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Economic evaluation of Nearly Zero Energy Cities

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  • Villa-Arrieta, Manuel
  • Sumper, Andreas

Abstract

As a contribution to the study of the urban energy transition, this paper proposes a novel model of energy-economic evaluation of the cities self-sufficiency and presents its application in the form of a case study. The objective of this study was to analyse the scope of the investment in the photovoltaic self-consumption of buildings in order to promote the creation of Prosumers communities within the cities. The operation of this model is based on the scalability of the Nearly Zero Energy concept from buildings to cities and seeks to evaluate Nearly Zero Energy Cities (nZEC): cities made up of Nearly Zero Energy Buildings (nZEB) and other installations of distributed generation to cover their energy demand by use of local renewable resources to the detriment of external resources. By using public data, we apply this model with the aim of economically evaluating the investment of six packages of energy rehabilitation and photovoltaic self-consumption in 17% of the residential buildings (37,800) in the city of Barcelona. To do this, we simulated 37 years of electricity distribution among Consumers, Producers and a hypothetical peer-to-peer community of Prosumers during the period 2014–2050 in hourly time intervals. The results indicated that the photovoltaic self-consumption and the local markets of Prosumers help to reduce primary energy consumption, the energy costs, and the CO2 emissions.

Suggested Citation

  • Villa-Arrieta, Manuel & Sumper, Andreas, 2019. "Economic evaluation of Nearly Zero Energy Cities," Applied Energy, Elsevier, vol. 237(C), pages 404-416.
  • Handle: RePEc:eee:appene:v:237:y:2019:i:c:p:404-416
    DOI: 10.1016/j.apenergy.2018.12.082
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    Cited by:

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    2. Waibel, Christoph & Evins, Ralph & Carmeliet, Jan, 2019. "Co-simulation and optimization of building geometry and multi-energy systems: Interdependencies in energy supply, energy demand and solar potentials," Applied Energy, Elsevier, vol. 242(C), pages 1661-1682.
    3. Eduardo Diz-Mellado & Samuele Rubino & Soledad Fernández-García & Macarena Gómez-Mármol & Carlos Rivera-Gómez & Carmen Galán-Marín, 2021. "Applied Machine Learning Algorithms for Courtyards Thermal Patterns Accurate Prediction," Mathematics, MDPI, vol. 9(10), pages 1-19, May.
    4. Cremers, Sho & Robu, Valentin & Zhang, Peter & Andoni, Merlinda & Norbu, Sonam & Flynn, David, 2023. "Efficient methods for approximating the Shapley value for asset sharing in energy communities," Applied Energy, Elsevier, vol. 331(C).
    5. Hassan Gholami & Harald Nils Røstvik, 2021. "Levelised Cost of Electricity (LCOE) of Building Integrated Photovoltaics (BIPV) in Europe, Rational Feed-In Tariffs and Subsidies," Energies, MDPI, vol. 14(9), pages 1-15, April.
    6. Sana Sayadi & Jan Akander & Abolfazl Hayati & Mattias Gustafsson & Mathias Cehlin, 2023. "Comparison of Space Cooling Systems from Energy and Economic Perspectives for a Future City District in Sweden," Energies, MDPI, vol. 16(9), pages 1-22, April.
    7. Jin-Li Hu & Min-Yueh Chuang, 2023. "The Importance of Energy Prosumers for Affordable and Clean Energy Development: A Review of the Literature from the Viewpoints of Management and Policy," Energies, MDPI, vol. 16(17), pages 1-16, August.
    8. Adam X. Hearn & Raul Castaño-Rosa, 2021. "Towards a Just Energy Transition, Barriers and Opportunities for Positive Energy District Creation in Spain," Sustainability, MDPI, vol. 13(16), pages 1-18, August.
    9. Yan Nie & Guoxing Zhang, 2020. "Indicator system to evaluate the effectiveness and efficiency of China clean power systems," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(7), pages 1381-1401, October.

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