nismod2

National Infrastructure Systems Model setup, configuration and tests

View the Project on GitHub nismod/nismod2

HIRE High-Resolution Energy Demand Model

Model code: nismod/energy_demand

Model documentation: ed.readthedocs.io

Key references:

Details of model inputs, parameters and outputs:

Notes on data sources:

Description

HIRE allows the simulation of long-term changes in energy demand patterns for the residential, service and industry sector on a high temporal and spatial scale. National end-use specific energy demand data is disaggregated on local authority district level and a bottom-up approach is implemented for hourly energy demand estimation for different fuel types and end uses.Future energy demand is simulated based on different socio-technical scenario assumptions such as technology efficiencies, changes in the technological mix per end use consumptions or behavioural change. Energy demand is simulated in relation to changes in scenario drivers of the base year. End-use specific socio-technical drivers for energy demands modelled where possible on a household level.

The methodology is published in [1].

For further model documentation, see [2]

References

  1. Eggimann, S., Hall, W.J., Eyre, N. (2019): A high-resolution spatio-temporal energy demand simulation of large-scale heat pump diffusion to explore the potential of heating demand side management. Applied Energy, 236, 997–1010. https://doi.org/10.1016/j.apenergy.2018.12.052.
  2. Eggimann, S., Usher, W., Russell, T. (2019) HIRE documentation. Available online: https://ed.readthedocs.io/en/latest/documentation.html

NISMOD Energy Demand data

DAFNI dataset v0.9.12

Data required by NISMOD Energy Demand model (HIRE).

Includes Local Authority District region definitions, hourly interval definitions, technology, efficiency, end-use and service parameters to explore changing energy demand, historic temperature time series from the Met Office, scenarios of future temperature derived from Weather@Home climate time series (aligned with the wind speed and insolation time series used to model renewables in energy supply), base year (2015) national and subnational energy consumption estimates, load profiles derived from the DECC Household Electricity Survey and Carbon Trust Advanced Metering Trial, and Office of National Statistics data on base year population and floor area.

Contains data covered by the Open Government Licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/ Contains National Statistics data © Crown copyright and database right 2012. Contains Ordnance Survey data © Crown copyright and database right 2012.

Contains national energy consumption estimates for 2015, derived from BEIS (2016): Energy consumption in the UK (ECUK). London, UK. Retrieved from: https://www.gov.uk/government/collections/energy-consumption-in-the-uk

Contains load profiles derived from DECC (2014) Household Electricity Survey. Retrieved from:https://www.gov.uk/government/collections/household-electricity-survey

Contains data derived from Carbon Trust Advanced Metering Trial licensed for academic research purposes, © Carbon Trust 2006, accessible at https://data.ukedc.rl.ac.uk/browse/edc/efficiency/residential/Buildings/AdvancedMeteringTrial_2006

Contains historic weather station data derived from Met Office (2019): Met Office MIDAS Open: UK Land Surface Stations Data (1853-current). Centre for Environmental Data Analysis, date of citation. http://catalogue.ceda.ac.uk/uuid/dbd451271eb04662beade68da43546e1

Contains future climate time series data derived from Guillod, B.P.; Jones, R.G.; Kay, A.L.; Massey, N.R.; Sparrow, S.; Wallom, D.C.H.; Wilson, S.S. (2017): Managing the Risks, Impacts and Uncertainties of drought and water Scarcity (MaRIUS) project: Large set of potential past and future climate time series for the UK from the weather@home2 model. Centre for Environmental Data Analysis, 17th April 2019. doi:10.5285/0cea8d7aca57427fae92241348ae9b03

All data compiled by Sven Eggimann, University of Oxford.