchase the required flexibility from the electricity market through an aggregator. The optimum demand response enables consumption of maximum renewable energy within the network constraints. Simulation studies are conducted using Matlab and DigSilent Power factory software on a Danish low-voltage distribution system. Simulation results show that the proposed method is effective for calculating the optimum demand response. From the test scenarios, it is inferred that absorption of renewable energy from PV increased by 38% applying optimum demand response during the evaluation period in the studied distribution network.
Original languageEnglish
Title of host publicationProceedings of 2017 52nd International Universities Power Engineering Conference (UPEC)
Number of pages6
PublisherIEEE Press
Publication dateAug 2017
ISBN (Electronic)978-1-5386-2344-2
DOI
StatePublished - Aug 2017
Publication categoryResearch
Peer-reviewedYes
Event2017 52nd International Universities Power Engineering Conference (UPEC) - Heraklion, Greece
Duration: 28 Aug 201731 Aug 2017

Conference

Conference2017 52nd International Universities Power Engineering Conference (UPEC)
LandGreece
ByHeraklion
Periode28/08/201731/08/2017

    Research areas

  • Active distribution network, Demand response, Model Predictive Control (MPC), High PV penetration

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