IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v62y2013icp617-624.html
   My bibliography  Save this article

Drivers, trends, and uncertainty in long-term price projections for energy management in public buildings

Author

Abstract

Buildings are responsible for almost 40% of energy consumption and CO2 emissions in the EU (EC, 2010). Improving the energy efficiency of buildings is a vital step towards achieving the EU climate and energy objectives. Directive 2010/31/EU outlines measures specifically focused on the energy performance of buildings. Incentives are created for building operators to optimize their energy sub-systems in a more robust, energy-efficient, and cost-effective manner. The challenge is to choose efficient energy-supply portfolios accounting for technological and market deregulation and risks. Decision support tools for energy management in public buildings using future scenarios of market and technological developments would be beneficial. The aim of this paper is to discuss the drivers and uncertainties in the recent and future energy market trends and prices, including technological progress and developments in fossil-fuel markets. This discussion is relevant for researchers and policymakers in general, and in particular, as an input for scenarios used in the development of decision support systems.

Suggested Citation

  • Egging, Ruud, 2013. "Drivers, trends, and uncertainty in long-term price projections for energy management in public buildings," Energy Policy, Elsevier, vol. 62(C), pages 617-624.
    • Handle: RePEc:eee:enepol:v:62:y:2013:i:c:p:617-624
    DOI: 10.1016/j.enpol.2013.07.022
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421513006654
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.enpol.2013.07.022?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Andrews, Clinton J. & Krogmann, Uta, 2009. "Technology diffusion and energy intensity in US commercial buildings," Energy Policy, Elsevier, vol. 37(2), pages 541-553, February.
    2. McDonald, Alan & Schrattenholzer, Leo, 2001. "Learning rates for energy technologies," Energy Policy, Elsevier, vol. 29(4), pages 255-261, March.
    3. Atkinson, Jonathan G.B. & Jackson, Tim & Mullings-Smith, Elizabeth, 2009. "Market influence on the low carbon energy refurbishment of existing multi-residential buildings," Energy Policy, Elsevier, vol. 37(7), pages 2582-2593, July.
    4. Graus, Wina & Worrell, Ernst, 2009. "Trend in efficiency and capacity of fossil power generation in the EU," Energy Policy, Elsevier, vol. 37(6), pages 2147-2160, June.
    5. Jamasb, T. & Köhler, J., 2007. "Learning Curves For Energy Technology and Policy Analysis: A Critical Assessment," Cambridge Working Papers in Economics 0752, Faculty of Economics, University of Cambridge.
    6. Dai, Xuezhi & Wu, Yong & Di, Yanqiang & Li, Qiaoyan, 2009. "Government regulation and associated innovations in building energy-efficiency supervisory systems for large-scale public buildings in a market economy," Energy Policy, Elsevier, vol. 37(6), pages 2073-2078, June.
    7. Ryghaug, Marianne & Sørensen, Knut H., 2009. "How energy efficiency fails in the building industry," Energy Policy, Elsevier, vol. 37(3), pages 984-991, March.
    8. Weigt, Hannes & Hirschhausen, Christian von, 2008. "Price formation and market power in the German wholesale electricity market in 2006," Energy Policy, Elsevier, vol. 36(11), pages 4227-4234, November.
    9. Sagar, Ambuj D. & van der Zwaan, Bob, 2006. "Technological innovation in the energy sector: R&D, deployment, and learning-by-doing," Energy Policy, Elsevier, vol. 34(17), pages 2601-2608, November.
    10. Grossman, Sanford J & Hart, Oliver D, 1983. "An Analysis of the Principal-Agent Problem," Econometrica, Econometric Society, vol. 51(1), pages 7-45, January.
    11. Graus, W.H.J. & Voogt, M. & Worrell, E., 2007. "International comparison of energy efficiency of fossil power generation," Energy Policy, Elsevier, vol. 35(7), pages 3936-3951, July.
    12. Yan-ping, Feng & Yong, Wu & Chang-bin, Liu, 2009. "Energy-efficiency supervision systems for energy management in large public buildings: Necessary choice for China," Energy Policy, Elsevier, vol. 37(6), pages 2060-2065, June.
    13. Weigt, Hannes, 2009. "Germany's wind energy: The potential for fossil capacity replacement and cost saving," Applied Energy, Elsevier, vol. 86(10), pages 1857-1863, October.
    14. Cai, W.G. & Wu, Y. & Zhong, Y. & Ren, H., 2009. "China building energy consumption: Situation, challenges and corresponding measures," Energy Policy, Elsevier, vol. 37(6), pages 2054-2059, June.
    15. Jin, Zhenxing & Wu, Yong & Li, Baizhan & Gao, Yafeng, 2009. "Energy efficiency supervision strategy selection of Chinese large-scale public buildings," Energy Policy, Elsevier, vol. 37(6), pages 2066-2072, June.
    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. Copiello, Sergio, 2017. "Building energy efficiency: A research branch made of paradoxes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1064-1076.
    2. Ebru Hancioglu Kuzgunkaya, 2019. "Energy performance assessment in terms of primary energy and exergy analyses of the nursing home and rehabilitation center," Energy & Environment, , vol. 30(8), pages 1506-1520, December.

