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Incentive mechanisms to promote energy efficiency programs in power distribution companies

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  • Osorio, Karim
  • Sauma, Enzo

Abstract

Power distribution companies (DISCOs) play an important role in promoting energy efficiency (hereafter EE), mainly due to the fact that they have detailed information regarding their clients' consumption patterns. However, under the traditional regulatory framework, DISCOs have disincentives to promote EE, due to the fact that a reduction in sales also means a reduction in their revenues and profits. Most regulatory policies encouraging EE have some embedded payment schemes that allow financing EE programs. In this paper, we focus on these EE-programs' payment schemes that are embedded into the regulatory policies. Specifically, this paper studies two models of the Principal–Agent bi-level type in order to analyze the economic effects of implementing different payment schemes to foster EE in DISCOs. The main difference between each model is that uncertainty in energy savings is considered by the electricity regulatory institution in only one of the models. In terms of the results, it is observed that, in general terms, it is more convenient for the regulator to adopt a performance-based incentive mechanism than a payment scheme financing only the fixed costs of implementing EE programs. However, if the electricity regulatory institution seeks a higher level of minimum expected utility, it is optimal to adopt a mixed system of compensation, which takes into account the fixed cost compensation and performance-based incentive payments.

Suggested Citation

  • Osorio, Karim & Sauma, Enzo, 2015. "Incentive mechanisms to promote energy efficiency programs in power distribution companies," Energy Economics, Elsevier, vol. 49(C), pages 336-349.
    • Handle: RePEc:eee:eneeco:v:49:y:2015:i:c:p:336-349
    DOI: 10.1016/j.eneco.2015.02.024
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    References listed on IDEAS

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    1. Antonio J. Conejo & Miguel Carrión & Juan M. Morales, 2010. "Decision Making Under Uncertainty in Electricity Markets," International Series in Operations Research and Management Science, Springer, number 978-1-4419-7421-1, December.
    2. Blumstein, Carl, 2010. "Program evaluation and incentives for administrators of energy-efficiency programs: Can evaluation solve the principal/agent problem?," Energy Policy, Elsevier, vol. 38(10), pages 6232-6239, October.
    3. Pousinho, H.M.I. & Mendes, V.M.F. & Catalão, J.P.S., 2011. "A risk-averse optimization model for trading wind energy in a market environment under uncertainty," Energy, Elsevier, vol. 36(8), pages 4935-4942.
    4. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
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    Cited by:

    1. Tsao, Yu-Chung & Vu, Thuy-Linh, 2019. "Power supply chain network design problem for smart grid considering differential pricing and buy-back policies," Energy Economics, Elsevier, vol. 81(C), pages 493-502.
    2. Felipe Barroco Fontes Cunha & Maria Cândida Arrais de Miranda Mousinho & Luciana Carvalho & Fábio Fernandes & Celso Castro & Marcelo Santana Silva & Ednildo Andrade Torres, 2021. "Renewable energy planning policy for the reduction of poverty in Brazil: lessons from Juazeiro," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(7), pages 9792-9810, July.
    3. Safarzadeh, Soroush & Rasti-Barzoki, Morteza & Hejazi, Seyed Reza, 2020. "A review of optimal energy policy instruments on industrial energy efficiency programs, rebound effects, and government policies," Energy Policy, Elsevier, vol. 139(C).

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    More about this item

    Keywords

    Conditional value at risk; Energy efficiency; Incentive mechanisms; Uncertainty;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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