IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v119y2014icp141-150.html
   My bibliography  Save this article

Locational marginal emissions: Analysis of pollutant emission reduction through spatial management of load distribution

Author

Listed:
  • Wang, Y.
  • Wang, C.
  • Miller, C.J.
  • McElmurry, S.P.
  • Miller, S.S.
  • Rogers, M.M.

Abstract

Environmental concerns associated with power generation drive an increasing interest in developing load management strategies to reduce pollutant emissions. Currently, no mechanism exists to directly influence pollutant emissions based on demand-side decisions. This shortcoming is addressed through the exploration of an alternative load distribution management paradigm based on the use of locational marginal emissions (LMEs). LMEs present a novel mechanism for optimizing load based on pollutant emissions. To demonstrate the application of LMEs, simulation studies using the IEEE 14-bus system and a large regional transmission system in the US (PJM) were performed and changes in CO2, SO2, and NOx emissions were quantified for varying levels of spatial load flexibility. The simulation results confirm that the proposed LME-based load management method is effective in reducing pollutant emissions in comparison to the traditional economic load distribution management method based on the locational marginal price (LMP). Emission reductions were found to become more significant as the proportion of spatially controllable loads increased. Adoption of LMEs by independent system operators (ISOs) or Regional Transmission Organizations (RTOs) would empower demand-side clients to reduce pollutant emissions based on their own load management decisions and enhance the sustainability of free-market power systems. Alternately, the LME management scheme could be automated by utilities through connections to Smart Grid compatible appliances.

Suggested Citation

  • Wang, Y. & Wang, C. & Miller, C.J. & McElmurry, S.P. & Miller, S.S. & Rogers, M.M., 2014. "Locational marginal emissions: Analysis of pollutant emission reduction through spatial management of load distribution," Applied Energy, Elsevier, vol. 119(C), pages 141-150.
    • Handle: RePEc:eee:appene:v:119:y:2014:i:c:p:141-150
    DOI: 10.1016/j.apenergy.2013.12.052
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261913010611
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2013.12.052?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. Rogers, Michelle M. & Wang, Yang & Wang, Caisheng & McElmurry, Shawn P. & Miller, Carol J., 2013. "Evaluation of a rapid LMP-based approach for calculating marginal unit emissions," Applied Energy, Elsevier, vol. 111(C), pages 812-820.
    2. Stephen P. Holland & Erin T. Mansur, 2008. "Is Real-Time Pricing Green? The Environmental Impacts of Electricity Demand Variance," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 550-561, August.
    3. ., 2013. "Auction theory and collusion," Chapters, in: Cartels, Competition and Public Procurement, chapter 4, pages 36-62, Edward Elgar Publishing.
    4. Liao, Gwo-Ching, 2011. "A novel evolutionary algorithm for dynamic economic dispatch with energy saving and emission reduction in power system integrated wind power," Energy, Elsevier, vol. 36(2), pages 1018-1029.
    5. ., 2013. "Application of auction theory in China," Chapters, in: Cartels, Competition and Public Procurement, chapter 8, pages 128-136, Edward Elgar Publishing.
    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. Hu, Tingli & Wang, Caisheng & Miller, Carol, 2021. "Identification of marginal generation units based on publicly available information," Applied Energy, Elsevier, vol. 281(C).
    2. Park, Byungkwon & Dong, Jin & Liu, Boming & Kuruganti, Teja, 2023. "Decarbonizing the grid: Utilizing demand-side flexibility for carbon emission reduction through locational marginal emissions in distribution networks," Applied Energy, Elsevier, vol. 330(PA).
    3. Lara J. Treemore-Spears & J. Morgan Grove & Craig K. Harris & Lawrence D. Lemke & Carol J. Miller & Kami Pothukuchi & Yifan Zhang & Yongli L. Zhang, 2016. "A workshop on transitioning cities at the food-energy-water nexus," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 6(1), pages 90-103, March.
    4. Bigazzi, Alexander, 2019. "Comparison of marginal and average emission factors for passenger transportation modes," Applied Energy, Elsevier, vol. 242(C), pages 1460-1466.
    5. Harris, A.R. & Rogers, Michelle Marinich & Miller, Carol J. & McElmurry, Shawn P. & Wang, Caisheng, 2015. "Residential emissions reductions through variable timing of electricity consumption," Applied Energy, Elsevier, vol. 158(C), pages 484-489.
    6. Chaparro, Iván & Watts, David & Gil, Esteban, 2017. "Modeling marginal CO2 emissions in hydrothermal systems: Efficient carbon signals for renewables," Applied Energy, Elsevier, vol. 204(C), pages 318-331.
    7. Amir Shahin Kamjou & Carol J. Miller & Mahdi Rouholamini & Caisheng Wang, 2021. "Comparison between Historical and Real-Time Techniques for Estimating Marginal Emissions Attributed to Electricity Generation," Energies, MDPI, vol. 14(17), pages 1-15, August.

