IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i9p2164-d353151.html
   My bibliography  Save this article

Effect of Heat Demand on Integration of Urban Large-Scale Renewable Schemes—Case of Helsinki City (60 °N)

Author

Listed:
  • Vahid Arabzadeh

    (New Energy Technologies Group, School of Science, Aalto University, P.O. Box 15100, FI-00076 Aalto, 02150 Espoo, Finland)

  • Peter D. Lund

    (New Energy Technologies Group, School of Science, Aalto University, P.O. Box 15100, FI-00076 Aalto, 02150 Espoo, Finland)

Abstract

Heat demand dominates the final energy use in northern cities. This study examines how changes in heat demand may affect solutions for zero-emission energy systems, energy system flexibility with variable renewable electricity production, and the use of existing energy systems for deep decarbonization. Helsinki city (60 °N) in the year 2050 is used as a case for the analysis. The future district heating demand is estimated considering activity-driven factors such as population increase, raising the ambient temperature, and building energy efficiency improvements. The effect of the heat demand on energy system transition is investigated through two scenarios. The BIO-GAS scenario employs emission-free gas technologies, bio-boilers and heat pumps. The WIND scenario is based on large-scale wind power with power-to-heat conversion, heat pumps, and bio-boilers. The BIO-GAS scenario combined with a low heat demand profile (−12% from 2018 level) yields 16% lower yearly costs compared to a business-as-usual higher heat demand. In the WIND-scenario, improving the lower heat demand in 2050 could save the annual system 6–13% in terms of cost, depending on the scale of wind power.

