||McKoen, K., Koch, A., Murshed, S.M., Meidl, P., Nichersu, A., Jumel, S. and Limani, B. Macro DE - Development of a methodology to calculate energy demand, ETI, 2010. https://doi.org/10.5286/UKERC.EDC.000277. Cite this using DataCite
||McKoen, K., Koch, A., Murshed, S.M., Meidl, P., Nichersu, A., Jumel, S. and Limani, B.
||Electricité de France SA (EDF SA)
||This project quantified the opportunity for Macro level Distributed Energy (DE) across the UK and accelerate the development of appropriate technology by 2020 for the purposes of significant implementation by 2030. The project studied energy demand such as residential accommodation, local services, hospitals, business parks and equipment, and is developing a software methodology to analyse local combinations of sites and technologies. This enabled the design of optimised distributed energy delivery solutions for these areas.
This deliverable is number 1 of 3 in Work Package 2. Its objective is to develop a methodology for forecasting energy demand profiles across residential and tertiary (light industry) properties in a given geographical area. In addition the report estimates the level of confidence in the methodology. The demand profiles generated form the basis for demandaggregation modelling in Work Package 4.
We believe that the methodology for the residential therrmal demand is sound and there is sufficient data such that a 10% uncertainty is reflective of the potential propagating error for the UK. While the tertiary sector data methodology is sound, there are two key issues with the datasets that may cause the larger error:
- The registered company information databases used in the tertiary sector demand calculations contain many records that are missing the number of employee data;
- Conversions between employee numbers and building floor area can only currently be performed at large tertiary sector groupings. The contribution of demand uncertainty from the tertiary component could be projected and tracked in the resulting demand calculations.
- The temporal resolution of the demand is good and the method, based on energy transporter load prediction techniques, seems able to predict the main trend and features of residential thermal demand
||ETI-DE2002: Macro Distributed Energy
||No associated datasets
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