Commercial Skip Rate

In our Skip Rates explainer we describe how NESO's skip rate calculation works.

By comparing the real-world decisions made by the control room engineers with a stylised perfect world scenario, the standard skip rate metric is a good metric for understanding how efficiently NESO managed the dispatch at a system level. The unaccepted orders which are commercially in merit but fall outside of the Volume-Adjusted In Merit Stack are still felt by asset owners but don't get classed as skips. We developed the Commercial Skip Rate to give the asset owner's perspective on this.

The animation below walks through how accepted, unaccepted and skipped orders are classified against the in-merit stack.

Our Commercial Skip Rate (CSR) is designed to interpret skip rates from an asset owner's point of view. We believe that what's important to an asset owner is not whether they would have been accepted in a perfect-world scenario, but whether they were accepted if they were commercially in merit.

To calculate this, we apply the same logic of exclusions to the broader set of commercially in merit orders. Our calculations correspond to the Stage 5 All BM NESO calculations. We use Stage 5 because Stage 6 is only published monthly in arrears and the exclusions are not explicit (there are no public data on MFR which is the additional exclusion in Stage 6). We use All BM because we want to represent as close to the real world scenario as possible.

CSR is a good choice to understand individual asset dispatch. It covers the gap between "would have been accepted in a perfect skip-free world" and "could have been accepted commercially". Because we include more orders we get higher skip rates. CSR is not a good judgement of system-wide efficiency. For that, we still prefer the NESO metrics.

We find CSR to be more stable over time. It removes the scenario where your skip rate was zero one day (because you were deemed out of merit by volume) and non-zero the next (because you were deemed in merit by volume). The benefits of CSR are better locational signals, clearer relationships between merit order and skip rate and a more consistent basis for reporting.