    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. Brouwer, Anne Sjoerd & van den Broek, Machteld & Seebregts, Ad & Faaij, André, 2015. "Operational flexibility and economics of power plants in future low-carbon power systems," Applied Energy, Elsevier, vol. 156(C), pages 107-128.
    2. Changkeun Lee & Euijune Kim, 2017. "Mobility of Workers and Population between Old and New Capital Cities Using the Interregional Economic Model," Sustainability, MDPI, vol. 9(10), pages 1-15, October.
    3. Bigazzi, Alexander, 2019. "Comparison of marginal and average emission factors for passenger transportation modes," Applied Energy, Elsevier, vol. 242(C), pages 1460-1466.
    4. Hawkes, A.D., 2014. "Long-run marginal CO2 emissions factors in national electricity systems," Applied Energy, Elsevier, vol. 125(C), pages 197-205.
    5. Jordehi, A. Rezaee, 2019. "Optimisation of demand response in electric power systems, a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 308-319.
    6. ITO Koichiro & IDA Takanori & TANAKA Makoto, 2015. "The Persistence of Moral Suasion and Economic Incentives: Field experimental evidence from energy demand," Discussion papers 15014, Research Institute of Economy, Trade and Industry (RIETI).
    7. 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).
    8. Graff Zivin, Joshua S. & Kotchen, Matthew J. & Mansur, Erin T., 2014. "Spatial and temporal heterogeneity of marginal emissions: Implications for electric cars and other electricity-shifting policies," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PA), pages 248-268.
    9. Rahmani, Shima & Amjady, Nima, 2017. "A new optimal power flow approach for wind energy integrated power systems," Energy, Elsevier, vol. 134(C), pages 349-359.
    10. Niknam, Taher & Azizipanah-Abarghooee, Rasoul & Narimani, Mohammad Rasoul, 2012. "Reserve constrained dynamic optimal power flow subject to valve-point effects, prohibited zones and multi-fuel constraints," Energy, Elsevier, vol. 47(1), pages 451-464.
    11. Azizipanah-Abarghooee, Rasoul & Niknam, Taher & Roosta, Alireza & Malekpour, Ahmad Reza & Zare, Mohsen, 2012. "Probabilistic multiobjective wind-thermal economic emission dispatch based on point estimated method," Energy, Elsevier, vol. 37(1), pages 322-335.
    12. Stephen P. Holland & Erin T. Mansur & Nicholas Z. Muller & Andrew J. Yates, 2016. "Are There Environmental Benefits from Driving Electric Vehicles? The Importance of Local Factors," American Economic Review, American Economic Association, vol. 106(12), pages 3700-3729, December.
    13. Palmer, Karen L. & Burtraw, Dallas, 2005. "The Environmental Impacts of Electricity Restructuring: Looking Back and Looking Forward," Discussion Papers 10656, Resources for the Future.
    14. Eid, Cherrelle & Koliou, Elta & Valles, Mercedes & Reneses, Javier & Hakvoort, Rudi, 2016. "Time-based pricing and electricity demand response: Existing barriers and next steps," Utilities Policy, Elsevier, vol. 40(C), pages 15-25.
    15. Heydarzadeh, Zahra & Mac Kinnon, Michael & Thai, Clinton & Reed, Jeff & Brouwer, Jack, 2020. "Marginal methane emission estimation from the natural gas system," Applied Energy, Elsevier, vol. 277(C).
    16. Hyun, Minwoo & Kim, Yeong Jae & Eom, Jiyong, 2020. "Assessing the impact of a demand-resource bidding market on an electricity generation portfolio and the environment," Energy Policy, Elsevier, vol. 147(C).
    17. Hunt Allcott, 2012. "The Smart Grid, Entry, and Imperfect Competition in Electricity Markets," NBER Working Papers 18071, National Bureau of Economic Research, Inc.
    18. Adela Conchado & Pedro Linares, 2010. "The Economic Impact of Demand-Response Programs on Power Systems. A survey of the State of the Art," Working Papers 02-2010, Economics for Energy.
    19. Fitiwi, Desta Z. & Olmos, L. & Rivier, M. & de Cuadra, F. & Pérez-Arriaga, I.J., 2016. "Finding a representative network losses model for large-scale transmission expansion planning with renewable energy sources," Energy, Elsevier, vol. 101(C), pages 343-358.
    20. Dubey, Hari Mohan & Pandit, Manjaree & Panigrahi, B.K., 2015. "Hybrid flower pollination algorithm with time-varying fuzzy selection mechanism for wind integrated multi-objective dynamic economic dispatch," Renewable Energy, Elsevier, vol. 83(C), pages 188-202.

    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:appene:v:119:y:2014:i:c:p:141-150. 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/wps/find/journaldescription.cws_home/405891/description#description .

    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.