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Local reactive power dispatch optimisation minimising global objectives

Author

Listed:
  • Gandhi, Oktoviano
  • Zhang, Wenjie
  • Rodríguez-Gallegos, Carlos D.
  • Verbois, Hadrien
  • Sun, Hongbin
  • Reindl, Thomas
  • Srinivasan, Dipti

Abstract

The number of distributed energy resources (DERs) deployed in distribution systems has been rapidly increasing in recent years. Consequently, many researchers have proposed to utilise the DERs for local reactive power support. Yet, the expansion of infrastructure necessary to allow communication among the DERs, and with a centralised controller, has not been as fast. This necessitates an independent local control method that is able to fulfil the objectives of a centralised controller. Therefore, this work proposes a data-driven local optimisation of global objectives (LOGO) algorithm to control the reactive power dispatch from DERs in distribution systems. The proposed method has been validated across different test systems with real topology, irradiance and load data, for steady-state undervoltage and overvoltage scenarios. The results have shown that LOGO performs almost as well as centralised optimisation without any communication and without any information regarding the grid topology. LOGO is able to satisfy the voltage constraints using only locally available information even when other algorithms fail to do so. Compared with distributed and other local reactive power controls, LOGO is much more stable and yields significantly better results. Moreover, LOGO’s superiority over other control methods increases with system size and complexity. Hence, this work provides a viable alternative for real-life dispatch optimisation and opens up new possibilities to optimise global variables without any communication. Lastly, this paper also highlights the importance of accurate solar forecasting and validation of reactive power control.

Suggested Citation

  • Gandhi, Oktoviano & Zhang, Wenjie & Rodríguez-Gallegos, Carlos D. & Verbois, Hadrien & Sun, Hongbin & Reindl, Thomas & Srinivasan, Dipti, 2020. "Local reactive power dispatch optimisation minimising global objectives," Applied Energy, Elsevier, vol. 262(C).
    • Handle: RePEc:eee:appene:v:262:y:2020:i:c:s0306261920300416
    DOI: 10.1016/j.apenergy.2020.114529
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    References listed on IDEAS

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    1. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2016. "Optimization framework for distributed energy systems with integrated electrical grid constraints," Applied Energy, Elsevier, vol. 171(C), pages 296-313.
    2. Gandhi, Oktoviano & Rodríguez-Gallegos, Carlos D. & Zhang, Wenjie & Srinivasan, Dipti & Reindl, Thomas, 2018. "Economic and technical analysis of reactive power provision from distributed energy resources in microgrids," Applied Energy, Elsevier, vol. 210(C), pages 827-841.
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    4. Zhang, Wenjie & Gandhi, Oktoviano & Quan, Hao & Rodríguez-Gallegos, Carlos D. & Srinivasan, Dipti, 2018. "A multi-agent based integrated volt-var optimization engine for fast vehicle-to-grid reactive power dispatch and electric vehicle coordination," Applied Energy, Elsevier, vol. 229(C), pages 96-110.
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    Cited by:

    1. Rodríguez-Gallegos, Carlos D. & Vinayagam, Lokesh & Gandhi, Oktoviano & Yagli, Gokhan Mert & Alvarez-Alvarado, Manuel S. & Srinivasan, Dipti & Reindl, Thomas & Panda, S.K., 2021. "Novel forecast-based dispatch strategy optimization for PV hybrid systems in real time," Energy, Elsevier, vol. 222(C).
    2. A.S. Jameel Hassan & Umar Marikkar & G.W. Kasun Prabhath & Aranee Balachandran & W.G. Chaminda Bandara & Parakrama B. Ekanayake & Roshan I. Godaliyadda & Janaka B. Ekanayake, 2021. "A Sensitivity Matrix Approach Using Two-Stage Optimization for Voltage Regulation of LV Networks with High PV Penetration," Energies, MDPI, vol. 14(20), pages 1-24, October.
    3. Zhou, Yu & Li, Zhengshuo & Wang, Guangrui, 2021. "Study on leveraging wind farms' robust reactive power range for uncertain power system reactive power optimization," Applied Energy, Elsevier, vol. 298(C).
    4. Gandhi, Oktoviano & Rodríguez-Gallegos, Carlos D. & Zhang, Wenjie & Reindl, Thomas & Srinivasan, Dipti, 2022. "Levelised cost of PV integration for distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    5. Daiva Stanelytė & Virginijus Radziukynas, 2022. "Analysis of Voltage and Reactive Power Algorithms in Low Voltage Networks," Energies, MDPI, vol. 15(5), pages 1-26, March.
    6. 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.
    7. 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).
    8. Jayesh Thaker & Robert Höller, 2023. "Evaluation of High Resolution WRF Solar," Energies, MDPI, vol. 16(8), pages 1-13, April.
    9. Gandhi, Oktoviano & Zhang, Wenjie & Kumar, Dhivya Sampath & Rodríguez-Gallegos, Carlos D. & Yagli, Gokhan Mert & Yang, Dazhi & Reindl, Thomas & Srinivasan, Dipti, 2024. "The value of solar forecasts and the cost of their errors: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).

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