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Data-driven based behavior intervention decision-making to ease energy poverty

Energy poverty households face insufficient access to affordable and reliable energy services, which can lead to adverse health effects and risky coping strategies. The EU made energy poverty a policy priority in the Clean energy... ver más

31/05/2025

KIT

130K€

Presupuesto del proyecto: 130K€

Líder del proyecto

KARLSRUHER INSTITUT FUER TECHNOLOGIE No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

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Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2023-07-14

HORIZON-MSCA-2022-PF-01-01: MSCA Postdoctoral Fellowships 2022 ExpectedOutcome:

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Cerrada hace 2 años

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2 Participantes

KIT

130.39K€ | Lider

TECHNICAL UNIVERSITY OF DENM...

N.D. | Participante

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Duración del proyecto: 22 meses Fecha Inicio: 2023-07-14
Fecha Fin: 2025-05-31

Líder del proyecto

KARLSRUHER INSTITUT FUER TECHNOLOGIE No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 130K€

Descripción del proyecto Energy poverty households face insufficient access to affordable and reliable energy services, which can lead to adverse health effects and risky coping strategies. The EU made energy poverty a policy priority in the Clean energy for all Europeans package in 2019, and one of the objectives is to address energy poverty by promoting energy-efficient behaviors. However, intervening in users' behavioral decisions is difficult as it requires a deep understanding of the behavior patterns and a rational explanation of the behavior mechanism. This project will address a key question in energy poverty research: can behavior pattern analytics facilitate the decision-making of energy poverty? Hence, the main objective is to assess if data-driven analytics of energy use patterns can provide insight into behavioral interventions to address energy poverty. Through this project, the applicant plans to use three progressive analytics tasks to answer the question: (i) Identify the behavior patterns of energy consumption (Descriptive Analytics). (ii) Reveal potential cognitive biases that impede high energy efficiency (Prescriptive Analytics). (iii) Explore policy interventions against cognitive bias (Prediction Analytics). The project will analyze user-level data through Graph Data Modeling to quantify energy use patterns and behaviors, overcoming the limitations of the traditional method relying only on descriptive statistics. Host and secondment will complement the interdisciplinarity of the project from the perspectives of energy behavior (behavioral science) and cognitive visualization (computer science) respectively. The project will facilitate the applicant's long-term research goals with interdisciplinary knowledge, enhancing the development of his career as an independent researcher. Potential beneficiaries are energy poverty households and energy stakeholders. The proposal is in line with the Sustainable Development Goals (SDGs) and objectives of the H2020 program.

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