IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v81y2018ip2p2870-2878.html
   My bibliography  Save this article

Residential electricity pricing in China: The context of price-based demand response

Author

Listed:
  • Yang, Changhui
  • Meng, Chen
  • Zhou, Kaile

Abstract

As a secondary energy, electricity is an important channel between original energy and energy consumers. Electricity price is a critical factor for the interests of all involvers in the electric power market. It also plays an important role for the sustainable development of energy and environment. Smart grid is a new conception proposed in recent years to improve the intelligent level and increase the efficiency of electric power system operation. Smart grid combines and integrates information technology, communication technology and intelligent control technology with tradition power system. To achieve the many objectives of smart grid, Demand response (DR), as an effective technique of demand side management (DSM), refers to the changes in electricity consumption behavior of users in response to the dynamic price or incentive rewards. Price based demand response (PBDR) is one of the two major DR programs. In this paper, we first introduce the pricing theories in economics, the pricing of electricity and the development of electricity pricing in China. Then, we present a detailed discussion on the PBDR strategies in the DSM of smart grid. Also, the research status of PBDR is reviewed. Finally, it gives a summary of the whole paper in the last Section.

Suggested Citation

  • Yang, Changhui & Meng, Chen & Zhou, Kaile, 2018. "Residential electricity pricing in China: The context of price-based demand response," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2870-2878.
  • Handle: RePEc:eee:rensus:v:81:y:2018:i:p2:p:2870-2878
    DOI: 10.1016/j.rser.2017.06.093
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032117310432
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.rser.2017.06.093?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. Alberini, Anna & Filippini, Massimo, 2011. "Response of residential electricity demand to price: The effect of measurement error," Energy Economics, Elsevier, vol. 33(5), pages 889-895, September.
    2. Hung, Ming-Feng & Huang, Tai-Hsin, 2015. "Dynamic demand for residential electricity in Taiwan under seasonality and increasing-block pricing," Energy Economics, Elsevier, vol. 48(C), pages 168-177.
    3. Siano, Pierluigi, 2014. "Demand response and smart grids—A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 461-478.
    4. 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.
    5. Zhou, Kai-le & Yang, Shan-lin & Shen, Chao, 2013. "A review of electric load classification in smart grid environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 103-110.
    6. 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.
    7. Liu, Ming-Hua & Margaritis, Dimitris & Zhang, Yang, 2013. "Market-driven coal prices and state-administered electricity prices in China," Energy Economics, Elsevier, vol. 40(C), pages 167-175.
    8. Panapakidis, Ioannis P. & Dagoumas, Athanasios S., 2016. "Day-ahead electricity price forecasting via the application of artificial neural network based models," Applied Energy, Elsevier, vol. 172(C), pages 132-151.
    9. Xu, Fang Yuan & Zhang, Tao & Lai, Loi Lei & Zhou, Hao, 2015. "Shifting Boundary for price-based residential demand response and applications," Applied Energy, Elsevier, vol. 146(C), pages 353-370.
    10. Wang, Zhaohua & Zhang, Bin & Zhang, Yixiang, 2012. "Determinants of public acceptance of tiered electricity price reform in China: Evidence from four urban cities," Applied Energy, Elsevier, vol. 91(1), pages 235-244.
    11. Koichiro Ito, 2014. "Do Consumers Respond to Marginal or Average Price? Evidence from Nonlinear Electricity Pricing," American Economic Review, American Economic Association, vol. 104(2), pages 537-563, February.
