Voltage Optimization Strategy for Distribution Network Considering Distributed Photovoltaic Active Power Reduction

  • Wenbin Wang
  • Ning Wang
  • Qiao Zhang
  • Jinqing YangEmail author
  • Wei Jin
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 585)


A long-term scale voltage optimization control strategy for distributed photovoltaic actively participated with distribution network considering active reduction is proposed. The residual capacity of PV inverters outside the active power is used to participate in the reactive power optimization for voltage control. If the voltage still exceeds the threshold values, the active power curtailment strategy to PVs is applied to provide more capacity for reactive power optimization and maintain the voltage in range. Considering the uncertainties of photovoltaics and load outputs, the complex affine method is employed to establish the power output model in each time period. Combination of the Ybus power flow calculation and the linear decreasing weight particle swarm optimization is used to solve the proposed optimization model. Case studies on an IEEE 33-bus system are conducted to verify the effectiveness of the proposed optimization strategy.


Voltage and reactive power optimization Distributed photovoltaics Active power curtailment Residual capacity of inverter 



This work is supported by the National Science Foundations of China under grant No. 51607153.


  1. 1.
    Deng N, Ding XQ, Deng CT et al (2018) Multi-objective coordinated optimization of active and reactive power for distribution network integrated with high proportion of photovoltaic generation. Autom Electr Power Syst 42(06):33–39+91Google Scholar
  2. 2.
    Xiao H, Pei W, Deng W et al (2016) Analysis of the impact of distributed generation on distribution network voltage and its optimal control strategy. Trans China Electrotechnical Soc 31(S1):203–213Google Scholar
  3. 3.
    Huang W, Liu SL, Yi YQ et al (2019) Multi-time-scale slack optimal in distribution network based on voltage optimization for point of common coupling of PV. Autom Electr Power Syst 43(03):92–107Google Scholar
  4. 4.
    Zhang HP, Lin SJ, Liu MB (2016) Robust optimal allocation of reactive power compensation in low voltage distribution networks considering uncertainty of photovoltaic generation. Power Syst Technol 40(12):3880–3887Google Scholar
  5. 5.
    Ma W, Wang W, Wu XZ et al (2019) Optimal dispatching strategy of hybrid energy storage system for smoothing power fluctuation of grid-connected photovoltaic. Autom Electr Power Syst 43(03):58–66Google Scholar
  6. 6.
    Calderaro V, Conio G, Caldi V et al (2014) Optimal decentralized voltage control for distribution systems with inverter-based distributed generators. IEEE Trans Power Syst 29(01):230–241CrossRefGoogle Scholar
  7. 7.
    Jia QQ, Qi XM, Ning SY et al (2015) Strategy research of voltage and reactive power operation involved with distributed PV system. Acta Energiae Solaris Sinica 36(12):2954–2959Google Scholar
  8. 8.
    Wang N, Gao P, Jia QQ et al (2017) Research on active and reactive power coordination control strategy of PV grid-connected system for voltage regulation. Adv Technol Electr Eng Energy 36(08):23–29Google Scholar
  9. 9.
    Tonkoski R, Lopes LAC (2011) Impact of active power curtailment on overvoltage prevention and energy production of PV inverters connected to low voltage residential feeders. Renew Energy 36(12):566–3574CrossRefGoogle Scholar
  10. 10.
    Tonkoski R, Lopes LAC, El-Fouly THM (2011) Coordinated active power curtailment of grid connected PV inverters for overvoltage prevention. IEEE Trans Sustain Energy 2(02):139–147CrossRefGoogle Scholar
  11. 11.
    Xing ZB, Wei G, He J et al (2017) A dual stage voltage control method in active distribution network based on graph theory. Trans China Electrotechnical Soc 32(01):40–47Google Scholar
  12. 12.
    Zhang L, Xu YQ, Wang ZP et al (2011) Reactive power optimization for distribution system with distributed generators. Trans China Electrotechnical Soc 26(03):168–174Google Scholar
  13. 13.
    Lv QJ, Wang S, Liu TL (2012) Active/reactive power integrated optimization in distribution networks with distributed generation. Power Syst Prot Control 40(10):71–76+83Google Scholar
  14. 14.
    Huang W, Liu SL, Wang W et al (2018) Optimal reactive power dispatch with long-time scale in distribution network considering uncertainty of photovoltaic. Autom Electr Power Syst 42(05):154–162Google Scholar
  15. 15.
    Fu Y, Liao JB, Li ZK et al (2017) Day-ahead optimal scheduling and operating of active distribution network considering violation risk. Proc CSEE 37(21):6328–6338Google Scholar
  16. 16.
    Ren JY, Gu W, Wang Y et al (2018) Multi-time scale active and reactive power coordinated optimal dispatch in active distribution network based on model predictive control. Proc CSEE 38(05):1397–1407Google Scholar
  17. 17.
    Hu ZC, Wang XF, Gareth T (2010) Stochastic optimal reactive power dispatch: formulation and solution method. Int J Electr Power Energy Syst 32(6):615–621CrossRefGoogle Scholar
  18. 18.
    Ding T, Cui HT, Gu W et al (2012) An uncertainty power flow algorithm based on interval and affine arithmetic. Autom Electr Power Syst 36(13):51–55Google Scholar
  19. 19.
    Huang L (2009) Research and application of parallel Y_bus load flow algorithm. North China Electric Power University, Beijing, pp 25–30Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Wenbin Wang
    • 1
  • Ning Wang
    • 2
  • Qiao Zhang
    • 2
  • Jinqing Yang
    • 2
    Email author
  • Wei Jin
    • 1
  1. 1.Xingtai Power Supply CompanyState Grid Hebei Electric Power Co. LtdXingtaiChina
  2. 2.School of Electrical EngineeringYanshan UniversityQinhuangdaoChina

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