IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v88y2011i7p2548-2558.html
   My bibliography  Save this article

Effect of optimal spinning reserve requirement on system pollution emission considering reserve supplying demand response in the electricity market

Author

Listed:
  • Behrangrad, Mahdi
  • Sugihara, Hideharu
  • Funaki, Tsuyoshi

Abstract

Pollution emission reduction is becoming an inevitable global goal. Incorporating pollution reduction goals into power system operation affects several different aspects, such as unit scheduling and system reliability. At the same time, changes in the energy scheduling change the required optimal reserve amount. Optimal spinning reserve scheduling also affects the energy market scheduling. Optimal reserve allocation changes the energy scheduling, which affect the amount of pollution emission. Therefore, incorporating pollution emission reduction and optimal spinning reserve scheduling cannot be studied separately. Analysis of the system effects of pollution reduction should be performed considering the ancillary service market, specificity the optimal spinning reserve scheduling. This problem is addressed in this paper by incorporating optimal spinning reserve scheduling in a combined environment economic dispatch (CEED) in one objective function. The framework of this paper enables the study of the effect of optimal reserve scheduling and emission reduction as well as an analysis of the system effects of pollution reduction. With the increased AMI and smart grid realization, the reserve supplying demand response (RSDR) is becoming an important player in the reserve market, and thus, these resources are also taken into account. In this paper, the objective function is social cost minimization, including the costs associated with energy provision, reserve procurement, expected interruptions and environmental pollution. A MIP-based optimization method is developed, which reduces the computational burden considerably while maintaining the ability to reach to the optimal solution. The IEEE RTS 1996 is used as a test case for numerical simulations, and the results are presented. The numerical results show that optimal reserve scheduling and RSDR utilization resources have a considerable impact on environmental-economic cost characteristics.

