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Reducing CO 2 Emissions for PV-CHP Hybrid Systems by Using a Hierarchical Control Algorithm

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  • Tanja M. Kneiske

    (Fraunhofer Institute for Energy Economics and Energy System Technology (IEE), Joseph-Beuys-Str. 8, 34117 Kassel, Germany
    Current address: Fraunhofer Research Institution for Energy Infrastructures and Geothermal Systems (IEG), Gulbener Str. 23, 03046 Cottbus, Germany.)

Abstract

National targets for CO 2 reduction in the German building sector have stagnated due to low refurbishment rates. This paper proposes an alternative approach using highly efficient, decentralized energy systems. By combining photovoltaic (PV) systems and combined heat and power (CHP) plants controlled by a modified hierarchical control algorithm, CO 2 emissions can be reduced. Results from a single-family home show a 13% CO 2 reduction with only 11% higher operational costs on heating days. On summer days, up to 50% CO 2 emissions can be avoided without additional costs. The control algorithm easily adapts to changing input parameters, making it suitable for different countries and business cases. Overall, with its modified control, the PV-CHP hybrid system can effectively reduce CO 2 emissions and adapt to varying conditions. The control can be easily used for other energy systems, like fuel cells or heat pumps.

Suggested Citation

  • Tanja M. Kneiske, 2023. "Reducing CO 2 Emissions for PV-CHP Hybrid Systems by Using a Hierarchical Control Algorithm," Energies, MDPI, vol. 16(17), pages 1-24, August.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:17:p:6176-:d:1225187
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    References listed on IDEAS

    as
    1. Kneiske, T.M. & Braun, M. & Hidalgo-Rodriguez, D.I., 2018. "A new combined control algorithm for PV-CHP hybrid systems," Applied Energy, Elsevier, vol. 210(C), pages 964-973.
    2. Romero Rodríguez, Laura & Salmerón Lissén, José Manuel & Sánchez Ramos, José & Rodríguez Jara, Enrique Ángel & Álvarez Domínguez, Servando, 2016. "Analysis of the economic feasibility and reduction of a building’s energy consumption and emissions when integrating hybrid solar thermal/PV/micro-CHP systems," Applied Energy, Elsevier, vol. 165(C), pages 828-838.
    3. Balcombe, Paul & Rigby, Dan & Azapagic, Adisa, 2015. "Environmental impacts of microgeneration: Integrating solar PV, Stirling engine CHP and battery storage," Applied Energy, Elsevier, vol. 139(C), pages 245-259.
    4. Negri, Simone & Giani, Federico & Blasuttigh, Nicola & Massi Pavan, Alessandro & Mellit, Adel & Tironi, Enrico, 2022. "Combined model predictive control and ANN-based forecasters for jointly acting renewable self-consumers: An environmental and economical evaluation," Renewable Energy, Elsevier, vol. 198(C), pages 440-454.
    5. Fischer, David & Bernhardt, Josef & Madani, Hatef & Wittwer, Christof, 2017. "Comparison of control approaches for variable speed air source heat pumps considering time variable electricity prices and PV," Applied Energy, Elsevier, vol. 204(C), pages 93-105.
    6. Kertu Lepiksaar & Vladislav Mašatin & Igor Krupenski & Anna Volkova, 2023. "Effects of Coupling Combined Heat and Power Production with District Cooling," Energies, MDPI, vol. 16(12), pages 1-16, June.
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