IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i5p1264-d330230.html
   My bibliography  Save this article

Energy Potential Mapping: Open Data in Support of Urban Transition Planning

Author

Listed:
  • Michiel Fremouw

    (Faculty of Architecture and the Built Environment, Department of Architectural Engineering + Technology, Delft University of Technology, 2628 BL Delft, The Netherlands)

  • Annamaria Bagaini

    (Department of Planning, Design and Technology of Architecture, Sapienza University, 00185 Rome, Italy)

  • Paolo De Pascali

    (Department of Planning, Design and Technology of Architecture, Sapienza University, 00185 Rome, Italy)

Abstract

Cities play a key role in driving the transition to sustainable energy. Urban areas represent between 60% and 80% of global energy consumption and are a significant source of CO 2 emissions, making energy management at the urban scale an important area of research. Urban energy systems have a strong influence on the environment, economy, social dimensions and urban spatial planning. Energy consumption affects the urban microclimate, urban comfort, human health, and conversely, urban physical, economic and social characteristics affect the energy urban profile. In order to improve the quality of energy strategies, policies, and plans, local authorities need decision support tools, like energy potential mapping, which have risen significance in the last decades. Energy data are crucial for those tools. They can increase the quality and effectiveness of energy planning but also support the integration between energy and spatial planning. Energy data can also stimulate citizen engagement as well as encourage sustainable behaviours and CO 2 emission reduction. This paper aims to increase the practice of data-aware planning, through the study of problems in energy data acquisition and processing observed in European projects focused on developing energy mapping tools. The problems observed attend to two main areas: technical and socio-economic issues. Those were derived from a comparison of energy mapping tools, and the work conducted for the PLANHEAT development. The scope of the research is to understand the main recurring issues in energy data acquisition and processing, in order to overcome the barriers in data availability. Increasing awareness of the relevance of energy data can foster the use of energy mapping tools, increasing the quality of energy policies and planning.

