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Optimal Scheduling for the Complementary Energy Storage System Operation Based on Smart Metering Data in the DC Distribution System

Author

Listed:
  • Bokyung Ko

    (School of Electrical Engineering, Korea University, Seoul 136-713, Korea)

  • Nugroho Prananto Utomo

    (School of Electrical Engineering, Korea University, Seoul 136-713, Korea)

  • Gilsoo Jang

    (School of Electrical Engineering, Korea University, Seoul 136-713, Korea)

  • Jaehan Kim

    (Korea Electric Power Research Institute (KEPRI), Daejeon 305-760, Korea)

  • Jintae Cho

    (Korea Electric Power Research Institute (KEPRI), Daejeon 305-760, Korea)

Abstract

The increasing penetration of distributed generation (DG) sources in low-voltage grid feeders causes problems concerning voltage regulation. The penetration of DG sources such as photovoltaics (PVs) in the distribution system can significantly impact the power flow and voltage conditions on the customer side. As the DG sources are more commonly connected to low-voltage distribution systems, voltage fluctuations in the distribution system are experienced because of the DG fluctuation and uncertainty. Therefore, the penetration of DGs in distribution systems is often limited by the required operating voltage ranges. By using an energy storage system (ESS), voltage fluctuation can be compensated for, thus satisfying the voltage regulation requirements. This paper presents an ESS scheduling algorithm based on the power injection data obtained from a smart metering system. The proposed ESS scheduling algorithm is designed for use within a direct current (DC) distribution grid, which comprises customers, each with a PV and an ESS system. The purpose of this ESS scheduling algorithm is to optimize the ESS scheduling by considering the complementary operation among all the ESSs.

Suggested Citation

  • Bokyung Ko & Nugroho Prananto Utomo & Gilsoo Jang & Jaehan Kim & Jintae Cho, 2013. "Optimal Scheduling for the Complementary Energy Storage System Operation Based on Smart Metering Data in the DC Distribution System," Energies, MDPI, vol. 6(12), pages 1-17, December.
    • Handle: RePEc:gam:jeners:v:6:y:2013:i:12:p:6569-6585:d:31472
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    References listed on IDEAS

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    1. Wenpeng Yu & Dong Liu & Yuhui Huang, 2013. "Operation Optimization Based on the Power Supply and Storage Capacity of an Active Distribution Network," Energies, MDPI, vol. 6(12), pages 1-16, December.
    2. Depuru, Soma Shekara Sreenadh Reddy & Wang, Lingfeng & Devabhaktuni, Vijay, 2011. "Smart meters for power grid: Challenges, issues, advantages and status," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 2736-2742, August.
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    Cited by:

    1. Luis Hernández-Callejo, 2019. "A Comprehensive Review of Operation and Control, Maintenance and Lifespan Management, Grid Planning and Design, and Metering in Smart Grids," Energies, MDPI, vol. 12(9), pages 1-50, April.
    2. Yongchun Yang & Xiaodan Wang & Jingjing Luo & Jie Duan & Yajing Gao & Hong Li & Xiangning Xiao, 2017. "Multi-Objective Coordinated Planning of Distributed Generation and AC/DC Hybrid Distribution Networks Based on a Multi-Scenario Technique Considering Timing Characteristics," Energies, MDPI, vol. 10(12), pages 1-29, December.
    3. Hong Li & Xiaodan Wang & Jie Duan & Feifan Chen & Yajing Gao, 2018. "Locating Optimization of an Integrated Energy Supply Centre in a Typical New District Based on the Load Density," Energies, MDPI, vol. 11(4), pages 1-22, April.
    4. Sam Weckx & Reinhilde D'hulst & Johan Driesen, 2015. "Locational Pricing to Mitigate Voltage Problems Caused by High PV Penetration," Energies, MDPI, vol. 8(5), pages 1-22, May.

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