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Voltage Regulation For Residential Prosumers Using a Set of Scalable Power Storage

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  • Igor Cavalcante Torres

    (Engineering and Agricultural Sciences Campus, Federal University of Alagoas, Rio Largo 57100-000, Brazil
    These authors contributed equally to this work.)

  • Daniel M. Farias

    (Computer Institute, Federal University of Alagoas, Maceió 57072-970, Brazil
    These authors contributed equally to this work.)

  • Andre L. L. Aquino

    (Computer Institute, Federal University of Alagoas, Maceió 57072-970, Brazil)

  • Chigueru Tiba

    (Department of Nuclear Energy, Federal University of Pernambuco, Recife 50740-540, Pernambuco)

Abstract

Among the electrical problems observed from the solar irradiation variability, the electrical energy quality and the energetic dispatch guarantee stand out. The great revolution in batteries technologies has fostered its usage with the installation of photovoltaic system (PVS). This work presents a proposition for voltage regulation for residential prosumers using a set of scalable power batteries in passive mode, operating as a consumer device. The mitigation strategy makes decisions acting directly on the demand, for a storage bank, and the power of the storage element is selected in consequence of the results obtained from the power flow calculation step combined with the prediction of the solar radiation calculated by a recurrent neural network Long Short-Term Memory (LSTM) type. The results from the solar radiation predictions are used as subsidies to estimate, the state of the power grid, solving the power flow and evidencing the values of the electrical voltages 1-min enabling the entry of the storage device. In this stage, the OpenDSS (Open distribution system simulator) software is used, to perform the complete modeling of the power grid where the study will be developed, as well as simulating the effect of the overvoltages mitigation system. The clear sky day stored 9111 Wh/day of electricity to mitigate overvoltages at the supply point; when compared to other days, the clear sky day needed to store less electricity. On days of high variability, the energy stored to regulate overvoltages was 84% more compared to a clear day. In order to maintain a constant state of charge (SoC), it is necessary that the capacity of the battery bank be increased to meet the condition of maximum accumulated energy. Regarding the total loading of the storage system, the days of low variability consumed approximately 12% of the available capacity of the battery, considering the SoC of 70% of the capacity of each power level.

Suggested Citation

  • Igor Cavalcante Torres & Daniel M. Farias & Andre L. L. Aquino & Chigueru Tiba, 2021. "Voltage Regulation For Residential Prosumers Using a Set of Scalable Power Storage," Energies, MDPI, vol. 14(11), pages 1-28, June.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:11:p:3288-:d:568816
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    References listed on IDEAS

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    1. Igor Cavalcante Torres & Gustavo F. Negreiros & Chigueru Tiba, 2019. "Theoretical and Experimental Study to Determine Voltage Violation, Reverse Electric Current and Losses in Prosumers Connected to Low-Voltage Power Grid," Energies, MDPI, vol. 12(23), pages 1-20, November.
    2. Javier Marcos & Iñigo De la Parra & Miguel García & Luis Marroyo, 2014. "Control Strategies to Smooth Short-Term Power Fluctuations in Large Photovoltaic Plants Using Battery Storage Systems," Energies, MDPI, vol. 7(10), pages 1-27, October.
    3. Giorgio Guariso & Giuseppe Nunnari & Matteo Sangiorgio, 2020. "Multi-Step Solar Irradiance Forecasting and Domain Adaptation of Deep Neural Networks," Energies, MDPI, vol. 13(15), pages 1-18, August.
    4. Qiangqiang Xie & Xiangrong Shentu & Xusheng Wu & Yi Ding & Yongzhu Hua & Jiadong Cui, 2019. "Coordinated Voltage Regulation by On-Load Tap Changer Operation and Demand Response Based on Voltage Ranking Search Algorithm," Energies, MDPI, vol. 12(10), pages 1-19, May.
    5. João Martins & Sergiu Spataru & Dezso Sera & Daniel-Ioan Stroe & Abderezak Lashab, 2019. "Comparative Study of Ramp-Rate Control Algorithms for PV with Energy Storage Systems," Energies, MDPI, vol. 12(7), pages 1-15, April.
    6. Mahmud, Nasif & Zahedi, A., 2016. "Review of control strategies for voltage regulation of the smart distribution network with high penetration of renewable distributed generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 582-595.
    7. Resch, Matthias & Bühler, Jochen & Klausen, Mira & Sumper, Andreas, 2017. "Impact of operation strategies of large scale battery systems on distribution grid planning in Germany," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1042-1063.
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    Cited by:

    1. Yih-Der Lee & Wei-Chen Lin & Jheng-Lun Jiang & Jia-Hao Cai & Wei-Tzer Huang & Kai-Chao Yao, 2021. "Optimal Individual Phase Voltage Regulation Strategies in Active Distribution Networks with High PV Penetration Using the Sparrow Search Algorithm," Energies, MDPI, vol. 14(24), pages 1-22, December.
    2. Bartłomiej Mroczek & Paweł Pijarski, 2022. "Machine Learning in Operating of Low Voltage Future Grid," Energies, MDPI, vol. 15(15), pages 1-30, July.

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