Suggested Citation

  • Behrangrad, Mahdi & Sugihara, Hideharu & Funaki, Tsuyoshi, 2011. "Effect of optimal spinning reserve requirement on system pollution emission considering reserve supplying demand response in the electricity market," Applied Energy, Elsevier, vol. 88(7), pages 2548-2558, July.
  • Handle: RePEc:eee:appene:v:88:y:2011:i:7:p:2548-2558
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306-2619(11)00052-3
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Phalan, Ben, 2009. "The social and environmental impacts of biofuels in Asia: An overview," Applied Energy, Elsevier, vol. 86(Supplemen), pages 21-29, November.
    2. Curtis Carlson & Dallas Burtraw & Maureen Cropper & Karen L. Palmer, 2000. "Sulfur Dioxide Control by Electric Utilities: What Are the Gains from Trade?," Journal of Political Economy, University of Chicago Press, vol. 108(6), pages 1292-1326, December.
    3. Pekala, Lukasz M. & Tan, Raymond R. & Foo, Dominic C.Y. & Jezowski, Jacek M., 2010. "Optimal energy planning models with carbon footprint constraints," Applied Energy, Elsevier, vol. 87(6), pages 1903-1910, June.
    4. Zarnikau, Jay W., 2010. "Demand participation in the restructured Electric Reliability Council of Texas market," Energy, Elsevier, vol. 35(4), pages 1536-1543.
    5. Isemonger, Alan G., 2009. "The evolving design of RTO ancillary service markets," Energy Policy, Elsevier, vol. 37(1), pages 150-157, January.
    6. Li, Y.F. & Li, Y.P. & Huang, G.H. & Chen, X., 2010. "Energy and environmental systems planning under uncertainty--An inexact fuzzy-stochastic programming approach," Applied Energy, Elsevier, vol. 87(10), pages 3189-3211, October.
    7. Schmidt, Johannes & Leduc, Sylvain & Dotzauer, Erik & Kindermann, Georg & Schmid, Erwin, 2010. "Cost-effective CO2 emission reduction through heat, power and biofuel production from woody biomass: A spatially explicit comparison of conversion technologies," Applied Energy, Elsevier, vol. 87(7), pages 2128-2141, July.
    8. Hall, Darwin C. & Sandii Win, M. & Hall, Jane V., 1995. "Air pollution impacts from demand-side management," Energy, Elsevier, vol. 20(1), pages 27-35.
    9. Papagiannis, G. & Dagoumas, A. & Lettas, N. & Dokopoulos, P., 2008. "Economic and environmental impacts from the implementation of an intelligent demand side management system at the European level," Energy Policy, Elsevier, vol. 36(1), pages 163-180, January.
    10. Aghaei, J. & Shayanfar, H.A. & Amjady, N., 2009. "Joint market clearing in a stochastic framework considering power system security," Applied Energy, Elsevier, vol. 86(9), pages 1675-1682, September.
    11. Aalami, H.A. & Moghaddam, M. Parsa & Yousefi, G.R., 2010. "Demand response modeling considering Interruptible/Curtailable loads and capacity market programs," Applied Energy, Elsevier, vol. 87(1), pages 243-250, January.
    12. Vahidinasab, V. & Jadid, S., 2009. "Multiobjective environmental/techno-economic approach for strategic bidding in energy markets," Applied Energy, Elsevier, vol. 86(4), pages 496-504, 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. Behrangrad, Mahdi, 2015. "A review of demand side management business models in the electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 270-283.
    2. Liu, Fan & Bie, Zhaohong & Liu, Shiyu & Ding, Tao, 2017. "Day-ahead optimal dispatch for wind integrated power system considering zonal reserve requirements," Applied Energy, Elsevier, vol. 188(C), pages 399-408.
    3. Alasseri, Rajeev & Tripathi, Ashish & Joji Rao, T. & Sreekanth, K.J., 2017. "A review on implementation strategies for demand side management (DSM) in Kuwait through incentive-based demand response programs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 617-635.
    4. Wang, Dan & Zhou, Yue & Jia, Hongjie & Wang, Chengshan & Lu, Ning & Sui, Pang-Chieh & Fan, Menghua, 2016. "An energy-constrained state priority list model using deferrable electrolyzers as a load management mechanism," Applied Energy, Elsevier, vol. 167(C), pages 201-210.
    5. Yebai Qi & Dan Wang & Yu Lan & Hongjie Jia & Chengshan Wang & Kaixin Liu & Qing’e Hu & Menghua Fan, 2017. "A Two-Level Optimal Scheduling Strategy for Central Air-Conditioners Based on Metal Model with Comprehensive State-Queueing Control Models," Energies, MDPI, vol. 10(12), pages 1-21, December.
    6. Hong, Ying-Yi & Apolinario, Gerard Francesco DG. & Chung, Chen-Nien & Lu, Tai-Ken & Chu, Chia-Chi, 2020. "Effect of Taiwan's energy policy on unit commitment in 2025," Applied Energy, Elsevier, vol. 277(C).
    7. Reihani, Ehsan & Motalleb, Mahdi & Thornton, Matsu & Ghorbani, Reza, 2016. "A novel approach using flexible scheduling and aggregation to optimize demand response in the developing interactive grid market architecture," Applied Energy, Elsevier, vol. 183(C), pages 445-455.
    8. Toh, G.K. & Gooi, H.B., 2012. "Procurement of interruptible load services in electricity supply systems," Applied Energy, Elsevier, vol. 98(C), pages 533-539.
    9. Heydarian-Forushani, E. & Golshan, M.E.H. & Shafie-khah, M., 2015. "Flexible security-constrained scheduling of wind power enabling time of use pricing scheme," Energy, Elsevier, vol. 90(P2), pages 1887-1900.
    10. Edwin Garcia & Alexander Águila & Leony Ortiz & Milton Ruiz, 2024. "Optimum Stochastic Allocation for Demand Response for Power Markets in Microgrids," Energies, MDPI, vol. 17(5), pages 1-16, February.
