TSO-DSO coordination to acquire services from distribution grids: Simulations, cost-benefit analysis and regulatory conclusions from the SmartNet project

Rossi, Marco; Migliavacca, Gianluigi; Viganò, Giacomo; Siface, Dario; Madina, Carlos; Gómez, Inés; Kockar, Ivana; Morch, Andrei

doi:10.1016/j.epsr.2020.106700

Cited by 33 publications

(29 citation statements)

References 14 publications

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“…Although significant effort has been reported with regard to managing the information and data exchange between TSOs and DSOs, the continued growth of flexibility resources within the operational boundaries of the DSO has increased the amount of information being exchanged, making it crucial for the enhanced coordination and cooperation between TSOs and DSOs (Givisiezet al, 2020;Rossi et al, 2020). In Rossi et al (2020), the main challenges in simulating flexibility markets are investigated, in terms of a cost-benefit analysis for three European countries, Italy, Denmark, and Spain, based on 2030 scenarios. In Givisiez, et al (2020), relevant techniques for different TSO-DSO coordination schemes are reviewed and investigated.…”

Section: Introductionmentioning

confidence: 99%

Developing Enhanced TSO-DSO Information and Data Exchange Based on a Novel Use Case Methodology

et al. 2021

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The growing penetration of renewable energy sources (RES) in the electrical power sector has increased the amount of distributed generation (DG) units connected at the distribution system level. In this context, new balancing challenges have arisen, creating the need for a novel use case methodology to enable an active role at the distribution system level such that transmission system operators (TSOs) can coordinate with distribution system operators (DSOs) with regard to connected resources for balancing purposes. In this study, the exploitation of the DSO-connected resources for balancing purposes in a market environment is proposed and evaluated via a novel business use case (BUC) methodology based on the categorization of IEC 62913-1. More specifically, in order to address different balancing market situations, two scenarios are considered with regard to the BUC. The first one represents the data exchange between the TSO, the DSO, and the balancing service provider (BSP). The second one represents an alternative scenario where data are exchanged directly between the TSO and the DSO, where the DSO also takes on the role of the BSP. The proposed BUC was also developed in order to validate the required data modeling and exchange mechanisms between DSOs and TSOs in order to exploit DSO-connected resources for overall system balancing purposes across different time scales.

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Section: Introductionmentioning

confidence: 99%

Developing Enhanced TSO-DSO Information and Data Exchange Based on a Novel Use Case Methodology

et al. 2021

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“…Linearization of ( 14), ( 15) and (28). Since the above constraints are similar in their structure, the lineaization is demonstrated by using constraints (14). The linearization is performed in two steps.…”

Section: B Practical Considerations Of the Methodsmentioning

confidence: 99%

“…Within Case Study 1, a small 1-hour example with 4 buses 2 generators within TSO, and one DSO is considered to demonstrate the convergence of multipliers. Within Case Study 2, a small 9-bus system [43] is considered to demonstrate the efficiency of linearization and convergence of voltages to satisfy constraints ( 13)- (14). Within Case Study 3, 4-, 8-and 16-hour instances with 1 TSO modeled using IEEE 118-bus system [43] and 32 DSOs modeled using IEEE 34-bus systems [43] are considered to demonstrate the methods ability to coordinate a large number of DSO and the cost advantage of the coordination.…”

Section: Numerical Testingmentioning

confidence: 99%

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TSO-DSO Operational Planning Coordination through Surrogate Lagrangian Relaxation

Bragin¹,

Dvorkin²

2021

Preprint

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With the proliferation of distributed energy resources (DERs), located at the Distribution System Operator (DSO) level, uncertainties propagate from Transmission System Operator (TSO) to DSOs and vice versa. Therefore, to enable interoperability, while ensuring higher flexibility and cost-efficiency, both systems need to be efficiently coordinated to operate in sync. Moreover, because of the intermittency of renewable generation, voltages exhibit fluctuations thus necessitating the inclusion of AC power flow. Difficulties behind creating such TSO-DSO coordination include the combinatorial nature of the operational planning problem involved at the transmission level as well as the nonlinearity of AC power flow within both systems. These considerations significantly increase the complexity even under the deterministic setting. In this paper, a deterministic TSO-DSO operational planning coordination problem is considered and a novel decomposition and coordination approach is developed. Within the new method, the problem is decomposed into TSO and DSO subproblems, which are efficiently coordinated by updating Lagrangian multipliers. The nonlinearities at the TSO level caused by AC power flow constraints are resolved through a novel dynamic linearization. Numerical results based on the coordination of 118-bus TSO system with 32 DSO 34-bus systems indicate that both systems benefit from the coordination.<br>

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“…Flexibility benefits benefits enabled by DERs [1], [2], [5]- [7], [11], [16], [17], [21]- [23], which include balancing supply and demand, and voltage control [2], [16], [17], voltage fluctuation and congestion mitigation [21], as well as prosumer behavior of customers [1], can be achieved. The cost-benefits have also been discussed in [18]- [20]. With high penetration of DERs, to enable efficient integration of renewable resources at TSO and DSO levels, proactive management of resources is required through appropriate TSO-DSO coordination [8].…”

mentioning

confidence: 99%

TSO-DSO Operational Planning Coordination through "l1-Proximal" Surrogate Lagrangian Relaxation

Bragin¹,

Dvorkin²

2021

Preprint

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The proliferation of distributed energy resources (DERs), located at the Distribution System Operator (DSO) level, bring new opportunities as well as new challenges to the operations within the grid, specifically, when it comes to the interaction with the Transmission System Operator (TSO). To enable interoperability, while ensuring higher flexibility and cost-efficiency, DSOs and the TSO need to be efficiently coordinated. Difficulties behind creating such TSO-DSO coordination include the combinatorial nature of the operational planning problem involved at the transmission level as well as the nonlinearity of AC power flow within both systems. These considerations significantly increase the complexity even under the deterministic setting. In this paper, a deterministic TSO-DSO operational planning coordination problem is considered and a novel decomposition and coordination approach is developed. Within the new method, the problem is decomposed into TSO and DSO subproblems, which are efficiently coordinated by updating Lagrangian multipliers. The nonlinearities at the TSO level caused by AC power flow constraints are resolved through a dynamic linearization while guaranteeing feasibility through ``l1-proximal'' terms. Numerical results based on the coordination of the 118-bus TSO system with up to 32 DSO 34-bus systems indicate that the method efficiently overcomes the computational difficulties of the problem.<br>

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TSO-DSO coordination to acquire services from distribution grids: Simulations, cost-benefit analysis and regulatory conclusions from the SmartNet project

Cited by 33 publications

References 14 publications

Developing Enhanced TSO-DSO Information and Data Exchange Based on a Novel Use Case Methodology

Developing Enhanced TSO-DSO Information and Data Exchange Based on a Novel Use Case Methodology

TSO-DSO Operational Planning Coordination through Surrogate Lagrangian Relaxation

TSO-DSO Operational Planning Coordination through "l1-Proximal" Surrogate Lagrangian Relaxation

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