MacMackin, N., Miller, L., & Carriveau, R. (2019). Modeling and disaggregating hourly effects of weather on sectoral electricity demand. Energy, 188, 115956. http://agris.fao.org/agris-search/search.do?recordID=US201900427952
- Rupp Carriveau, Nicholas MacMackin
The CLEEN2040 Demand Curve Model (DCM) is a parameterized dynamic model that projects the average and peak hourly distribution of energy demand up to the year 2040 for representative energy utilities, customers or ISOs. The model was developed in such a way that all modifying parameters are implemented in the form of dynamic controls. This allows the user to quickly adjust parameter values, assessing a wide range of scenarios and identifying the effect of each factor and their potential interactions.
A preliminary utility level, bottom-up model has been developed in Excel VBA and a paper detailing this work has been submitted to Applied Energy. This model is unique in that it parameterizes all of these factors with dynamically adjustable controls. Based off of data from utility partners and literature sources, 100 demand coefficients were determined for each sector and parameter, essentially indicating the average percentage of daily demand occurring at each hour of the day, for each season. Likewise, an equal number of scaling factors were determined to estimate the peak demand on extreme weather days in each season. The magnitude of each sector and parameter’s load curve can be determined from current data and scaled based on dynamic controls for growth and technology penetration rates; meanwhile other controls adjust the shape (coefficients) based on policy or technology changes.
For more information about the supply match model, please contact the author.
Utility planning, storage planning, estimating GHG emissions from various technology penetration levels
Utilities, ISOs, customers
|Lindsay Miller-Branovacki||University of Windsor|