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Capacity Market and CfD Bidding Strategies case study

Modelling security of supply risks

The background

The Department of Energy and Climate Change (DECC) commissioned us to build a model that quantified the risk of system security events in the electricity market, to support their policy design decisions on the Capacity Market.

Our solution

We worked with DECC to deliver a model, known as the Unserved Energy Model (UEM), that produces security of supply metrics using high-resolution stochastic modelling.

The model we developed employed historical half hourly data from NASA on wind speeds to simulate the output of individual wind farms based on their location. This allowed the geographical diversification benefits of new wind to be accurately measured and thus quantified the contribution that wind could make to security of supply.  This is combined with historical demand and plant outage data from National Grid to enable a comprehensive analysis on the risks to GB’s security of supply.

The UEM can provide single-point estimates of key security metrics Loss of Load Expectation (hours) and Expected Energy Unserved (MWh) using a probabilistic calculation. It can also be run stochastically to provide an understanding of the uncertainty around these metrics and produce information on the probability, duration and severity of the security events.

The results

The LCP model has been used by DECC in its analysis on system security and supported its policy design decisions on the Capacity Market (CM). The model has also been integrated into DECC’s Dynamic Dispatch Model (DDM), where it is used to dynamically determine the annual capacity auction targets.

In addition, the model is now used by National Grid for its annual analysis to support recommendations on the CM volume to secure. This means that the model is ultimately used to determine how much generation capacity GB requires and therefore the volume of capacity contracts available.

 

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