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VIDEO
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Summary
Benchmarking performance is key to understanding the efficacy of your decision making and enables you to interrogateanalyse, and thereby improve, the decision making process.
Performance metrics will change and evolve as manual bids transition to algo Algo bids and as the sophistication of algo Algo bids improves. Therefore the number and types of reports will develop is likely to change over time.
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Using a Report Page
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Open a Report
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Report Types
Actual (Manual) vs Algo ‘what if’
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Download Data
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Report Types
Benchmarking reports evolve over time as reporting requirements change. Therefore the following list is an example set only.
Performance detailed 5min
This report compares the gross margin of Actual Manual bids against Algo “what if” bidsBids against What If Bids. Other metrics such as the difference in volumes are also reported. Note that as manual bids are replaced by Algo bids, new benchmarking reports will compare Algo actual gross margin against Algo “perfect hindsight” gross margin where perfect hindsight is calculated by rerunning the Algos using actual price outcomes to formulate optimal volumes from which gross margin is derived.
Content
A break down of the gross margin by service for both the Algo ‘what if’ and the manual actual bid (see gross margin description below). What If and Actual Bids
A description of gross margin is below
The difference between these values. What If and the Actual Bid gross margin.
Note that the difference is defined as
What If minus Actual
Specific effects on gross margin that can be attributed to certain particular market conditions. These are:
The service allocation stack (SAS) for lowerFCAS and RaiseFCAS.
Gross margin difference is attributed to lowerFCAS SAS when Algo expected energy target is greater than manual expected energy target. Therefore Under certain market conditions the algorithms increase energy generation in order to increase lowerFCAS gross margin enablement resulting in overall greater gross margin.
Gross margin difference is attributed to raiseFCAS SAS when Algo expected energy target is less than manual expected energy target. Therefore Under certain market conditions the algorithms decrease energy generation in order to increase raiseFCAS gross margin enablement resulting in overall greater gross margin.
Avoiding negative regulation gross margin for either lowerReg or raiseReg due to the change in generated energy caused by unit response to regulation AGC component.
Gross margin difference is attributed to Algo Algos avoiding negative gross margin if the Algo optimised regulation volume is zero, and to avoid double counting for SAS (above), the Algo and manual energy bid must be the same.
Daily Summary
This report contains the same components of gross margin as Actual What If described above. However this report aggregates (sums) the 5 minute values for the selected day. Note that it does not include the specific effects on gross margin.
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Raise Contingency Liability
This report shows the total liability for the cost recovery mechanism of Raise Contingency Services. The report includes the Generator Liability $ per MWh and the total liability by duid (that being the Generator Liability $ per MWh multiplied by the MWh of generation).
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Definitions
Gross Margin
As a good first order approximation, total gross margin includes the revenue gained from providing a service plus the impact on the energy produced and the fuel used in providing an FCAS service plus any other impacts.
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Gross Margin = Service Revenue + Impact on Energy Revenue + Impact on Fuel Value + Other |
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