    11. Behrangrad, Mahdi & Sugihara, Hideharu & Funaki, Tsuyoshi, 2012. "Integrating the cold load pickup effect of reserve supplying demand response resource in social cost minimization based system scheduling," Energy, Elsevier, vol. 45(1), pages 1034-1041.
    12. Vardakas, John S. & Zorba, Nizar & Verikoukis, Christos V., 2015. "Performance evaluation of power demand scheduling scenarios in a smart grid environment," Applied Energy, Elsevier, vol. 142(C), pages 164-178.
    13. Motalleb, Mahdi & Thornton, Matsu & Reihani, Ehsan & Ghorbani, Reza, 2016. "A nascent market for contingency reserve services using demand response," Applied Energy, Elsevier, vol. 179(C), pages 985-995.
    14. Wang, D. & Parkinson, S. & Miao, W. & Jia, H. & Crawford, C. & Djilali, N., 2013. "Hierarchical market integration of responsive loads as spinning reserve," Applied Energy, Elsevier, vol. 104(C), pages 229-238.
    15. Ho-Sung Ryu & Mun-Kyeom Kim, 2020. "Combined Economic Emission Dispatch with Environment-Based Demand Response Using WU-ABC Algorithm," Energies, MDPI, vol. 13(23), pages 1-20, 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. Tan, Raymond R. & Aviso, Kathleen B. & Barilea, Ivan U. & Culaba, Alvin B. & Cruz, Jose B., 2012. "A fuzzy multi-regional input–output optimization model for biomass production and trade under resource and footprint constraints," Applied Energy, Elsevier, vol. 90(1), pages 154-160.
    2. Aghaei, Jamshid & Alizadeh, Mohammad-Iman, 2013. "Multi-objective self-scheduling of CHP (combined heat and power)-based microgrids considering demand response programs and ESSs (energy storage systems)," Energy, Elsevier, vol. 55(C), pages 1044-1054.
    3. 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.
    4. Heydarian-Forushani, E. & Golshan, M.E.H. & Shafie-khah, M., 2015. "Flexible security-constrained scheduling of wind power enabling time of use pricing scheme," Energy, Elsevier, vol. 90(P2), pages 1887-1900.
    5. Hosseini, Seyyed Ahmad & Amjady, Nima & Shafie-khah, Miadreza & Catalão, João P.S., 2016. "A new multi-objective solution approach to solve transmission congestion management problem of energy markets," Applied Energy, Elsevier, vol. 165(C), pages 462-471.
    6. Esmaili, Masoud & Shayanfar, Heidar Ali & Amjady, Nima, 2010. "Congestion management enhancing transient stability of power systems," Applied Energy, Elsevier, vol. 87(3), pages 971-981, March.
    7. Navid Rezaei & Abdollah Ahmadi & Mohammadhossein Deihimi, 2022. "A Comprehensive Review of Demand-Side Management Based on Analysis of Productivity: Techniques and Applications," Energies, MDPI, vol. 15(20), pages 1-28, October.
    8. Stötzer, Martin & Hauer, Ines & Richter, Marc & Styczynski, Zbigniew A., 2015. "Potential of demand side integration to maximize use of renewable energy sources in Germany," Applied Energy, Elsevier, vol. 146(C), pages 344-352.
    9. Tan, Raymond R., 2011. "A general source-sink model with inoperability constraints for robust energy sector planning," Applied Energy, Elsevier, vol. 88(11), pages 3759-3764.
    10. Najafi, M. & Ehsan, M. & Fotuhi-Firuzabad, M. & Akhavein, A. & Afshar, K., 2010. "Optimal reserve capacity allocation with consideration of customer reliability requirements," Energy, Elsevier, vol. 35(9), pages 3883-3890.
    11. Nikzad, Mehdi & Mozafari, Babak & Bashirvand, Mahdi & Solaymani, Soodabeh & Ranjbar, Ali Mohamad, 2012. "Designing time-of-use program based on stochastic security constrained unit commitment considering reliability index," Energy, Elsevier, vol. 41(1), pages 541-548.
    12. Schroeder, Andreas, 2011. "Modeling storage and demand management in power distribution grids," Applied Energy, Elsevier, vol. 88(12), pages 4700-4712.
    13. Duy Phuc Le & Duong Minh Bui & Cao Cuong Ngo & Anh My Thi Le, 2018. "FLISR Approach for Smart Distribution Networks Using E-Terra Software—A Case Study," Energies, MDPI, vol. 11(12), pages 1-33, November.
    14. Esmaili, Masoud & Amjady, Nima & Shayanfar, Heidar Ali, 2011. "Multi-objective congestion management by modified augmented [epsilon]-constraint method," Applied Energy, Elsevier, vol. 88(3), pages 755-766, March.
    15. Chen, C. & Li, Y.P. & Huang, G.H. & Zhu, Y., 2012. "An inexact robust nonlinear optimization method for energy systems planning under uncertainty," Renewable Energy, Elsevier, vol. 47(C), pages 55-66.
    16. Chen, C. & Li, Y.P. & Huang, G.H., 2013. "An inexact robust optimization method for supporting carbon dioxide emissions management in regional electric-power systems," Energy Economics, Elsevier, vol. 40(C), pages 441-456.
    17. Yiqi Dong & Zuoji Dong, 2023. "Bibliometric Analysis of Game Theory on Energy and Natural Resource," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
    18. Stavins, Robert, 2001. "Lessons From the American Experiment With Market-Based Environmental Policies," RFF Working Paper Series dp-01-53, Resources for the Future.
    19. James Thurlow & Giacomo Branca & Erika Felix & Irini Maltsoglou & Luis E. Rincón, 2016. "Producing Biofuels in Low-Income Countries: An Integrated Environmental and Economic Assessment for Tanzania," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 64(2), pages 153-171, June.
    20. Ba, Birome Holo & Prins, Christian & Prodhon, Caroline, 2016. "Models for optimization and performance evaluation of biomass supply chains: An Operations Research perspective," Renewable Energy, Elsevier, vol. 87(P2), pages 977-989.

    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:88:y:2011:i:7:p:2548-2558. 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.