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Reducing Greenhouse Gas Emissions by Inducing Energy Conservation and Distributed Generation from Elimination of Electric Utility Customer Charges

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  • Joshua Pearce

    (MTU - Michigan Technological University)

  • Paul J Harris

    (Clarion University)

Abstract

This paper quantifies the increased green house gas emissions and negative effect on energy conservation (or "efficiency penalty") due to electric rate structures that employ an unavoidable customer charge. First the extent of customer charges was determined from a nationwide survey of U.S. electric tariffs. To eliminate the customer charge nationally while maintaining a fixed sum for electric companies for a given amount of electricity, an increase of 7.12% in the residential electrical rate was found to be necessary. If enacted, this increase in the electric rate would result in a 6.4% reduction in overall electricity consumption, conserving 73 billion kW-hrs, eliminating 44.3 million metric tons of carbon dioxide, and saving the entire U.S. residential sector over $8 billion per year. As shown here, these reductions would come from increased avoidable costs thus leveraging an increased rate of return on investments in energy efficiency, energy conservation behavior, distributed energy generation, and fuel choices. Finally, limitations of this study and analysis are discussed and conclusions are drawn for proposed energy policy changes.

Suggested Citation

  • Joshua Pearce & Paul J Harris, 2007. "Reducing Greenhouse Gas Emissions by Inducing Energy Conservation and Distributed Generation from Elimination of Electric Utility Customer Charges," Post-Print hal-02120518, HAL.
    • Handle: RePEc:hal:journl:hal-02120518
    Note: View the original document on HAL open archive server: https://hal.science/hal-02120518
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    References listed on IDEAS

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    Cited by:

    1. Islam, Aminul & Chan, Eng-Seng & Taufiq-Yap, Yun Hin & Mondal, Md. Alam Hossain & Moniruzzaman, M. & Mridha, Moniruzzaman, 2014. "Energy security in Bangladesh perspective—An assessment and implication," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 154-171.
    2. Shih, Yi-Hsuan & Tseng, Chao-Heng, 2014. "Cost-benefit analysis of sustainable energy development using life-cycle co-benefits assessment and the system dynamics approach," Applied Energy, Elsevier, vol. 119(C), pages 57-66.
    3. Liu, Chung-Ming & Liou, Ming-Lone & Yeh, Shin-Cheng & Shang, Neng-Chou, 2009. "Target-aimed versus wishful-thinking in designing efficient GHG reduction strategies for a metropolitan city: Taipei," Energy Policy, Elsevier, vol. 37(2), pages 400-406, February.
    4. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa & Shi, Guo-Hua & Zhang, Xu-Tao, 2008. "A fuzzy multi-criteria decision-making model for trigeneration system," Energy Policy, Elsevier, vol. 36(10), pages 3823-3832, October.
    5. Emily Prehoda & Joshua M. Pearce & Chelsea Schelly, 2019. "Policies to Overcome Barriers for Renewable Energy Distributed Generation: A Case Study of Utility Structure and Regulatory Regimes in Michigan," Energies, MDPI, vol. 12(4), pages 1-23, February.
    6. Branker, K. & Pathak, M.J.M. & Pearce, J.M., 2011. "A review of solar photovoltaic levelized cost of electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4470-4482.
    7. Srinivasan, Sunderasan, 2009. "Subsidy policy and the enlargement of choice," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(9), pages 2728-2733, December.

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