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Evaluating the influence of increasing block tariffs in residential gas sector using agent-based computational economics

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  • Gong, Chengzhu
  • Yu, Shiwei
  • Zhu, Kejun
  • Hailu, Atakelty

Abstract

Designing a desirable increasing block tariff for the residential gas retail market has been a challenging task for regulated utilities, especially in China. To deal with such problems, in this paper, we establish an agent-based, computational economics system to provide a formal evaluation of the direct and indirect influences of several issued increasing block tariffs in the residential gas market. Moreover, a comprehensive demand response behaviour model has been improved in term of price elasticity, while still coping with income levels and complex social environment. We also compute and compare the outcomes of several increasing block tariffs with the initial flat tariff by running the system on a test-case using real-world data from a middle-scale gas retail market in Wuhan. The results indicate that there is an appropriate increasing block gas tariff scheme that has greater ability to improve social equity while still ensuring operator revenue and promoting gas conservation. In order to offset the limitations of the proposed increasing block tariffs, the regulator should adopt some complementary measures, such as applying appropriate policies targeting the intended consumers, and allowing large families to obtain extra allowance of volume.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:enepol:v:92:y:2016:i:c:p:334-347
    DOI: 10.1016/j.enpol.2016.02.014
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    1. John Cuddington & Zhongmin Wang, 2006. "Assessing the Degree of Spot Market Integration for U.S. Natural Gas: Evidence from Daily Price Data," Journal of Regulatory Economics, Springer, vol. 29(2), pages 195-210, March.
    2. Yu, Shiwei & Wei, Yi-Ming & Guo, Haixiang & Ding, Liping, 2014. "Carbon emission coefficient measurement of the coal-to-power energy chain in China," Applied Energy, Elsevier, vol. 114(C), pages 290-300.
    3. Sun, Chuanwang & Lin, Boqiang, 2013. "Reforming residential electricity tariff in China: Block tariffs pricing approach," Energy Policy, Elsevier, vol. 60(C), pages 741-752.
    4. Freund, Caroline & Wallich, Christine, 1997. "Public-Sector Price Reforms in Transition Economies: Who Gains? Who Loses? The Case of Household Energy Prices in Poland," Economic Development and Cultural Change, University of Chicago Press, vol. 46(1), pages 35-59, October.
    5. Andre Gabor, 1955. "A Note on Block Tariffs," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 23(1), pages 32-41.
    6. 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.
    7. An, Li, 2012. "Modeling human decisions in coupled human and natural systems: Review of agent-based models," Ecological Modelling, Elsevier, vol. 229(C), pages 25-36.
    8. 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.
    9. C G Amrhein, 1995. "Searching for the Elusive Aggregation Effect: Evidence from Statistical Simulations," Environment and Planning A, , vol. 27(1), pages 105-119, January.
    10. Aline Coudouel & Anis A. Dani & Stefano Paternostro, 2006. "Poverty and Social Impact Analysis of Reform : Lessons and Examples from Implementation," World Bank Publications - Books, The World Bank Group, number 7122.
    11. Faruqui, Ahmad & George, Stephen S., 2006. "Pushing the Envelope on Rate Design," The Electricity Journal, Elsevier, vol. 19(2), pages 33-42, March.
    12. Rahimiyan, Morteza & Rajabi Mashhadi, Habib, 2010. "Evaluating the efficiency of divestiture policy in promoting competitiveness using an analytical method and agent-based computational economics," Energy Policy, Elsevier, vol. 38(3), pages 1588-1595, March.
    13. Julie A. Hewitt & W. Michael Hanemann, 1995. "A Discrete/Continuous Choice Approach to Residential Water Demand under Block Rate Pricing," Land Economics, University of Wisconsin Press, vol. 71(2), pages 173-192.
    14. Zhu, Zhi-Shuang & Liao, Hua & Cao, Huai-Shu & Wang, Lu & Wei, Yi-Ming & Yan, Jinyue, 2014. "The differences of carbon intensity reduction rate across 89 countries in recent three decades," Applied Energy, Elsevier, vol. 113(C), pages 808-815.
    15. John J. Boland & Dale Whittington, 1998. "The Political Economy of Increasing Block Tariffs for Water in Developing Countries," EEPSEA Special and Technical Paper sp199801t3, Economy and Environment Program for Southeast Asia (EEPSEA), revised Jan 1998.
    16. Li, Lanlan & Gong, Chengzhu & Wang, Deyun & Zhu, Kejun, 2013. "Multi-agent simulation of the time-of-use pricing policy in an urban natural gas pipeline network: A case study of Zhengzhou," Energy, Elsevier, vol. 52(C), pages 37-43.
    17. Wang, Ting & Lin, Boqiang, 2014. "China's natural gas consumption and subsidies—From a sector perspective," Energy Policy, Elsevier, vol. 65(C), pages 541-551.
    18. Nigel Gilbert & Pietro Terna, 2000. "How to build and use agent-based models in social science," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 1(1), pages 57-72, March.
    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. Lee, Timothy & Yao, Runming & Coker, Phil, 2014. "An analysis of UK policies for domestic energy reduction using an agent based tool," Energy Policy, Elsevier, vol. 66(C), pages 267-279.
    21. Ma, Tieju & Nakamori, Yoshiteru, 2009. "Modeling technological change in energy systems – From optimization to agent-based modeling," Energy, Elsevier, vol. 34(7), pages 873-879.
    22. Paltsev, Sergey & Zhang, Danwei, 2015. "Natural gas pricing reform in China: Getting closer to a market system?," Energy Policy, Elsevier, vol. 86(C), pages 43-56.
    23. Maya Sopha, Bertha & Klöckner, Christian A. & Hertwich, Edgar G., 2011. "Exploring policy options for a transition to sustainable heating system diffusion using an agent-based simulation," Energy Policy, Elsevier, vol. 39(5), pages 2722-2729, May.
    24. Whittington, Dale, 1992. "Possible Adverse Effects of Increasing Block Water Tariffs in Developing Countries," Economic Development and Cultural Change, University of Chicago Press, vol. 41(1), pages 75-87, October.
    25. Gong, Chengzhu & Tang, Kai & Zhu, Kejun & Hailu, Atakelty, 2016. "An optimal time-of-use pricing for urban gas: A study with a multi-agent evolutionary game-theoretic perspective," Applied Energy, Elsevier, vol. 163(C), pages 283-294.
    26. Lester D. Taylor, 1975. "The Demand for Electricity: A Survey," Bell Journal of Economics, The RAND Corporation, vol. 6(1), pages 74-110, Spring.
    27. 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.
    28. Lin, Boqiang & Jiang, Zhujun, 2012. "Designation and influence of household increasing block electricity tariffs in China," Energy Policy, Elsevier, vol. 42(C), pages 164-173.
    29. Meran Georg & von Hirschhausen Christian, 2017. "Increasing Block Tariffs in the Water Sector – An Interpretation in Terms of Social Preferences," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 17(3), pages 1-24, July.
    30. Donald E. Agthe & R. Bruce Billings, 1987. "Equity, Price Elasticity, and Household Income Under Increasing Block Rates for Water," American Journal of Economics and Sociology, Wiley Blackwell, vol. 46(3), pages 273-286, July.
    31. Yu, Yihua & Zheng, Xinye & Han, Yi, 2014. "On the demand for natural gas in urban China," Energy Policy, Elsevier, vol. 70(C), pages 57-63.
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