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Sensitivity-Based Model of Low Voltage Distribution Systems with Distributed Energy Resources

Author

Listed:
  • Anna Rita Di Fazio

    (Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, Via di Biasio 43, I-03043 Cassino, Italy
    These authors contributed equally to this work.)

  • Mario Russo

    (Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, Via di Biasio 43, I-03043 Cassino, Italy
    These authors contributed equally to this work.)

  • Sara Valeri

    (Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, Via di Biasio 43, I-03043 Cassino, Italy
    These authors contributed equally to this work.)

  • Michele De Santis

    (Engineering Department, Università Niccolò Cusano, I-00166 Roma, Italy
    These authors contributed equally to this work.)

Abstract

A key issue in Low Voltage(LV) distribution systems is to identify strategies for the optimal management and control in the presence of Distributed Energy Resources (DERs). To reduce the number of variables to be monitored and controlled, virtual levels of aggregation, called Virtual Microgrids (VMs), are introduced and identified by using new models of the distribution system. To this aim, this paper, revisiting and improving the approach outlined in a conference paper, presents a sensitivity-based model of an LV distribution system, supplied by a Medium/Low Voltage (MV/LV) substation and composed by several feeders, which is suitable for the optimal management and control of the grid and for VM definition. The main features of the proposed method are: it evaluates the sensitivity coefficients in a closed form; it provides an overview of the sensitivity of the network to the variations of each DER connected to the grid; and it presents a limited computational burden. A comparison of the proposed method with both the exact load flow solutions and a perturb-and-observe method is discussed in a case study. Finally, the method is used to evaluate the impact of the DERs on the nodal voltages of the network.

Suggested Citation

  • Anna Rita Di Fazio & Mario Russo & Sara Valeri & Michele De Santis, 2016. "Sensitivity-Based Model of Low Voltage Distribution Systems with Distributed Energy Resources," Energies, MDPI, vol. 9(10), pages 1-16, October.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:10:p:801-:d:79818
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    Citations

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    Cited by:

    1. Min-Rong Chen & Huan Wang & Guo-Qiang Zeng & Yu-Xing Dai & Da-Qiang Bi, 2018. "Optimal P-Q Control of Grid-Connected Inverters in a Microgrid Based on Adaptive Population Extremal Optimization," Energies, MDPI, vol. 11(8), pages 1-19, August.
    2. Yunhwan Lee & Hwachang Song, 2019. "A Reactive Power Compensation Strategy for Voltage Stability Challenges in the Korean Power System with Dynamic Loads," Sustainability, MDPI, vol. 11(2), pages 1-19, January.
    3. Giuseppe Fusco & Mario Russo & Michele De Santis, 2021. "Decentralized Voltage Control in Active Distribution Systems: Features and Open Issues," Energies, MDPI, vol. 14(9), pages 1-31, April.
    4. Andrés Felipe Pérez Posada & Juan G. Villegas & Jesús M. López-Lezama, 2017. "A Scatter Search Heuristic for the Optimal Location, Sizing and Contract Pricing of Distributed Generation in Electric Distribution Systems," Energies, MDPI, vol. 10(10), pages 1-16, September.
    5. Chong Cao & Zhouquan Wu & Bo Chen, 2020. "Electric Vehicle–Grid Integration with Voltage Regulation in Radial Distribution Networks," Energies, MDPI, vol. 13(7), pages 1-18, April.
    6. Mu-Gu Jeong & Young-Jin Kim & Seung-Il Moon & Pyeong-Ik Hwang, 2017. "Optimal Voltage Control Using an Equivalent Model of a Low-Voltage Network Accommodating Inverter-Interfaced Distributed Generators," Energies, MDPI, vol. 10(8), pages 1-19, August.
    7. Jiawei Chen & Shuaicheng Hou & Xiang Li, 2018. "Decentralized Circulating Currents Suppression for Paralleled Inverters in Microgrids Using Adaptive Virtual Inductances," Energies, MDPI, vol. 11(7), pages 1-16, July.
    8. Hamed Moazami Goodarzi & Mohammad Hosein Kazemi, 2017. "A Novel Optimal Control Method for Islanded Microgrids Based on Droop Control Using the ICA-GA Algorithm," Energies, MDPI, vol. 10(4), pages 1-17, April.
    9. Anna Rita Di Fazio & Mario Russo & Michele De Santis, 2019. "Zoning Evaluation for Voltage Optimization in Distribution Networks with Distributed Energy Resources," Energies, MDPI, vol. 12(3), pages 1-28, January.
    10. Zhe Zhang & Hang Yang & Xianggen Yin & Jiexiang Han & Yong Wang & Guoyan Chen, 2018. "A Load-Shedding Model Based on Sensitivity Analysis in on-Line Power System Operation Risk Assessment," Energies, MDPI, vol. 11(4), pages 1-17, March.
    11. Hongmei Li & Hantao Cui & Chunjie Li, 2019. "Distribution Network Power Loss Analysis Considering Uncertainties in Distributed Generations," Sustainability, MDPI, vol. 11(5), pages 1-17, March.

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