IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v74y2014icp567-575.html
   My bibliography  Save this article

Micro-energy markets: The role of a consumer preference pricing strategy on microgrid energy investment

Author

Listed:
  • Faber, Isaac
  • Lane, William
  • Pak, Wayne
  • Prakel, Mary
  • Rocha, Cheyne
  • Farr, John V.

Abstract

The fragility of the modern electrical grid is exposed during random events such as storms, sporting events and often simply routine operation. Even with these obvious flaws large utilities and governments have been slow to create robust solutions due to the need of large capital investments required to address the issues. In this light creative economic and engineering solutions are desired to finance the needed upgrades. Driven by the requirement to have uninterrupted power that meets customers desires this research focuses on linking consumer preferences to a type of energy source in order to best fulfill stakeholder priorities. This approach is in contrast to the current and prevalent lowest cost methods to producing and consuming energy. This research yields a preliminary ‘micro-energy market’ that consists of an energy network architecture, pricing methodology and mathematical template which quantifies potential economic inefficiencies. If exploited these inefficiencies could be used to fund investment into various energy sources that provide unmet needs such as reduced carbon footprint, renewable, quality, and local production. These inefficiencies can be best exploited within the structure of a microgrid. Identification of opportunities on this smaller scale can provide an incentive for producers to develop a robust set of production facilities of varying size and characteristics to meet the consumer preferences. A stochastic optimization model of a microgrid implementation for a small military installation is used to evaluate the effects of this pricing methodology. The energy production of the resulting microgrid would be optimized to meet consumer preferences and minimize economic inefficiency.

Suggested Citation

  • Faber, Isaac & Lane, William & Pak, Wayne & Prakel, Mary & Rocha, Cheyne & Farr, John V., 2014. "Micro-energy markets: The role of a consumer preference pricing strategy on microgrid energy investment," Energy, Elsevier, vol. 74(C), pages 567-575.
    • Handle: RePEc:eee:energy:v:74:y:2014:i:c:p:567-575
    DOI: 10.1016/j.energy.2014.07.022
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544214008445
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2014.07.022?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. Aldy, Joseph Edgar & Leiserowitz, Anthony A & Kotchen, Matthew J, 2012. "Willingness to Pay and Political Support for a U.S. National Clean Energy Standard," Scholarly Articles 8832942, Harvard Kennedy School of Government.
    2. Hasan, Kazi Nazmul & Saha, Tapan Kumar & Eghbal, Mehdi, 2014. "Investigating the priority of market participants for low emission generation entry into the Australian grid," Energy, Elsevier, vol. 71(C), pages 445-455.
    3. Joseph E. Aldy & Matthew J. Kotchen & Anthony A. Leiserowitz, 2012. "Willingness to pay and political support for a US national clean energy standard," Nature Climate Change, Nature, vol. 2(8), pages 596-599, August.
    4. Kopsakangas Savolainen, Maria & Svento, Rauli, 2012. "Real-Time Pricing in the Nordic Power markets," Energy Economics, Elsevier, vol. 34(4), pages 1131-1142.
    5. Doostizadeh, Meysam & Ghasemi, Hassan, 2012. "A day-ahead electricity pricing model based on smart metering and demand-side management," Energy, Elsevier, vol. 46(1), pages 221-230.
    6. Shin, Jungwoo & Woo, JongRoul & Huh, Sung-Yoon & Lee, Jongsu & Jeong, Gicheol, 2014. "Analyzing public preferences and increasing acceptability for the Renewable Portfolio Standard in Korea," Energy Economics, Elsevier, vol. 42(C), pages 17-26.
    7. Lee, Mitchell & Soto, Daniel & Modi, Vijay, 2014. "Cost versus reliability sizing strategy for isolated photovoltaic micro-grids in the developing world," Renewable Energy, Elsevier, vol. 69(C), pages 16-24.
    8. Severin Borenstein, 2005. "The Long-Run Efficiency of Real-Time Electricity Pricing," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 93-116.
    9. Faria, P. & Vale, Z., 2011. "Demand response in electrical energy supply: An optimal real time pricing approach," Energy, Elsevier, vol. 36(8), pages 5374-5384.
    10. Quiggin, Daniel & Cornell, Sarah & Tierney, Michael & Buswell, Richard, 2012. "A simulation and optimisation study: Towards a decentralised microgrid, using real world fluctuation data," Energy, Elsevier, vol. 41(1), pages 549-559.
    11. F J Nogales & A J Conejo, 2006. "Electricity price forecasting through transfer function models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(4), pages 350-356, April.
    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. Wang, Richard & Hsu, Shu-Chien & Zheng, Saina & Chen, Jieh-Haur & Li, Xuran Ivan, 2020. "Renewable energy microgrids: Economic evaluation and decision making for government policies to contribute to affordable and clean energy," Applied Energy, Elsevier, vol. 274(C).
    2. Whei-Min Lin & Chia-Sheng Tu & Ming-Tang Tsai, 2015. "Energy Management Strategy for Microgrids by Using Enhanced Bee Colony Optimization," Energies, MDPI, vol. 9(1), pages 1-16, December.
    3. Pau Lloret-Gallego & Mònica Aragüés-Peñalba & Lien Van Schepdael & Eduard Bullich-Massagué & Pol Olivella-Rosell & Andreas Sumper, 2017. "Methodology for the Evaluation of Resilience of ICT Systems for Smart Distribution Grids," Energies, MDPI, vol. 10(9), pages 1-16, August.
    4. Whei-Min Lin & Chung-Yuen Yang & Chia-Sheng Tu & Ming-Tang Tsai, 2018. "An Optimal Scheduling Dispatch of a Microgrid under Risk Assessment," Energies, MDPI, vol. 11(6), pages 1-17, June.
    5. Yong Long & Yu Wang & Chengrong Pan, 2018. "Incentive Mechanism of Micro-grid Project Development," Sustainability, MDPI, vol. 10(1), pages 1-19, January.
    6. Sousa, Tiago & Soares, Tiago & Pinson, Pierre & Moret, Fabio & Baroche, Thomas & Sorin, Etienne, 2019. "Peer-to-peer and community-based markets: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 367-378.
    7. Tabar, Vahid Sohrabi & Jirdehi, Mehdi Ahmadi & Hemmati, Reza, 2017. "Energy management in microgrid based on the multi objective stochastic programming incorporating portable renewable energy resource as demand response option," Energy, Elsevier, vol. 118(C), pages 827-839.