    12. Lin, Whei-Min & Gow, Hong-Jey & Tsai, Ming-Tang, 2010. "An enhanced radial basis function network for short-term electricity price forecasting," Applied Energy, Elsevier, vol. 87(10), pages 3226-3234, October.
    13. Koliou, Elta & Eid, Cherrelle & Chaves-Ávila, José Pablo & Hakvoort, Rudi A., 2014. "Demand response in liberalized electricity markets: Analysis of aggregated load participation in the German balancing mechanism," Energy, Elsevier, vol. 71(C), pages 245-254.
    14. Milstein, Irena & Tishler, Asher, 2015. "Can price volatility enhance market power? The case of renewable technologies in competitive electricity markets," Resource and Energy Economics, Elsevier, vol. 41(C), pages 70-90.
    15. Kohler, Marcel, 2014. "Differential electricity pricing and energy efficiency in South Africa," Energy, Elsevier, vol. 64(C), pages 524-532.
    16. Shen, Bo & Ghatikar, Girish & Lei, Zeng & Li, Jinkai & Wikler, Greg & Martin, Phil, 2014. "The role of regulatory reforms, market changes, and technology development to make demand response a viable resource in meeting energy challenges," Applied Energy, Elsevier, vol. 130(C), pages 814-823.
    17. Dodonov, Boris & Opitz, Petra & Pfaffenberger, Wolfgang, 2004. "How much do electricity tariff increases in Ukraine hurt the poor?," Energy Policy, Elsevier, vol. 32(7), pages 855-863, May.
    18. Gaillard, Pierre & Goude, Yannig & Nedellec, Raphaël, 2016. "Additive models and robust aggregation for GEFCom2014 probabilistic electric load and electricity price forecasting," International Journal of Forecasting, Elsevier, vol. 32(3), pages 1038-1050.
    19. Li, Lanlan & Gong, Chengzhu & Tian, Shizhong & Jiao, Jianling, 2016. "The peak-shaving efficiency analysis of natural gas time-of-use pricing for residential consumers: Evidence from multi-agent simulation," Energy, Elsevier, vol. 96(C), pages 48-58.
    20. Herter, Karen & McAuliffe, Patrick & Rosenfeld, Arthur, 2007. "An exploratory analysis of California residential customer response to critical peak pricing of electricity," Energy, Elsevier, vol. 32(1), pages 25-34.
    21. Ericson, Torgeir, 2011. "Households' self-selection of dynamic electricity tariffs," Applied Energy, Elsevier, vol. 88(7), pages 2541-2547, July.
    22. Zhou, Kaile & Yang, Shanlin & Shao, Zhen, 2016. "Energy Internet: The business perspective," Applied Energy, Elsevier, vol. 178(C), pages 212-222.
    23. Dütschke, Elisabeth & Paetz, Alexandra-Gwyn, 2013. "Dynamic electricity pricing—Which programs do consumers prefer?," Energy Policy, Elsevier, vol. 59(C), pages 226-234.
    24. Nowotarski, Jakub & Weron, Rafał, 2016. "On the importance of the long-term seasonal component in day-ahead electricity price forecasting," Energy Economics, Elsevier, vol. 57(C), pages 228-235.
    25. Sun, Chuanwang & Lin, Boqiang, 2013. "Reforming residential electricity tariff in China: Block tariffs pricing approach," Energy Policy, Elsevier, vol. 60(C), pages 741-752.
    26. Sun, Chuanwang, 2015. "An empirical case study about the reform of tiered pricing for household electricity in China," Applied Energy, Elsevier, vol. 160(C), pages 383-389.
    27. Feuerriegel, Stefan & Neumann, Dirk, 2014. "Measuring the financial impact of demand response for electricity retailers," Energy Policy, Elsevier, vol. 65(C), pages 359-368.
    28. Lin, Boqiang & Liu, Xia, 2013. "Electricity tariff reform and rebound effect of residential electricity consumption in China," Energy, Elsevier, vol. 59(C), pages 240-247.
    29. Nelson, Tim & Orton, Fiona, 2013. "A new approach to congestion pricing in electricity markets: Improving user pays pricing incentives," Energy Economics, Elsevier, vol. 40(C), pages 1-7.
    30. Cherni, Judith A. & Kentish, Joanna, 2007. "Renewable energy policy and electricity market reforms in China," Energy Policy, Elsevier, vol. 35(7), pages 3616-3629, July.
