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Congestion vs Available capacity (customer with unpredictable load) #20

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FrankKr opened this issue Mar 27, 2023 · 2 comments
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@FrankKr
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FrankKr commented Mar 27, 2023

✅ DOR: profile for 2022 battery operator on FCR-market

The 'Congestion Management Paradigm' involves forecasting the load on a component, and calculating the amount of curtailment required to satisfy grid safety.
For customers with a particularly unpredictable load, such as a renewable generation, or a battery who acts on the FCR-market, both their contribution to the total load, as well as determining which setpoint to communicate to them are uncertain. In these cases, the 'congestion management' paradigm results in unused grid capacity, since wide safety margins need to be taken into account, twice.

Alternatively, the 'Available Capacity' for a (group of) customers can be forecasted. Here, the total load of all other customers on an asset is forecasted, and the remaining capacity is calculated.

Analyse and compare how much more kWh can be offered to e.g. a battery operator and how much congestion was caused when applying Congestion Management versus Available Capacity.

Acceptance criteria:

  • An analyses notebook is made, comparing how much grid capacity can be used by a customer when Congestion Management versus Available Capacity is used as a paradigm
  • The Congestion Management vs Available Capacity paradigms are clearly documented.

Additional information (Alliander internal): https://alliander.atlassian.net/wiki/spaces/SASOG/pages/3250390675/Mindset+choice%3A+Mitigating+Congestion+or+Free+Capacity

@MartijnCa
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@FrankKr can you refine this?

@FrankKr FrankKr moved this from 📋 Backlog to 🔖 Refined in AIFES project backlog May 19, 2023
@FrankKr
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FrankKr commented May 19, 2023

Refined!

@MartijnCa MartijnCa changed the title Congestion vs Available capacity Congestion vs Available capacity (battery operator) May 26, 2023
@MartijnCa MartijnCa changed the title Congestion vs Available capacity (battery operator) Congestion vs Available capacity (customer with unpredictable load) May 30, 2023
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