Suggested Citation

  • Vahid Arabzadeh & Peter D. Lund, 2020. "Effect of Heat Demand on Integration of Urban Large-Scale Renewable Schemes—Case of Helsinki City (60 °N)," Energies, MDPI, vol. 13(9), pages 1-17, May.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:9:p:2164-:d:353151
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/9/2164/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/9/2164/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kirkerud, Jon Gustav & Bolkesjø, Torjus Folsland & Trømborg, Erik, 2017. "Power-to-heat as a flexibility measure for integration of renewable energy," Energy, Elsevier, vol. 128(C), pages 776-784.
    2. Cheng Zhou & Jianyong Zheng & Sai Liu & Yu Liu & Fei Mei & Yi Pan & Tian Shi & Jianzhang Wu, 2019. "Operation Optimization of Multi-District Integrated Energy System Considering Flexible Demand Response of Electric and Thermal Loads," Energies, MDPI, vol. 12(20), pages 1-26, October.
    3. Calikus, Ece & Nowaczyk, Sławomir & Sant'Anna, Anita & Gadd, Henrik & Werner, Sven, 2019. "A data-driven approach for discovering heat load patterns in district heating," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    4. Suryanarayana, Gowri & Lago, Jesus & Geysen, Davy & Aleksiejuk, Piotr & Johansson, Christian, 2018. "Thermal load forecasting in district heating networks using deep learning and advanced feature selection methods," Energy, Elsevier, vol. 157(C), pages 141-149.
    5. Sandberg, Eli & Sneum, Daniel Møller & Trømborg, Erik, 2018. "Framework conditions for Nordic district heating - Similarities and differences, and why Norway sticks out," Energy, Elsevier, vol. 149(C), pages 105-119.
    6. Finck, Christian & Li, Rongling & Kramer, Rick & Zeiler, Wim, 2018. "Quantifying demand flexibility of power-to-heat and thermal energy storage in the control of building heating systems," Applied Energy, Elsevier, vol. 209(C), pages 409-425.
    7. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2017. "Decarbonizing the electricity grid: The impact on urban energy systems, distribution grids and district heating potential," Applied Energy, Elsevier, vol. 191(C), pages 125-140.
    8. Fang, Tingting & Lahdelma, Risto, 2016. "Evaluation of a multiple linear regression model and SARIMA model in forecasting heat demand for district heating system," Applied Energy, Elsevier, vol. 179(C), pages 544-552.
    9. Fang, Tingting & Lahdelma, Risto, 2015. "Genetic optimization of multi-plant heat production in district heating networks," Applied Energy, Elsevier, vol. 159(C), pages 610-619.
    10. Cao, Karl-Kiên & Nitto, Alejandro Nicolás & Sperber, Evelyn & Thess, André, 2018. "Expanding the horizons of power-to-heat: Cost assessment for new space heating concepts with Wind Powered Thermal Energy Systems," Energy, Elsevier, vol. 164(C), pages 925-936.
    11. Amundsen, Eirik S. & Bergman, Lars, 2006. "Why has the Nordic electricity market worked so well?," Utilities Policy, Elsevier, vol. 14(3), pages 148-157, September.
    12. Arnaudo, Monica & Topel, Monika & Puerto, Pablo & Widl, Edmund & Laumert, Björn, 2019. "Heat demand peak shaving in urban integrated energy systems by demand side management - A techno-economic and environmental approach," Energy, Elsevier, vol. 186(C).
    13. Askeland, Kristine & Bozhkova, Kristina N. & Sorknæs, Peter, 2019. "Balancing Europe: Can district heating affect the flexibility potential of Norwegian hydropower resources?," Renewable Energy, Elsevier, vol. 141(C), pages 646-656.
    14. Sannamari Pilpola & Vahid Arabzadeh & Jani Mikkola & Peter D. Lund, 2019. "Analyzing National and Local Pathways to Carbon-Neutrality from Technology, Emissions, and Resilience Perspectives—Case of Finland," Energies, MDPI, vol. 12(5), pages 1-22, March.
    15. Sovacool, Benjamin K., 2017. "Contestation, contingency, and justice in the Nordic low-carbon energy transition," Energy Policy, Elsevier, vol. 102(C), pages 569-582.
    16. Rinne, S. & Syri, S., 2015. "The possibilities of combined heat and power production balancing large amounts of wind power in Finland," Energy, Elsevier, vol. 82(C), pages 1034-1046.
    17. Dotzauer, Erik, 2002. "Simple model for prediction of loads in district-heating systems," Applied Energy, Elsevier, vol. 73(3-4), pages 277-284, November.
    18. Pilpola, Sannamari & Lund, Peter D., 2018. "Effect of major policy disruptions in energy system transition: Case Finland," Energy Policy, Elsevier, vol. 116(C), pages 323-336.
    19. Hellström, Jörgen & Lundgren, Jens & Yu, Haishan, 2012. "Why do electricity prices jump? Empirical evidence from the Nordic electricity market," Energy Economics, Elsevier, vol. 34(6), pages 1774-1781.
    20. Lundström, Lukas & Wallin, Fredrik, 2016. "Heat demand profiles of energy conservation measures in buildings and their impact on a district heating system," Applied Energy, Elsevier, vol. 161(C), pages 290-299.
    21. Mikkola, Jani & Lund, Peter D., 2016. "Modeling flexibility and optimal use of existing power plants with large-scale variable renewable power schemes," Energy, Elsevier, vol. 112(C), pages 364-375.
    22. Bolwig, Simon & Bazbauers, Gatis & Klitkou, Antje & Lund, Peter D. & Blumberga, Andra & Gravelsins, Armands & Blumberga, Dagnija, 2019. "Review of modelling energy transitions pathways with application to energy system flexibility," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 440-452.
    23. Nigitz, Thomas & Gölles, Markus, 2019. "A generally applicable, simple and adaptive forecasting method for the short-term heat load of consumers," Applied Energy, Elsevier, vol. 241(C), pages 73-81.
    24. An, Jingjing & Yan, Da & Hong, Tianzhen & Sun, Kaiyu, 2017. "A novel stochastic modeling method to simulate cooling loads in residential districts," Applied Energy, Elsevier, vol. 206(C), pages 134-149.
    25. Zihao Li & Daniel Friedrich & Gareth P. Harrison, 2020. "Demand Forecasting for a Mixed-Use Building Using Agent-Schedule Information with a Data-Driven Model," Energies, MDPI, vol. 13(4), pages 1-20, February.
    26. Hedegaard, Karsten & Mathiesen, Brian Vad & Lund, Henrik & Heiselberg, Per, 2012. "Wind power integration using individual heat pumps – Analysis of different heat storage options," Energy, Elsevier, vol. 47(1), pages 284-293.
    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. Gil-García, Isabel C. & Fernández-Guillamón, Ana & García-Cascales, M. Socorro & Molina-García, Angel & Dagher, Habib, 2024. "A green electrical matrix-based model for the energy transition: Maine, USA case example," Energy, Elsevier, vol. 290(C).
    2. Lindroos, Tomi J. & Mäki, Elina & Koponen, Kati & Hannula, Ilkka & Kiviluoma, Juha & Raitila, Jyrki, 2021. "Replacing fossil fuels with bioenergy in district heating – Comparison of technology options," Energy, Elsevier, vol. 231(C).
    3. Arabzadeh, Vahid & Miettinen, Panu & Kotilainen, Titta & Herranen, Pasi & Karakoc, Alp & Kummu, Matti & Rautkari, Lauri, 2023. "Urban vertical farming with a large wind power share and optimised electricity costs," Applied Energy, Elsevier, vol. 331(C).
    4. Ieva Pakere & Dace Lauka & Dagnija Blumberga, 2020. "Does the Balance Exist between Cost Efficiency of Different Energy Efficiency Measures? DH Systems Case," Energies, MDPI, vol. 13(19), pages 1-16, October.