    31. 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.
    32. Arteconi, Alessia & Ciarrocchi, Eleonora & Pan, Quanwen & Carducci, Francesco & Comodi, Gabriele & Polonara, Fabio & Wang, Ruzhu, 2017. "Thermal energy storage coupled with PV panels for demand side management of industrial building cooling loads," Applied Energy, Elsevier, vol. 185(P2), pages 1984-1993.
    33. Torriti, Jacopo, 2012. "Price-based demand side management: Assessing the impacts of time-of-use tariffs on residential electricity demand and peak shifting in Northern Italy," Energy, Elsevier, vol. 44(1), pages 576-583.
    34. Warren, Peter, 2014. "A review of demand-side management policy in the UK," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 941-951.
    35. 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.
    36. Falsafi, Hananeh & Zakariazadeh, Alireza & Jadid, Shahram, 2014. "The role of demand response in single and multi-objective wind-thermal generation scheduling: A stochastic programming," Energy, Elsevier, vol. 64(C), pages 853-867.
    37. Aghaei, Jamshid & Alizadeh, Mohammad-Iman, 2013. "Demand response in smart electricity grids equipped with renewable energy sources: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 64-72.
    38. Wang, Yong & Li, Lin, 2014. "Time-of-use based electricity cost of manufacturing systems: Modeling and monotonicity analysis," International Journal of Production Economics, Elsevier, vol. 156(C), pages 246-259.
    39. Gyamfi, Samuel & Krumdieck, Susan & Urmee, Tania, 2013. "Residential peak electricity demand response—Highlights of some behavioural issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 71-77.
    40. 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.
    41. Carroll, James & Lyons, Seán & Denny, Eleanor, 2014. "Reducing household electricity demand through smart metering: The role of improved information about energy saving," Energy Economics, Elsevier, vol. 45(C), pages 234-243.
    42. Dupont, B. & De Jonghe, C. & Olmos, L. & Belmans, R., 2014. "Demand response with locational dynamic pricing to support the integration of renewables," Energy Policy, Elsevier, vol. 67(C), pages 344-354.
    43. Faruqui, Ahmad & George, Stephen S., 2002. "The Value of Dynamic Pricing in Mass Markets," The Electricity Journal, Elsevier, vol. 15(6), pages 45-55, July.
    44. Du, Gang & Lin, Wei & Sun, Chuanwang & Zhang, Dingzhong, 2015. "Residential electricity consumption after the reform of tiered pricing for household electricity in China," Applied Energy, Elsevier, vol. 157(C), pages 276-283.
    45. Islyaev, Suren & Date, Paresh, 2015. "Electricity futures price models: Calibration and forecasting," European Journal of Operational Research, Elsevier, vol. 247(1), pages 144-154.
    46. Tsitsiklis, John N. & Xu, Yunjian, 2015. "Pricing of fluctuations in electricity markets," European Journal of Operational Research, Elsevier, vol. 246(1), pages 199-208.
    47. Herter, Karen, 2007. "Residential implementation of critical-peak pricing of electricity," Energy Policy, Elsevier, vol. 35(4), pages 2121-2130, April.
    48. Ming, Zeng & Song, Xue & Mingjuan, Ma & Lingyun, Li & Min, Cheng & Yuejin, Wang, 2013. "Historical review of demand side management in China: Management content, operation mode, results assessment and relative incentives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 470-482.
    49. Zhou, Kaile & Yang, Shanlin, 2015. "Demand side management in China: The context of China’s power industry reform," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 954-965.
    50. Ahmad Faruqui & Sanem Sergici, 2010. "Household response to dynamic pricing of electricity: a survey of 15 experiments," Journal of Regulatory Economics, Springer, vol. 38(2), pages 193-225, October.
