Reactive Power Provision for Voltage Support Activating Flexibility of Active Distribution Networks via a TSO-DSO Interactive Mechanism

Tang, Kunjie; Fang, Rui; Wang, Li; Li, Junge; Dong, Shufeng; Song, Yonghua

doi:10.1109/isgt-asia.2019.8881127

Cited by 10 publications

(3 citation statements)

References 14 publications

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“…However, the exact market rules remain unclear. The same approach is used by Tang et al [72]. In addition, they define the TSO-DSO interaction in detail: First, the TSO sends its reactive demand request to the DSO.…”

Section: Grid-level Marketsmentioning

confidence: 99%

Reactive Power Markets: A Review

2022

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Liberalization of the energy system sets the way towards market-based solutions for ancillary service provision. Local reactive power markets are envisioned to achieve more economically and technically efficient reactive power provision to solve voltage control problems in future distribution and transmission grids. However, market-based reactive power procurement is a difficult and yet unsolved problem. This survey provides a comprehensive overview of the characteristics and hardships of reactive power markets. That is followed by a literature overview of reactive power market design, including local markets and markets on system operator level. Further, methods how to analyse reactive power markets are discussed, focusing on market power, game theoretical approaches, Reinforcement Learning, and manipulation of reactive power markets. From this overview, trends and current research gaps are derived and some general research recommendations are given to serve as a guideline for future research in the field of reactive power markets.

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Section: Grid-level Marketsmentioning

confidence: 99%

Reactive Power Markets: A Review

2022

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“…In the second stage of the approach, the superordinate grid operator carries out an OPF in which downstream grids are taken into account as virtual power plants. A very similar approach of market coordination is presented by Tang et al (2019). The method comprises of four stages and starts with the TSO sending its reactive power request to the DSOs, which then simultaneously determine their flexibility ranges and EPFs to send them back to the TSO.…”

Section: State Of the Artmentioning

confidence: 99%

“…On the one hand, this reduces the amount of data that is exchanged between the market participants, on the other hand, convex functions can be used by a variety of optimizers and lead to shorter solution times of the optimization problem (Frank et al, 2012). Further, we assume exactly a single grid coupling point to the superordinate grid level for each grid and no horizontal grid coupling points, as it was done in similar approaches Doostizadeh et al, 2018;Pudjianto et al, 2019;Retorta et al, 2020;Tang et al, 2019). Finally, each network operator presumes a voltage of 1 pu at the slack node when determining its reactive power flexibility range.…”

Section: Market Assumptionsmentioning

confidence: 99%

Design and Evaluation of a Multi-level Reactive Power Market

Bozionek

Wolgast

Nieße

2022

Preprint

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The shift from conventional power plants on transmission level to distributed energy resources in the distribution grids requires procedures to enable efficient and economic reactive power exchange across different voltage levels. In this paper, we propose a multi-level reactive power market that enables reactive power provision from distributed energy resources to higher voltage levels. Each grid operator operates a local reactive power market and offers local reactive power potential, as an intermediary, to superordinate grid operators by passing on its aggregated cost curve and flexibility range. As a result, there is a low requirement of communication between the market participants and each grid operator is free to choose its local market rules as well as the optimization algorithm used. First results from a case study show that our decentralized market approach can realize an economically efficient multi-level reactive power provision that is close to a centrally computed optimal solution, without violating local grid constraints.

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