Reactive power optimization for power distribution networks using mixed-integer Second-order cone programming
The integration of a large number of Distributed Resources (DR) into the power distribution network presents significant challenges to the system’s reactive power and voltage control. This paper comprehensively considers the impacts of network losses, curtailment of renewable energy, and user electr...
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| Vydáno v: | Journal of physics. Conference series Ročník 2803; číslo 1; s. 12012 - 12020 |
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01.07.2024
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| ISSN: | 1742-6588, 1742-6596 |
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| Abstract | The integration of a large number of Distributed Resources (DR) into the power distribution network presents significant challenges to the system’s reactive power and voltage control. This paper comprehensively considers the impacts of network losses, curtailment of renewable energy, and user electricity consumption experiences, and establishes a reactive power optimization model for distribution networks with multiple types of distributed resources. Initially, complex relationships among power flow variables are approximated by linear expressions, transforming the power flow model into a Second-order Cone Programming (SOCP) formulation. Subsequently, quadratic nonlinear terms in the constraints are linearized through the use of auxiliary variable methods. Ultimately, the effectiveness of the proposed model is verified on the IEEE BUS-33 system, with an analysis conducted on the influence of distributed resource capacity, demand response weighting coefficients, and demand response levels on system operation. The study concludes that before the absorption capacity limit of the system, an increase in distributed resource capacity not only reduces system losses but also enhances the user’s electricity consumption experience. However, beyond this absorption capacity limit, further increases in distributed resource capacity not only lead to increased system losses but also result in renewable energy curtailment, thereby causing resource waste. |
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| AbstractList | The integration of a large number of Distributed Resources (DR) into the power distribution network presents significant challenges to the system’s reactive power and voltage control. This paper comprehensively considers the impacts of network losses, curtailment of renewable energy, and user electricity consumption experiences, and establishes a reactive power optimization model for distribution networks with multiple types of distributed resources. Initially, complex relationships among power flow variables are approximated by linear expressions, transforming the power flow model into a Second-order Cone Programming (SOCP) formulation. Subsequently, quadratic nonlinear terms in the constraints are linearized through the use of auxiliary variable methods. Ultimately, the effectiveness of the proposed model is verified on the IEEE BUS-33 system, with an analysis conducted on the influence of distributed resource capacity, demand response weighting coefficients, and demand response levels on system operation. The study concludes that before the absorption capacity limit of the system, an increase in distributed resource capacity not only reduces system losses but also enhances the user’s electricity consumption experience. However, beyond this absorption capacity limit, further increases in distributed resource capacity not only lead to increased system losses but also result in renewable energy curtailment, thereby causing resource waste. |
| Author | Gao, Shihong Xiang, Xiaojing |
| Author_xml | – sequence: 1 givenname: Xiaojing surname: Xiang fullname: Xiang, Xiaojing organization: State Grid Hubei Electric Power Company Lifeng Power Supply Company, Laifeng, Hubei, 445700, China – sequence: 2 givenname: Shihong surname: Gao fullname: Gao, Shihong organization: Hubei Minzu University , College of Intelligent Systems Science and Engineering, Enshi, Hubei, 445000, China |
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| Cites_doi | 10.27241/d.cnki.gnjgu.2021.000672 10.13335/j.1000-3673.pst.2022.1328 10.14044/j.1674-1757.pcrpc.2023.06.004 10.1109/CICED.2014.6991759 10.1109/TPWRS.2013.2255317 10.27441/d.cnki.gyzdu.2020.002484 10.19768/j.cnki.dgjs.2023.05.018 10.16081/j.epae.202311027 10.1109/PESGM.2014.6939786 10.19595/j.cnki.1000-6753.tces.231652 10.13334/j.0258-8013.pcsee.2014.16.007 10.1109/TPWRS.2011.2180406 10.1109/TPWRS.2010.2051168 10.27461/d.cnki.gzjdx.2022.002122 |
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| SubjectTerms | Absorption Complex variables Demand analysis Electric power demand Electric power distribution Electricity consumption Energy distribution Energy management Mixed integer Optimization models Power flow Reactive power Renewable energy Renewable resources |
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| Title | Reactive power optimization for power distribution networks using mixed-integer Second-order cone programming |
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