    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. Guo, Hongye & Davidson, Michael R. & Chen, Qixin & Zhang, Da & Jiang, Nan & Xia, Qing & Kang, Chongqing & Zhang, Xiliang, 2020. "Power market reform in China: Motivations, progress, and recommendations," Energy Policy, Elsevier, vol. 145(C).
    2. Sulaima, Mohamad Fani & Dahlan, Nofri Yenita & Yasin, Zuhaila Mat & Rosli, Marlinda Mohd & Omar, Zulkiflee & Hassan, Mohammad Yusri, 2019. "A review of electricity pricing in peninsular Malaysia: Empirical investigation about the appropriateness of Enhanced Time of Use (ETOU) electricity tariff," Renewable and Sustainable Energy Reviews, Elsevier, vol. 110(C), pages 348-367.
    3. Proskuryakova, Liliana & Starodubtseva, Alena & Bianco, Vincenzo, 2020. "Modelling a household tariff for reducing sectoral cross-subsidies in the Russian power market," Energy, Elsevier, vol. 213(C).
    4. Jasiński, Tomasz, 2022. "A new approach to modeling cycles with summer and winter demand peaks as input variables for deep neural networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    5. Tahir, Muhammad Faizan & Chen, Haoyong & Khan, Asad & Javed, Muhammad Sufyan & Cheema, Khalid Mehmood & Laraik, Noman Ali, 2020. "Significance of demand response in light of current pilot projects in China and devising a problem solution for future advancements," Technology in Society, Elsevier, vol. 63(C).
    6. Jia, Jun-Jun & Guo, Jin & Wei, Chu, 2021. "Elasticities of residential electricity demand in China under increasing-block pricing constraint: New estimation using household survey data," Energy Policy, Elsevier, vol. 156(C).
    7. Srivastava, A. & Van Passel, S. & Valkering, P. & Laes, E.J.W., 2021. "Power outages and bill savings: A choice experiment on residential demand response acceptability in Delhi," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    8. Hojnik, Jana & Ruzzier, Mitja & Fabri, Stephanie & Klopčič, Alenka Lena, 2021. "What you give is what you get: Willingness to pay for green energy," Renewable Energy, Elsevier, vol. 174(C), pages 733-746.
    9. Amiri-Pebdani, Sima & Alinaghian, Mahdi & Safarzadeh, Soroush, 2022. "Time-Of-Use pricing in an energy sustainable supply chain with government interventions: A game theory approach," Energy, Elsevier, vol. 255(C).
    10. Agarwal, Sumit & Sing, Tien Foo & Sultana, Mahanaaz, 2022. "Public media campaign and energy conservation: A natural experiment in Singapore," Energy Economics, Elsevier, vol. 114(C).
    11. Mohammad Esmaeil Honarmand & Vahid Hosseinnezhad & Barry Hayes & Pierluigi Siano, 2021. "Local Energy Trading in Future Distribution Systems," Energies, MDPI, vol. 14(11), pages 1-19, May.
    12. Liangkai Li & Jingguang Huang & Zhenxing Li & Hao Qi, 2023. "Optimized Dispatch of Regional Integrated Energy System Considering Wind Power Consumption in Low-Temperature Environment," Energies, MDPI, vol. 16(23), pages 1-19, November.
    13. Lijing Zhang & Shuke Fu & Jiali Tian & Jiachao Peng, 2022. "A Review of Energy Industry Chain and Energy Supply Chain," Energies, MDPI, vol. 15(23), pages 1-21, December.
    14. Gupta, Preeti & Pal Verma, Yajvender, 2021. "Voltage profile improvement using demand side management in distribution networks under frequency linked pricing regime," Applied Energy, Elsevier, vol. 295(C).
    15. Khalilpour, Kaveh R. & Lusis, Peter, 2020. "Network capacity charge for sustainability and energy equity: A model-based analysis," Applied Energy, Elsevier, vol. 266(C).
    16. Xiao Gong & Fan Li & Bo Sun & Dong Liu, 2020. "Collaborative Optimization of Multi-Energy Complementary Combined Cooling, Heating, and Power Systems Considering Schedulable Loads," Energies, MDPI, vol. 13(4), pages 1-17, February.
    17. Nirbheram, Joshi Sukhdev & Mahesh, Aeidapu & Bhimaraju, Ambati, 2023. "Techno-economic analysis of grid-connected hybrid renewable energy system adapting hybrid demand response program and novel energy management strategy," Renewable Energy, Elsevier, vol. 212(C), pages 1-16.

