MINIMIZE DISTRIBUTION NETWORK LOSSES USING WIND POWER

Aeishwarya Baviskar*, Kaushik Das, Anca D. Hansen

*Corresponding author for this work

    Research output: Contribution to conferencePaperResearch

    109 Downloads (Pure)

    Abstract

    The increased penetration of weather-dependent distributed generation, such as wind power plants and photovoltaics, in distribution networks, presents new challenges for the distribution system operators to improve their networks’ operation by effectively utilizing the available resources. A higher amount of distributed generation also directly translates to more power losses in the network. In this regard, wind power plant capabilities can prove valuable to avoid network congestion, maintain supply and reduce network losses. This paper aims to minimize losses in distribution networks with a large share of wind power plants by optimizing the reactive power flow through the distribution networks by controlling reactive power set-points of wind power plants using genetic-algorithm based optimization. The study is conducted on a real Danish distribution network, with a large share of controllable wind power plants, under varying wind and load conditions using actual measurements. The results show that the reactive power support from wind power plants can reduce network losses by ≈ 2.5 % (103 MWh) with a 0.25 % uncertainty in the mean loss reduction. However, the uncertainty in loss reduction depends on the loss in the network without using wind power plant capabilities. This work successfully demonstrates that the control capability of wind power plants can support distribution system operators by reducing losses in distribution networks.
    Original languageEnglish
    Publication date2021
    Number of pages5
    Publication statusPublished - 2021
    EventCIRED 2021 Conference - Virtual event
    Duration: 20 Sept 202123 Sept 2021

    Conference

    ConferenceCIRED 2021 Conference
    CityVirtual event
    Period20/09/202123/09/2021

    Keywords

    • Wind power plant control
    • Distribution network
    • Loss minimization
    • Genetic algorithm
    • Reactive power support

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