Digitalization for Energy Demand - Energy demand digital and social trends: understanding and modeling
EDITS is a joint project between the Research Institute of Innovative Technology for the Earth (RITE) and RFF-CMCC European Institute on Economics and the Environment with the aim at collaborating on the empirical and modeling analysis of new disruptive trends of technological and social innovation for reducing energy demand. The institutes will develop the energy demand digital and social trends.
The project EDITS aims at shedding new light on the impact of technological and social transformations on energy demand. This requires improving the representation of energy utilization in models used to evaluate climate and energy scenarios and to improve the calibration of the models based on big data.The project EDITS aims at shedding new light on the impact of technological and social transformations on energy demand. This requires improving the representation of energy utilization in models used to evaluate climate and energy scenarios and to improve the calibration of the models based on big data.The following tasks are foreseen:
- The development of a new framework to describe in full the potential dynamics governing the way in which digitalization will impact decarbonisation. The paper will discuss potential impacts on energy demand, but also the socio-economic changes brought about by digitalization, its impact on the distribution of wealth and on the labour market, and potential implications for competitiveness. Finally, the paper will propose and summarize several indicators which can be used in empirical analyses to measure digitalization and its impact on the transition towards carbon neutrality.
- Analysis of smart meter electricity data to inform energy-demand modeling. This task foresees the analysis of big data coming from electricity smart meters. We plan to evaluate patterns of electricity consumption for hundreds of thousands of Italian customers at different temporal resolution. Using techniques from machine learning, we plan to identify clusters of consumers who exhibit different patterns of electricity utilization. These clusters can be used to improve the representation of heterogeneity of energy demand models.
- Energy demand scenarios with a building sector global model. We plan to improve the representation of the building sector renovation and new constructions in a building sector model. We plan to expand the EDGE modeling framework (co-developed by CMCC and PIK) and analyze energy demand scenarios under different socio-economic pathways (SSPs) for all the world major economies.
A paper and two reports are foreseen:
- Paper “A framework for the assessment of the impact of digitalization on the transition towards carbon neutrality” - Paper presenting a framework for the assessment of the impact of digitalization on the transition towards carbon neutrality, and potential indicators for use in empirical analysis
- Report “Empirical evidence of energy demand in the residential sector” - Report summarizing the empirical analysis of task 2
- Report “Modeling the energy demand in the building sector: key drivers and scenarios” - Report summarizing the building sector model assumptions and scenarios
Research Institute of Innovative Technology for the Earth (RITE)
04 November 2020
31 March 2021