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Analysis of energy service systems in urban areas and their CO2 mitigations and economic impacts

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  • Aki, Hirohisa
  • Oyama, Tsutomu
  • Tsuji, Kiichiro

Abstract

Three kinds of energy service system were examined as alternative energy systems in urban areas. A comparison of these energy systems was performed by finding Pareto optimum solutions for a multi-objective model. The model had two objective functions: CO2 emission and cost to consumer. Various energy pricings were provided in the model as variables. The assumed alternative systems were those in which: (1) every consumer had a cogeneration system (CGS); (2) there was a centralized energy supply plant (ESP) that had a CGS installed and supplied energy (electricity, gas, cooling and heating) to consumers; and (3) both (1) and (2) were installed. Minimization of CO2 emissions and minimization of cost to consumers were assumed as objective functions of the multi-objective model. Energy prices that consumers paid were used in the model as variables. We performed an analysis and comparison of the three kinds of system from the viewpoints of CO2 emission, economic impact on consumers and ESP, using system operations as evaluation indexes.

Suggested Citation

  • Aki, Hirohisa & Oyama, Tsutomu & Tsuji, Kiichiro, 2006. "Analysis of energy service systems in urban areas and their CO2 mitigations and economic impacts," Applied Energy, Elsevier, vol. 83(10), pages 1076-1088, October.
  • Handle: RePEc:eee:appene:v:83:y:2006:i:10:p:1076-1088
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    Cited by:

    1. Mancarella, Pierluigi, 2014. "MES (multi-energy systems): An overview of concepts and evaluation models," Energy, Elsevier, vol. 65(C), pages 1-17.
    2. Carpaneto, Enrico & Chicco, Gianfranco & Mancarella, Pierluigi & Russo, Angela, 2011. "Cogeneration planning under uncertainty: Part I: Multiple time frame approach," Applied Energy, Elsevier, vol. 88(4), pages 1059-1067, April.
    3. Tolis, Athanasios I. & Rentizelas, Athanasios A., 2011. "An impact assessment of electricity and emission allowances pricing in optimised expansion planning of power sector portfolios," Applied Energy, Elsevier, vol. 88(11), pages 3791-3806.
    4. repec:eee:energy:v:137:y:2017:i:c:p:1231-1251 is not listed on IDEAS
    5. Keirstead, James & Jennings, Mark & Sivakumar, Aruna, 2012. "A review of urban energy system models: Approaches, challenges and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 3847-3866.
    6. Dong, Cong & Huang, Guohe & Cai, Yanpeng & Li, Wei & Cheng, Guanhui, 2014. "Fuzzy interval programming for energy and environmental systems management under constraint-violation and energy-substitution effects: A case study for the City of Beijing," Energy Economics, Elsevier, vol. 46(C), pages 375-394.
    7. Chicco, Gianfranco & Mancarella, Pierluigi, 2009. "Distributed multi-generation: A comprehensive view," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(3), pages 535-551, April.
    8. Mirko M. Stojiljković & Mladen M. Stojiljković & Bratislav D. Blagojević, 2014. "Multi-Objective Combinatorial Optimization of Trigeneration Plants Based on Metaheuristics," Energies, MDPI, Open Access Journal, vol. 7(12), pages 1-28, December.
    9. Ashina, Shuichi & Fujino, Junichi & Masui, Toshihiko & Ehara, Tomoki & Hibino, Go, 2012. "A roadmap towards a low-carbon society in Japan using backcasting methodology: Feasible pathways for achieving an 80% reduction in CO2 emissions by 2050," Energy Policy, Elsevier, vol. 41(C), pages 584-598.

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    Keywords

    Energy systems CO2 mitigation Energy pricing;

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