    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. Liu, Pei & Pistikopoulos, Efstratios N. & Li, Zheng, 2010. "An energy systems engineering approach to the optimal design of energy systems in commercial buildings," Energy Policy, Elsevier, vol. 38(8), pages 4224-4231, August.
    2. Hanee Ryu & Hyejae Jung, 2021. "Impact of public R&D as market matures: Evidence from solar PV industry," Energy & Environment, , vol. 32(8), pages 1543-1558, December.
    3. Eunji Kim & Yoonhee Ha, 2021. "Vitalization Strategies for the Building Energy Management System (BEMS) Industry Ecosystem Based on AHP Analysis," Energies, MDPI, vol. 14(9), pages 1-16, April.
    4. Arias-Gaviria, Jessica & van der Zwaan, Bob & Kober, Tom & Arango-Aramburo, Santiago, 2017. "The prospects for Small Hydropower in Colombia," Renewable Energy, Elsevier, vol. 107(C), pages 204-214.
    5. Ebru Hancioglu Kuzgunkaya, 2019. "Energy performance assessment in terms of primary energy and exergy analyses of the nursing home and rehabilitation center," Energy & Environment, , vol. 30(8), pages 1506-1520, December.
    6. Elia, A. & Kamidelivand, M. & Rogan, F. & Ó Gallachóir, B., 2021. "Impacts of innovation on renewable energy technology cost reductions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    7. Hayward, Jennifer A. & Graham, Paul W., 2013. "A global and local endogenous experience curve model for projecting future uptake and cost of electricity generation technologies," Energy Economics, Elsevier, vol. 40(C), pages 537-548.
    8. Singh, Anuraag & Triulzi, Giorgio & Magee, Christopher L., 2021. "Technological improvement rate predictions for all technologies: Use of patent data and an extended domain description," Research Policy, Elsevier, vol. 50(9).
    9. Harborne, Paul & Hendry, Chris, 2009. "Pathways to commercial wind power in the US, Europe and Japan: The role of demonstration projects and field trials in the innovation process," Energy Policy, Elsevier, vol. 37(9), pages 3580-3595, September.
    10. Kukkikatte Ramamurthy Rao, Harshadeep & Gemechu, Eskinder & Thakur, Ujwal & Shankar, Karthik & Kumar, Amit, 2021. "Techno-economic assessment of titanium dioxide nanorod-based perovskite solar cells: From lab-scale to large-scale manufacturing," Applied Energy, Elsevier, vol. 298(C).
    11. Graus, Wina & Worrell, Ernst, 2011. "Methods for calculating CO2 intensity of power generation and consumption: A global perspective," Energy Policy, Elsevier, vol. 39(2), pages 613-627, February.
    12. Seyedmohammadreza Heibati & Wahid Maref & Hamed H. Saber, 2019. "Assessing the Energy and Indoor Air Quality Performance for a Three-Story Building Using an Integrated Model, Part One: The Need for Integration," Energies, MDPI, vol. 12(24), pages 1-18, December.
    13. Chang, Yu Sang, 2014. "Comparative analysis of long-term road fatality targets for individual states in the US—An application of experience curve models," Transport Policy, Elsevier, vol. 36(C), pages 53-69.
    14. Upstill, Garrett & Hall, Peter, 2018. "Estimating the learning rate of a technology with multiple variants: The case of carbon storage," Energy Policy, Elsevier, vol. 121(C), pages 498-505.
    15. Lohwasser, Richard & Madlener, Reinhard, 2013. "Relating R&D and investment policies to CCS market diffusion through two-factor learning," Energy Policy, Elsevier, vol. 52(C), pages 439-452.
    16. Zhang, Jiefeng & Bai, Zhipeng & Chang, Victor W.C. & Ding, Xiao, 2011. "Balancing BEC and IAQ in civil buildings during rapid urbanization in China: Regulation, interplay and collaboration," Energy Policy, Elsevier, vol. 39(10), pages 5778-5790, October.
    17. Yu Sang Chang & Dosoung Choi & Hann Earl Kim, 2017. "Dynamic Trends of Carbon Intensities among 127 Countries," Sustainability, MDPI, vol. 9(12), pages 1-21, December.
    18. Lin, Boqiang & Sai, Rockson, 2021. "A multi factor Malmquist CO2emission performance indices: Evidence from Sub Saharan African public thermal power plants," Energy, Elsevier, vol. 223(C).
    19. Kim, Seunghyok & Koo, Jamin & Lee, Chang Jun & Yoon, En Sup, 2012. "Optimization of Korean energy planning for sustainability considering uncertainties in learning rates and external factors," Energy, Elsevier, vol. 44(1), pages 126-134.
    20. Williams, Eric & Hittinger, Eric & Carvalho, Rexon & Williams, Ryan, 2017. "Wind power costs expected to decrease due to technological progress," Energy Policy, Elsevier, vol. 106(C), pages 427-435.

    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:eee:enepol:v:62:y:2013:i:c:p:617-624. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

    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.