    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. Meyabadi, A. Fattahi & Deihimi, M.H., 2017. "A review of demand-side management: Reconsidering theoretical framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 367-379.
    2. Haider, Haider Tarish & See, Ong Hang & Elmenreich, Wilfried, 2016. "Residential demand response scheme based on adaptive consumption level pricing," Energy, Elsevier, vol. 113(C), pages 301-308.
    3. Märkle-Huß, Joscha & Feuerriegel, Stefan & Neumann, Dirk, 2018. "Large-scale demand response and its implications for spot prices, load and policies: Insights from the German-Austrian electricity market," Applied Energy, Elsevier, vol. 210(C), pages 1290-1298.
    4. Ussama Assad & Muhammad Arshad Shehzad Hassan & Umar Farooq & Asif Kabir & Muhammad Zeeshan Khan & S. Sabahat H. Bukhari & Zain ul Abidin Jaffri & Judit Oláh & József Popp, 2022. "Smart Grid, Demand Response and Optimization: A Critical Review of Computational Methods," Energies, MDPI, vol. 15(6), pages 1-36, March.
    5. 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.
    6. Zhou, Kaile & Yang, Shanlin, 2015. "Demand side management in China: The context of China’s power industry reform," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 954-965.
    7. Khanna, Nina Zheng & Guo, Jin & Zheng, Xinye, 2016. "Effects of demand side management on Chinese household electricity consumption: Empirical findings from Chinese household survey," Energy Policy, Elsevier, vol. 95(C), pages 113-125.
    8. Paterakis, Nikolaos G. & Erdinç, Ozan & Catalão, João P.S., 2017. "An overview of Demand Response: Key-elements and international experience," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 871-891.
    9. Wang, Chen & Zhou, Kaile & Yang, Shanlin, 2017. "A review of residential tiered electricity pricing in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 533-543.
    10. Yan, Xing & Ozturk, Yusuf & Hu, Zechun & Song, Yonghua, 2018. "A review on price-driven residential demand response," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 411-419.
    11. Lin, Boqiang & Chen, Xing, 2018. "Is the implementation of the Increasing Block Electricity Prices policy really effective?--- Evidence based on the analysis of synthetic control method," Energy, Elsevier, vol. 163(C), pages 734-750.
    12. Li, Yao & Fan, Jin & Zhao, Dingtao & Wu, Yanrui & Li, Jun, 2016. "Tiered gasoline pricing: A personal carbon trading perspective," Energy Policy, Elsevier, vol. 89(C), pages 194-201.
    13. Wang, Yong & Li, Lin, 2016. "Critical peak electricity pricing for sustainable manufacturing: Modeling and case studies," Applied Energy, Elsevier, vol. 175(C), pages 40-53.
    14. Haider, Haider Tarish & See, Ong Hang & Elmenreich, Wilfried, 2016. "A review of residential demand response of smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 166-178.
    15. Guo, Peiyang & Li, Victor O.K. & Lam, Jacqueline C.K., 2017. "Smart demand response in China: Challenges and drivers," Energy Policy, Elsevier, vol. 107(C), pages 1-10.
    16. Makena Coffman & Paul Bernstein & Sherilyn Wee & Aida Arik, 2016. "Estimating the Opportunity for Load-Shifting in Hawaii: An Analysis of Proposed Residential Time-of-Use Rates," Working Papers 2016-10, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
    17. Wang, Zhaohua & Sun, Yefei & Wang, Bo, 2020. "Policy cognition is more effective than step tariff in promoting electricity saving behaviour of residents," Energy Policy, Elsevier, vol. 139(C).
    18. Gong, Chengzhu & Yu, Shiwei & Zhu, Kejun & Hailu, Atakelty, 2016. "Evaluating the influence of increasing block tariffs in residential gas sector using agent-based computational economics," Energy Policy, Elsevier, vol. 92(C), pages 334-347.
    19. 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.
    20. 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.

    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:rensus:v:81:y:2018:i:p2:p:2870-2878. 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/600126/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.