Articles producció científicaEnginyeria Mecànica

A hybrid data-driven Co-simulation approach for enhanced integrations of renewables and thermal storage in building district energy systems

  • Identification data

    Identifier:  imarina:9452262
    Authors:  Elomari, Youssef; Aspetakis, Giorgos; Mateu, Carles; Shobo, Adedamola; Boer, Dieter; Marin-Genesca, M; Wang, Qian
    Abstract:
    Increasing the share of renewables is crucial for accelerating the sustainable transitions of modern building and district heating systems. This study develops a hybrid co-simulation framework, integrating a Python-based model with an established district energy system (DES) TRNSYS model, to optimize the design and control of on-site renewables such as photovoltaic panels (PV), solar thermal collectors, a water-to-water heat pump, seasonal thermal storage, a domestic hot water tank, and auxiliary heaters. The methodology combines diverse simulation tools and datadriven control sequences, enabling interaction across system components for enhanced energy efficiency and performance. The findings indicate that the optimized framework reduces net present cost by approximately 14 % and environmental impacts by 11 %. The data-driven controls further minimized temperature deviations significantly better than traditional Rule-Based Controls, achieving nearly optimal comfort levels with minimal environmental impact. The developed co-simulation enhances energy efficiency and intelligent controls in building applications, minimizes environmental impacts, and effectively covers the energy demand in building and districts (building clusters). These findings highlight the essential role of advanced hybrid co-simulation frameworks in improving DH system design and control, emphasizing their potential for sustainable urban energy transitions.
  • Others:

    Link to the original source: https://www.sciencedirect.com/science/article/pii/S2352710225006424?via%3Dihub
    APA: Elomari, Youssef; Aspetakis, Giorgos; Mateu, Carles; Shobo, Adedamola; Boer, Dieter; Marin-Genesca, M; Wang, Qian (2025). A hybrid data-driven Co-simulation approach for enhanced integrations of renewables and thermal storage in building district energy systems. Journal Of Building Engineering, 104(), 112405-. DOI: 10.1016/j.jobe.2025.112405
    Paper original source: Journal Of Building Engineering. 104 112405-
    Article's DOI: 10.1016/j.jobe.2025.112405
    Journal publication year: 2025
    Entity: Universitat Rovira i Virgili
    Paper version: info:eu-repo/semantics/publishedVersion
    Record's date: 2025-04-30
    URV's Author/s: Boer, Dieter-Thomas / Marín Genescà, Marc
    Department: Enginyeria Mecànica
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Publication Type: Journal Publications
    Author, as appears in the article.: Elomari, Youssef; Aspetakis, Giorgos; Mateu, Carles; Shobo, Adedamola; Boer, Dieter; Marin-Genesca, M; Wang, Qian
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Thematic Areas: Architecture, Arquitetura, urbanismo e design, Building and construction, Civil and structural engineering, Construction & building technology, Engenharias i, Engineering, civil, Mechanics of materials, Safety, risk, reliability and quality
    Author's mail: dieter.boer@urv.cat, marc.marin@urv.cat
  • Keywords:

    Co-simulation framework
    Deep reinforcement learning
    District energy system
    Heating system
    Multi-objective optimization
    Optimization
    Plants
    Pum
    Rule-based contro
    Rule-based control
    Architecture
    Building and Construction
    Civil and Structural Engineering
    Construction & Building Technology
    Engineering
    Civil
    Mechanics of Materials
    Safety
    Risk
    Reliability and Quality
    Arquitetura
    urbanismo e design
    Engenharias i
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