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TSO-DSO Coordination Schemes to Facilitate Distributed Resources Integration

Author

Listed:
  • Fatemeh Najibi

    (Artificial Intelligence Research Centre, Department of Computer Science, University of London, London EC1V 0HB, UK)

  • Dimitra Apostolopoulou

    (Department of Electrical and Electronic Engineering, University of London, London EC1V 0HB, UK)

  • Eduardo Alonso

    (Artificial Intelligence Research Centre, Department of Computer Science, University of London, London EC1V 0HB, UK)

Abstract

The incorporation of renewable energy into power systems poses serious challenges to the transmission and distribution power system operators (TSOs and DSOs). To fully leverage these resources there is a need for a new market design with improved coordination between TSOs and DSOs. In this paper we propose two coordination schemes between TSOs and DSOs: one centralised and another decentralised that facilitate the integration of distributed based generation; minimise operational cost; relieve congestion; and promote a sustainable system. In order to achieve this, we approximate the power equations with linearised equations so that the resulting optimal power flows (OPFs) in both the TSO and DSO become convex optimisation problems. In the resulting decentralised scheme, the TSO and DSO collaborate to optimally allocate all resources in the system. In particular, we propose an iterative bi-level optimisation technique where the upper level is the TSO that solves its own OPF and determines the locational marginal prices at substations. We demonstrate numerically that the algorithm converges to a near optimal solution. We study the interaction of TSOs and DSOs and the existence of any conflicting objectives with the centralised scheme. More specifically, we approximate the Pareto front of the multi-objective optimal power flow problem where the entire system, i.e., transmission and distribution systems, is modelled. The proposed ideas are illustrated through a five bus transmission system connected with distribution systems, represented by the IEEE 33 and 69 bus feeders.

Suggested Citation

  • Fatemeh Najibi & Dimitra Apostolopoulou & Eduardo Alonso, 2021. "TSO-DSO Coordination Schemes to Facilitate Distributed Resources Integration," Sustainability, MDPI, vol. 13(14), pages 1-29, July.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:14:p:7832-:d:593515
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    References listed on IDEAS

    as
    1. Yuan, Zhao & Hesamzadeh, Mohammad Reza, 2017. "Hierarchical coordination of TSO-DSO economic dispatch considering large-scale integration of distributed energy resources," Applied Energy, Elsevier, vol. 195(C), pages 600-615.
    2. Najibi, Fatemeh & Niknam, Taher & Kavousi-Fard, Abdollah, 2016. "Optimal stochastic management of renewable MG (micro-grids) considering electro-thermal model of PV (photovoltaic)," Energy, Elsevier, vol. 97(C), pages 444-459.
    3. Gerard, Helena & Rivero Puente, Enrique Israel & Six, Daan, 2018. "Coordination between transmission and distribution system operators in the electricity sector: A conceptual framework," Utilities Policy, Elsevier, vol. 50(C), pages 40-48.
    4. Hadush, Samson Yemane & Meeus, Leonardo, 2018. "DSO-TSO cooperation issues and solutions for distribution grid congestion management," Energy Policy, Elsevier, vol. 120(C), pages 610-621.
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    1. Pearson, Simon & Wellnitz, Sonja & Crespo del Granado, Pedro & Hashemipour, Naser, 2022. "The value of TSO-DSO coordination in re-dispatch with flexible decentralized energy sources: Insights for Germany in 2030," Applied Energy, Elsevier, vol. 326(C).

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