GB Non-renewable Embedded Generation Forecasting Study
National Grid Electricity System Operator and National Grid Electricity Transmission
Jeremy Caplin (.box.SO.Innovation@nationalgrid.com)
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Network Innovation Allowance
Modelling, Distributed Generation and Electricity Transmission Networks
The focus of the project will be on 2 to 7 days ahead forecasts and review of all embedded generation fuel types for potential categorisation according to constraints e.g. limited supply (waste), less restricted supply (diesel).
Development of specific embedded generation models for biomass, landfill gas, diesel generation. Consideration will be given to the implementation of these models within the current Energy Forecasting System (EFS) software used in National Grid. A full report with complete model specifications will be produced.
To design the embedded generation models, this project will
- Investigate how large is their total contribution, and if there characteristic generation profiles for these generators.
- Determine if there a characteristic profiles for the net effect of all the embedded generation (excluding wind and solar as these are weather dependent).
- Identify any there correlations between the net effect of the embedded generation and any other generator type.
- Identify any variables that have a significant impact on the generation profiles for each of the generators.
- Identify incremental project benefit by defining forecasting error with and without the developed non-renewable embedded generation models.
- Detailed models of embedded generation (other than wind and solar) resulting from data analysis. These models will be validated for implementation within National Grid’s Energy Forecasting System.
- Incremental project benefit demonstrated from the developed embedded generation models.