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Renewable Energy Generation Scenarios Using 3D Urban Modeling Tools—Methodology for Heat Pump and Co-Generation Systems with Case Study Application †

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  • Verena Weiler

    (Centre for Sustainable Energy Technology, University of Applied Sciences Stuttgart, 70174 Stuttgart, Germany
    These authors contributed equally to this work.)

  • Jonas Stave

    (Centre for Sustainable Energy Technology, University of Applied Sciences Stuttgart, 70174 Stuttgart, Germany
    These authors contributed equally to this work.)

  • Ursula Eicker

    (Centre for Sustainable Energy Technology, University of Applied Sciences Stuttgart, 70174 Stuttgart, Germany)

Abstract

In the paper, a method was developed to automatically dimensionalize and calculate central energy generation and supply scenarios with a district heating system for cities based on 3D building models in the CityGML format and their simulated heat demand. In addition, the roof geometry of every individual building is used to model photovoltaic energy generation potential. Two types of supply systems, namely a central heat pump (HP) system and a large co-generation (combined heat and power-CHP) system (both with a central storage and district distribution system), are modeled to supply the heat demand of the area under investigation. Both energy generation models are applied to a case study town of 1610 buildings. For the HP scenario, it can be shown that the case study town’s heat demand can be covered by a monovalent, low-temperature system with storage, but that the PV only contributes 15% to the HP electricity requirement. For the CHP scenario, only 61% of the heat demand can be covered by the CHP, as it was designed for a minimum of 4000 operating hours. Both the PV and the CHP excess electricity are fully injected into the grid. As a result, the primary energy comparison of both systems strongly depends on the chosen primary energy factors (PEF): with given German regulations the CHP system performs better than the HP system, as the grid-injected electricity has a PEF of 2.8. In the future, with increasingly lower PEFs for electricity, the situation reverses, and HPs perform better, especially if the CHP continues to use natural gas. Even when renewable gas from a power to gas (P2G) process is used for the CHP, the primary energy balance of the HP system is better, because of high conversion losses in the P2G process.

Suggested Citation

  • Verena Weiler & Jonas Stave & Ursula Eicker, 2019. "Renewable Energy Generation Scenarios Using 3D Urban Modeling Tools—Methodology for Heat Pump and Co-Generation Systems with Case Study Application †," Energies, MDPI, vol. 12(3), pages 1-19, January.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:3:p:403-:d:201284
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    References listed on IDEAS

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    Cited by:

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    2. Vytautas Bocullo & Linas Martišauskas & Ramūnas Gatautis & Otilija Vonžudaitė & Rimantas Bakas & Darius Milčius & Rytis Venčaitis & Darius Pupeikis, 2023. "A Digital Twin Approach to City Block Renovation Using RES Technologies," Sustainability, MDPI, vol. 15(12), pages 1-26, June.
    3. S. Köhler & M. Betz & E. Duminil & U. Eicker & B. Schröter, 2021. "A holistic approach to model electricity loads in cities [Ein ganzheitlicher Ansatz zur Modellierung des Stromverbrauchs in Städten]," NachhaltigkeitsManagementForum | Sustainability Management Forum, Springer, vol. 29(2), pages 143-152, June.
    4. Eid Gul & Giorgio Baldinelli & Pietro Bartocci, 2022. "Energy Transition: Renewable Energy-Based Combined Heat and Power Optimization Model for Distributed Communities," Energies, MDPI, vol. 15(18), pages 1-18, September.
    5. Verena Weiler & Ursula Eicker, 2021. "Automatic energy demand and system simulation at district level," NachhaltigkeitsManagementForum | Sustainability Management Forum, Springer, vol. 29(2), pages 133-141, June.
    6. Francesco Calise & Maria Vicidomini & Mário Costa & Qiuwang Wang & Poul Alberg Østergaard & Neven Duić, 2019. "Toward an Efficient and Sustainable Use of Energy in Industries and Cities," Energies, MDPI, vol. 12(16), pages 1-28, August.
    7. Keyu Bao & Rushikesh Padsala & Volker Coors & Daniela Thrän & Bastian Schröter, 2021. "A GIS-Based Simulation Method for Regional Food Potential and Demand," Land, MDPI, vol. 10(8), pages 1-18, August.

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