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WHY

Climbing the causality ladder to understand and project the energy demand of the residential sector
Funder: European CommissionProject code: 891943 Call for proposal: H2020-LC-SC3-EE-2019
Funded under: H2020 | RIA Overall Budget: 1,999,980 EURFunder Contribution: 1,999,980 EUR
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Description

In order to mitigate climate change effects, urgent action is required in all sectors of the economy to significantly reduce greenhouse gases (GHG) emission. Energy System Models (ESM) are tools that help energy analysts, planners and policy makers to rationally describe energy systems and systematically evaluate the impacts of long-term scenarios. On the supply side, ESMs have provided useful results, but however, on the demand side, they lack the degree of accuracy required for proper characterization of, among others, the use of energy in households. One of the intrinsic difficulties is that energy demand in the residential sector is influenced by a myriad of factors (like the high diversity of dwellings, socio-economic conditions of the social/family units, and behavioral-related consumption patterns) that cannot easily be accounted for in traditional ESMs. To overcome this challenge, the novel Causal Modeling will be used to quantitatively analyse human decision making in energy consumption and their reactions to interventions (e.g. policy changes). This will be combined with an innovative FFORMA approach which allows multiple different load profiles to be categorised by a set of vectors describing it. WHY will therefore create innovative methodologies for short and long term load forecasting. The WHY modeling will allow to directly assess the impact of a multitude of policies on the energy system as well as performing both ex-ante and ex-post assessment over policy measures. WHY will therefore contribute to a holistic understanding of household energy consumption and improved demand modelling. The WHY toolkit will be used to assess several scenarios simulating different policy measures. Integration with widely-used ESMs (PRIMES, TIMES) will be demonstrated and the results analyzed. All results will be open-sourced to maximize uptake, and be widely disseminated to diverse target audiences (i.e. DSOs, energy companies, policy makers, researchers).

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