    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. Taylan G. Topcu & Konstantinos Triantis, 2022. "An ex-ante DEA method for representing contextual uncertainties and stakeholder risk preferences," Annals of Operations Research, Springer, vol. 309(1), pages 395-423, February.
    2. Rhodes, Ekaterina & Scott, William A. & Jaccard, Mark, 2021. "Designing flexible regulations to mitigate climate change: A cross-country comparative policy analysis," Energy Policy, Elsevier, vol. 156(C).
    3. Jin, Ming & Feng, Wei & Marnay, Chris & Spanos, Costas, 2018. "Microgrid to enable optimal distributed energy retail and end-user demand response," Applied Energy, Elsevier, vol. 210(C), pages 1321-1335.
    4. Kruse, Tobias & Atkinson, Giles, 2022. "Understanding public support for international climate adaptation payments: Evidence from a choice experiment," Ecological Economics, Elsevier, vol. 194(C).
    5. Mattias Vesterberg and Chandra Kiran B. Krishnamurthy, 2016. "Residential End-use Electricity Demand: Implications for Real Time Pricing in Sweden," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    6. L. Mundaca & H. Moncreiff, 2021. "New Perspectives on Green Energy Defaults," Journal of Consumer Policy, Springer, vol. 44(3), pages 357-383, September.
    7. Li, Xiao Hui & Hong, Seung Ho, 2014. "User-expected price-based demand response algorithm for a home-to-grid system," Energy, Elsevier, vol. 64(C), pages 437-449.
    8. Jarke-Neuert, Johannes & Perino, Grischa & Schwickert, Henrike, 2021. "Free-Riding for Future: Field Experimental Evidence of Strategic Substitutability in Climate Protest," SocArXiv sh6dm, Center for Open Science.
    9. Jens Abildtrup & Jette Bredahl Jacobsen & Suzanne Elizabeth Vedel & Udo Mantau & Robert Mavsar & Davide Pettenella & Irina Prokofieva & Florian Schubert & Anne Stenger & Elsa Varela & Enrico Vidale & , 2024. "Preferences for climate change policies: the role of co-benefits," Journal of Environmental Economics and Policy, Taylor & Francis Journals, vol. 13(1), pages 110-128, January.
    10. Bigerna, Simona & Hagspiel, Verena & Kort, Peter M. & Wen, Xingang, 2023. "How damaging are environmental policy targets in terms of welfare?," European Journal of Operational Research, Elsevier, vol. 311(1), pages 354-372.
    11. Zhang, Yunchao & Islam, Md Monirul & Sun, Zeyi & Yang, Sijia & Dagli, Cihan & Xiong, Haoyi, 2018. "Optimal sizing and planning of onsite generation system for manufacturing in Critical Peaking Pricing demand response program," International Journal of Production Economics, Elsevier, vol. 206(C), pages 261-267.
    12. Sundt, Swantje & Rehdanz, Katrin, 2015. "Consumers' willingness to pay for green electricity: A meta-analysis of the literature," Energy Economics, Elsevier, vol. 51(C), pages 1-8.
    13. Wang, Yong & Li, Lin, 2015. "Time-of-use electricity pricing for industrial customers: A survey of U.S. utilities," Applied Energy, Elsevier, vol. 149(C), pages 89-103.
    14. Perlaviciute, Goda & Steg, Linda, 2014. "Contextual and psychological factors shaping evaluations and acceptability of energy alternatives: Integrated review and research agenda," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 361-381.
    15. Katz, Jonas & Andersen, Frits Møller & Morthorst, Poul Erik, 2016. "Load-shift incentives for household demand response: Evaluation of hourly dynamic pricing and rebate schemes in a wind-based electricity system," Energy, Elsevier, vol. 115(P3), pages 1602-1616.
    16. Aklin, Michaël & Bayer, Patrick & Harish, S.P. & Urpelainen, Johannes, 2013. "Understanding environmental policy preferences: New evidence from Brazil," Ecological Economics, Elsevier, vol. 94(C), pages 28-36.
    17. Tvinnereim, Endre & Ivarsflaten, Elisabeth, 2016. "Fossil fuels, employment, and support for climate policies," Energy Policy, Elsevier, vol. 96(C), pages 364-371.
    18. Yu, Ying & Yamaguchi, Kensuke & Thuy, Truong Dang & Kittner, Noah, 2022. "Will the public in emerging economies support renewable energy? Evidence from Ho Chi Minh City, Vietnam," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    19. Hong, Seung Ho & Kim, Se Hwan & Kim, Gi Myung & Kim, Hyung Lae, 2014. "Experimental evaluation of BZ-GW (BACnet-ZigBee smart grid gateway) for demand response in buildings," Energy, Elsevier, vol. 65(C), pages 62-70.
    20. Boßmann, Tobias & Eser, Eike Johannes, 2016. "Model-based assessment of demand-response measures—A comprehensive literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1637-1656.

    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:energy:v:74:y:2014:i:c:p:567-575. 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.journals.elsevier.com/energy .

    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.