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Optimal operation of distribution networks with high penetration of wind and solar power within a joint active and reactive distribution market environment

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  • Zubo, Rana H.A.
  • Mokryani, Geev
  • Abd-Alhameed, Raed

Abstract

In this paper, a stochastic approach for the operation of active distribution networks within a joint active and reactive distribution market environment is proposed. The method maximizes the social welfare using market based active and reactive optimal power flow (OPF) subject to network constraints with integration of demand response (DR). Scenario-Tree technique is employed to model the uncertainties associated with solar irradiance, wind speed and load demands.

Suggested Citation

  • Zubo, Rana H.A. & Mokryani, Geev & Abd-Alhameed, Raed, 2018. "Optimal operation of distribution networks with high penetration of wind and solar power within a joint active and reactive distribution market environment," Applied Energy, Elsevier, vol. 220(C), pages 713-722.
    • Handle: RePEc:eee:appene:v:220:y:2018:i:c:p:713-722
    DOI: 10.1016/j.apenergy.2018.02.016
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    4. Anaya, Karim L. & Pollitt, Michael G., 2022. "A social cost benefit analysis for the procurement of reactive power: The case of Power Potential," Applied Energy, Elsevier, vol. 312(C).
    5. Anaya, Karim L. & Pollitt, Michael G., 2020. "Reactive power procurement: A review of current trends," Applied Energy, Elsevier, vol. 270(C).
    6. Ahmed T. Hachemi & Fares Sadaoui & Abdelhakim Saim & Mohamed Ebeed & Hossam E. A. Abbou & Salem Arif, 2023. "Optimal Operation of Distribution Networks Considering Renewable Energy Sources Integration and Demand Side Response," Sustainability, MDPI, vol. 15(24), pages 1-32, December.
    7. Hariri, Ali-Mohammad & Hashemi-Dezaki, Hamed & A. Hejazi, Maryam, 2020. "A novel generalized analytical reliability assessment method of smart grids including renewable and non-renewable distributed generations and plug-in hybrid electric vehicles," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    8. Zahid Ullah & Arshad & Hany Hassanin, 2022. "Modeling, Optimization, and Analysis of a Virtual Power Plant Demand Response Mechanism for the Internal Electricity Market Considering the Uncertainty of Renewable Energy Sources," Energies, MDPI, vol. 15(14), pages 1-16, July.
    9. Jay, Devika & Swarup, K.S., 2021. "A comprehensive survey on reactive power ancillary service markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    10. Fabio Massaro & Maria Luisa Di Silvestre & Marco Ferraro & Francesco Montana & Eleonora Riva Sanseverino & Salvatore Ruffino, 2024. "Energy Hub Model for the Massive Adoption of Hydrogen in Power Systems," Energies, MDPI, vol. 17(17), pages 1-31, September.
    11. Karim Anaya & Michael Pollitt, 2021. "An evaluation of a local reactive power market: the case of Power Potential," Working Papers EPRG2124, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    12. Xu, Jiuping & Wang, Fengjuan & Lv, Chengwei & Huang, Qian & Xie, Heping, 2018. "Economic-environmental equilibrium based optimal scheduling strategy towards wind-solar-thermal power generation system under limited resources," Applied Energy, Elsevier, vol. 231(C), pages 355-371.
    13. Salil Madhav Dubey & Hari Mohan Dubey & Manjaree Pandit & Surender Reddy Salkuti, 2021. "Multiobjective Scheduling of Hybrid Renewable Energy System Using Equilibrium Optimization," Energies, MDPI, vol. 14(19), pages 1-20, October.
    14. Noorollahi, Younes & Golshanfard, Aminabbas & Hashemi-Dezaki, Hamed, 2022. "A scenario-based approach for optimal operation of energy hub under different schemes and structures," Energy, Elsevier, vol. 251(C).
    15. Zhang, Jingrui & Li, Zhuoyun & Wang, Beibei, 2021. "Within-day rolling optimal scheduling problem for active distribution networks by multi-objective evolutionary algorithm based on decomposition integrating with thought of simulated annealing," Energy, Elsevier, vol. 223(C).

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