I. Selection of NSTs and Quantification of Impacts on Energy Demand: This step encompassed a process of selecting clusters of NSTs, which were integrated into the relevant demand-side models for quantitative analysis in the further WPs, based on literature review and stakeholder workshops. These trends and their potential importance and disruptiveness were discussed and narratives describing their mechanisms were developed.
II. Development of Transition Pathways for NSTs and Methodological Improvement in Modeling such Trends: A gap analysis (e.g. cross-sectoral aspects) has been carried out to identify to which extend the models were able to capture NSTs before their enhancement. This guided the further model developments and the focus analysis in step IV.
III. Policy Needs and Policy Analysis for Influencing Energy Demand Arising from NSTs: Policies, which can enhance the demand decreasing trends of NSTs, were analysed through literature research, expert interviews with policy makers from four EC DGs and workshops. As a result, policy challenges that need to be addressed by the energy demand models were identified and their representation in the energy demand models was assessed. Furthermore, a novel machine learning techniques that can be used to leverage on large smart meter data for policy evaluation was developed.
IV. Within the focus studies we investigated how energy demand models are to be improved to represent such NSTs. We further aimed at representing in energy demand models policies that can influence such trends in the light of the Energy Efficiency First (EE1) Principle brought forward in the EU policy framework.
• Prosumaging in residential buildings (WP 5): We investigated how different prices impact decision making of prosumagers specifically examining what load shifting potential prosumagers have, given different fiscal incentives and consequently how this affects energy consumption.
• Circular economy in the industry sector (WP 6): we improved the modelling of the impact of a circular economy on the industry sector via endogenous consideration of material stocks and flows related to the emission intensive materials steel and cement for buildings. In addition, the developed model considers cross-sectoral impacts by soft linking the building stock model, Invert/EE-Lab, and the industry model, FORECAST.
• Digitalization of the tertiary sector (WP 6): we implemented model enhancements to reflect the new trends of teleworking, e-commerce, building automation and data centers. We established cross-sectoral linkages to the residential and the transport sector through indicators in the fields of e-commerce and teleworking.
• Sharing economy in the transport sector (WP 7): we operationalized a satellite shared mobility module with PRIMES-TREMOVE. We quantified the energy requirements per mobility service and explicitly represented the choice of drivers for alternative options.
V. Overall scenarios and macro-economic modeling (WP 3): Based on the sectoral results we provide four scenarios that show how the NSTs might impact future energy demand. Furthermore, we modelled the macro-economic effects in these scenarios. Based on the sectoral results a bottom-up representation of key elements of energy system including transportation / mobility options, power generation energy efficiency programs was modelled
VI. Communication and dissemination: In the first reporting period, the newTRENDs project organized its first stakeholder workshop on ‘Policies for new trends in energy demand modeling”.