Suggested Citation

  • Michiel Fremouw & Annamaria Bagaini & Paolo De Pascali, 2020. "Energy Potential Mapping: Open Data in Support of Urban Transition Planning," Energies, MDPI, vol. 13(5), pages 1-15, March.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:5:p:1264-:d:330230
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/5/1264/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/5/1264/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Owens, Susan E., 1992. "Land-use planning for energy efficiency," Applied Energy, Elsevier, vol. 43(1-3), pages 81-114.
    2. Futcher, Julie Ann & Mills, Gerald, 2013. "The role of urban form as an energy management parameter," Energy Policy, Elsevier, vol. 53(C), pages 218-228.
    3. William P. Anderson & Pavlos S. Kanaroglou & Eric J. Miller, 1996. "Urban Form, Energy and the Environment: A Review of Issues, Evidence and Policy," Urban Studies, Urban Studies Journal Limited, vol. 33(1), pages 7-35, February.
    4. Manfren, Massimiliano & Caputo, Paola & Costa, Gaia, 2011. "Paradigm shift in urban energy systems through distributed generation: Methods and models," Applied Energy, Elsevier, vol. 88(4), pages 1032-1048, April.
    5. Jaccard, Mark & Failing, Lee & Berry, Trent, 1997. "From equipment to infrastructure: community energy management and greenhouse gas emission reduction," Energy Policy, Elsevier, vol. 25(13), pages 1065-1074, November.
    6. Alhamwi, Alaa & Medjroubi, Wided & Vogt, Thomas & Agert, Carsten, 2017. "GIS-based urban energy systems models and tools: Introducing a model for the optimisation of flexibilisation technologies in urban areas," Applied Energy, Elsevier, vol. 191(C), pages 1-9.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. João Monteiro & Nuno Sousa & João Coutinho-Rodrigues & Eduardo Natividade-Jesus, 2024. "Challenges Ahead for Sustainable Cities: An Urban Form and Transport System Review," Energies, MDPI, vol. 17(2), pages 1-26, January.
    2. Paola Marrone & Federico Fiume & Antonino Laudani & Ilaria Montella & Martina Palermo & Francesco Riganti Fulginei, 2023. "Distributed Energy Systems: Constraints and Opportunities in Urban Environments," Energies, MDPI, vol. 16(6), pages 1-27, March.
    3. Dumiter Florin Cornel & Turcaș Florin Marius & Boiţă Marius, 2023. "Oil Shock Impact Upon Energy Companies Investment Portfolios. Trends and Evolutions in the Energy Consumption Sector," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, vol. 33(1), pages 1-27, March.
    4. Benedetto Nastasi & Massimiliano Manfren & Michel Noussan, 2020. "Open Data and Energy Analytics," Energies, MDPI, vol. 13(9), pages 1-3, May.
    5. Hailiang Huang & Changfeng Shi, 2023. "Analysis of the Path Optimization of the Sustainable Development of Coal-Energy Cities Based on TOPSIS Evaluation Model," Energies, MDPI, vol. 16(2), pages 1-17, January.
    6. Nils Artiges & Simon Rouchier & Benoit Delinchant & Frédéric Wurtz, 2021. "Bayesian Inference of Dwellings Energy Signature at National Scale: Case of the French Residential Stock," Energies, MDPI, vol. 14(18), pages 1-26, September.
    7. Kleanthis Koupidis & Charalampos Bratsas & Christos Vlachokostas, 2022. "OpΕnergy: An Intelligent System for Monitoring EU Energy Strategy Using EU Open Data," Energies, MDPI, vol. 15(21), pages 1-15, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lowitzsch, J. & Hoicka, C.E. & van Tulder, F.J., 2020. "Renewable energy communities under the 2019 European Clean Energy Package – Governance model for the energy clusters of the future?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 122(C).
    2. Yigit Kazancoglu & Yalcin Berberoglu & Cisem Lafci & Oleksander Generalov & Denys Solohub & Viktor Koval, 2023. "Environmental Sustainability Implications and Economic Prosperity of Integrated Renewable Solutions in Urban Development," Energies, MDPI, vol. 16(24), pages 1-24, December.
    3. Gassar, Abdo Abdullah Ahmed & Cha, Seung Hyun, 2021. "Review of geographic information systems-based rooftop solar photovoltaic potential estimation approaches at urban scales," Applied Energy, Elsevier, vol. 291(C).
    4. Villa-Arrieta, Manuel & Sumper, Andreas, 2018. "A model for an economic evaluation of energy systems using TRNSYS," Applied Energy, Elsevier, vol. 215(C), pages 765-777.
    5. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    6. Sayegh, M.A. & Danielewicz, J. & Nannou, T. & Miniewicz, M. & Jadwiszczak, P. & Piekarska, K. & Jouhara, H., 2017. "Trends of European research and development in district heating technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P2), pages 1183-1192.
    7. Marcus Adolphson, 2010. "Kernel Densities and Mixed Functionality in a Multicentred Urban Region," Environment and Planning B, , vol. 37(3), pages 550-566, June.
    8. Changchun Feng & Hao Zhang & Liang Xiao & Yongpei Guo, 2022. "Land Use Change and Its Driving Factors in the Rural–Urban Fringe of Beijing: A Production–Living–Ecological Perspective," Land, MDPI, vol. 11(2), pages 1-18, February.
    9. 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.
    10. Stadler, M. & Groissböck, M. & Cardoso, G. & Marnay, C., 2014. "Optimizing Distributed Energy Resources and building retrofits with the strategic DER-CAModel," Applied Energy, Elsevier, vol. 132(C), pages 557-567.
    11. Aste, Niccolò & Del Pero, Claudio & Leonforte, Fabrizio & Manfren, Massimiliano, 2013. "A simplified model for the estimation of energy production of PV systems," Energy, Elsevier, vol. 59(C), pages 503-512.
    12. Theresa Liegl & Simon Schramm & Philipp Kuhn & Thomas Hamacher, 2023. "Considering Socio-Technical Parameters in Energy System Models—The Current Status and Next Steps," Energies, MDPI, vol. 16(20), pages 1-19, October.
    13. Yazdanie, Mashael & Densing, Martin & Wokaun, Alexander, 2017. "Cost optimal urban energy systems planning in the context of national energy policies: A case study for the city of Basel," Energy Policy, Elsevier, vol. 110(C), pages 176-190.
    14. Nutkiewicz, Alex & Yang, Zheng & Jain, Rishee K., 2018. "Data-driven Urban Energy Simulation (DUE-S): A framework for integrating engineering simulation and machine learning methods in a multi-scale urban energy modeling workflow," Applied Energy, Elsevier, vol. 225(C), pages 1176-1189.
    15. Hamdi-Cherif, Meriem & Waisman, Henri & Guivarch, Céline & Hourcade, Jean-Charles, 2012. "Mitigation costs in second-best economies: time profile of emission reductions and sequencing of accompanying measures," Conference papers 332206, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    16. Banister, David, 2011. "Cities, mobility and climate change," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1538-1546.
    17. Huang, Zishuo & Yu, Hang & Chu, Xiangyang & Peng, Zhenwei, 2017. "A goal programming based model system for community energy plan," Energy, Elsevier, vol. 134(C), pages 893-901.
    18. Juliane Große & Christian Fertner & Niels Boje Groth, 2016. "Urban Structure, Energy and Planning: Findings from Three Cities in Sweden, Finland and Estonia," Urban Planning, Cogitatio Press, vol. 1(1), pages 24-40.
    19. Yu Li & Ji Zheng & Fei Li & Xueting Jin & Chen Xu, 2017. "Assessment of municipal infrastructure development and its critical influencing factors in urban China: A FA and STIRPAT approach," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-14, August.
    20. Steinberger, Julia K. & van Niel, Johan & Bourg, Dominique, 2009. "Profiting from negawatts: Reducing absolute consumption and emissions through a performance-based energy economy," Energy Policy, Elsevier, vol. 37(1), pages 361-370, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:13:y:2020:i:5:p:1264-:d:330230. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.