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Amin Moazami

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Associate Professor

Norwegian University of Science and Technology

Norway

Research Interests

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Professors in Norway Professors in Energy Engineering Energy Engineering professors in Norway

Recent Grants

Grant: Close

Harnessing Synergies and minimizing Trade-off among Deep Renovation measures and decarbonizing District Heating system (STaDRenDHeat)

Open Date: 2022-01-01

Close Date: 2025-01-01

Grant: Close

How prepared are Swedish detached houses to adapt to Climate Change?

Open Date: 2022-01-01

Close Date: 2025-01-01

Grant: Close

Optimal Utilization of Resources towards Neutral Climate Built Environments in Europe by 2030-2050 (LIFELINE-2050)

Open Date: 2022-01-01

Close Date: 2025-01-01

Grant: Close

COLLECTiEF - Collective Intelligence for Energy Flexibility

Open Date: 2021-06-01

Close Date: 2025-05-01

Grant: Close

Konseptutredning for innovative energi-og klimaløsninger i bygg, områderog energisystem

Open Date: 2020-01-01

Close Date: 2021-01-01

Articles (12)

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2026

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2026

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2026

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2025

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2025

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2025

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2023

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2023

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2023

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2021

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2021

Year:

2020

Collaborators (6)

Kavan Javanroodi

Assistant Professor

Lund University

SWEDEN

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Mohammadreza Aghaei

Senior Scientist

Norwegian University of Science and Technology (NTNU)

NORWAY

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Vahid M. Nik

Full Professor

Lund University

SWEDEN

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Behzad Najafi

Associate Professor

Politecnico di Milano

ITALY

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Fabio Rinaldi

Associate Professor

Politecnico di Milano

ITALY

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Zoltan Nagy

Professor and Chair

Eindhoven University of Technology

NETHERLANDS

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ApplyKite TwinLearns as you apply

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Amin Moazami

Research Interests

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Recent Grants

Articles (12)

Experimental insights on CIRLEM

Energy flexibility estimation and forecasting in large buildings for local flexibility markets applications

Ageing in a warming world: Projecting heating and cooling demands for elderly housing in norway – A case study

Enhancing self-consumption ratio in a smart microgrid by applying a reinforcement learning-based energy management system

From flexible building to resilient energy communities

Assessing the impact of building geometry detail levels on the accuracy of calibrated urban building energy models

Assessing the impact of employing machine learning-based baseline load prediction pipelines with sliding-window training scheme on offered flexibility estimation for different building categories

Machine learning-based estimation of buildings' characteristics employing electrical and chilled water consumption data: Pipeline optimization

Machine-Learning-Based Prediction of HVAC-Driven Load Flexibility in Warehouses

On the impact of stochastic modeling of occupant behavior on the energy use of office buildings

Using collective intelligence to enhance demand flexibility and climate resilience in urban areas

A performance comparison of multi-objective optimization-based approaches for calibrating white-box building energy models.

Collaborators (6)

Kavan Javanroodi

Mohammadreza Aghaei

Vahid M. Nik

Behzad Najafi

Fabio Rinaldi

Zoltan Nagy

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