    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. Golmohamadi, Hessam & Larsen, Kim Guldstrand & Jensen, Peter Gjøl & Hasrat, Imran Riaz, 2022. "Integration of flexibility potentials of district heating systems into electricity markets: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    2. Maciej Bujalski & Paweł Madejski, 2021. "Forecasting of Heat Production in Combined Heat and Power Plants Using Generalized Additive Models," Energies, MDPI, vol. 14(8), pages 1-15, April.
    3. Peter D. Lund & Klaus Skytte & Simon Bolwig & Torjus Folsland Bolkesjö & Claire Bergaentzlé & Philipp Andreas Gunkel & Jon Gustav Kirkerud & Antje Klitkou & Hardi Koduvere & Armands Gravelsins & Dagni, 2019. "Pathway Analysis of a Zero-Emission Transition in the Nordic-Baltic Region," Energies, MDPI, vol. 12(17), pages 1-20, August.
    4. Yuan, Jianjuan & Zhou, Zhihua & Tang, Huajie & Wang, Chendong & Lu, Shilei & Han, Zhao & Zhang, Ji & Sheng, Ying, 2020. "Identification heat user behavior for improving the accuracy of heating load prediction model based on wireless on-off control system," Energy, Elsevier, vol. 199(C).
    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. Ma, Weiwu & Fang, Song & Liu, Gang & Zhou, Ruoyu, 2017. "Modeling of district load forecasting for distributed energy system," Applied Energy, Elsevier, vol. 204(C), pages 181-205.
    7. Sannamari Pilpola & Vahid Arabzadeh & Jani Mikkola & Peter D. Lund, 2019. "Analyzing National and Local Pathways to Carbon-Neutrality from Technology, Emissions, and Resilience Perspectives—Case of Finland," Energies, MDPI, vol. 12(5), pages 1-22, March.
    8. Saletti, Costanza & Zimmerman, Nathan & Morini, Mirko & Kyprianidis, Konstantinos & Gambarotta, Agostino, 2021. "Enabling smart control by optimally managing the State of Charge of district heating networks," Applied Energy, Elsevier, vol. 283(C).
    9. Arabzadeh, Vahid & Miettinen, Panu & Kotilainen, Titta & Herranen, Pasi & Karakoc, Alp & Kummu, Matti & Rautkari, Lauri, 2023. "Urban vertical farming with a large wind power share and optimised electricity costs," Applied Energy, Elsevier, vol. 331(C).
    10. Dahl, Magnus & Brun, Adam & Andresen, Gorm B., 2017. "Using ensemble weather predictions in district heating operation and load forecasting," Applied Energy, Elsevier, vol. 193(C), pages 455-465.
    11. Xue, Puning & Jiang, Yi & Zhou, Zhigang & Chen, Xin & Fang, Xiumu & Liu, Jing, 2019. "Multi-step ahead forecasting of heat load in district heating systems using machine learning algorithms," Energy, Elsevier, vol. 188(C).
    12. Pilpola, Sannamari & Lund, Peter D., 2020. "Analyzing the effects of uncertainties on the modelling of low-carbon energy system pathways," Energy, Elsevier, vol. 201(C).
    13. Triebs, Merlin Sebastian & Tsatsaronis, George, 2022. "From heat demand to heat supply: How to obtain more accurate feed-in time series for district heating systems," Applied Energy, Elsevier, vol. 311(C).
    14. Sandberg, Eli & Kirkerud, Jon Gustav & Trømborg, Erik & Bolkesjø, Torjus Folsland, 2019. "Energy system impacts of grid tariff structures for flexible power-to-district heat," Energy, Elsevier, vol. 168(C), pages 772-781.
    15. Aunedi, Marko & Pantaleo, Antonio Marco & Kuriyan, Kamal & Strbac, Goran & Shah, Nilay, 2020. "Modelling of national and local interactions between heat and electricity networks in low-carbon energy systems," Applied Energy, Elsevier, vol. 276(C).
    16. Wang, Yang & Zhang, Shanhong & Chow, David & Kuckelkorn, Jens M., 2021. "Evaluation and optimization of district energy network performance: Present and future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    17. Magnus Dahl & Adam Brun & Oliver S. Kirsebom & Gorm B. Andresen, 2018. "Improving Short-Term Heat Load Forecasts with Calendar and Holiday Data," Energies, MDPI, vol. 11(7), pages 1-16, June.
    18. Xue, Puning & Zhou, Zhigang & Fang, Xiumu & Chen, Xin & Liu, Lin & Liu, Yaowen & Liu, Jing, 2017. "Fault detection and operation optimization in district heating substations based on data mining techniques," Applied Energy, Elsevier, vol. 205(C), pages 926-940.
    19. Ahmad, Tanveer & Chen, Huanxin, 2019. "Deep learning for multi-scale smart energy forecasting," Energy, Elsevier, vol. 175(C), pages 98-112.
    20. Gong, Mingju & Zhao, Yin & Sun, Jiawang & Han, Cuitian & Sun, Guannan & Yan, Bo, 2022. "Load forecasting of district heating system based on Informer," Energy, Elsevier, vol. 253(C).

    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:9:p:2164-:d:353151. 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.