IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i8p1910-d345218.html
   My bibliography  Save this article

A Simple Distribution Energy Tariff under the Penetration of DG

Author

Listed:
  • Javier Borquez

    (Departamento de Ingenieria Electrica, Universidad de Santiago de Chile, Estación Central, Santiago 9160000, Chile)

  • Hector Chavez

    (Departamento de Ingenieria Electrica, Universidad de Santiago de Chile, Estación Central, Santiago 9160000, Chile)

  • Karina A. Barbosa

    (Departamento de Ingenieria Electrica, Universidad de Santiago de Chile, Estación Central, Santiago 9160000, Chile)

  • Marcela Jamett

    (Departamento de Ingenieria Electrica, Universidad de Santiago de Chile, Estación Central, Santiago 9160000, Chile)

  • Rodrigo Acuna

    (Departamento de Ingenieria Electrica, Universidad de Santiago de Chile, Estación Central, Santiago 9160000, Chile)

Abstract

In a scenario where distributed generation infrastructure is increasing, the impact of that integration on electricity tariffs has captured particular attention. As the distribution sector is mainly regulated, tariff systems are defined by the authority. Then, tariffs must be simple, so the methodology, criteria, and procedures can be made public to ensure transparency and responsiveness of the customers to price signals. In the aim of simplicity, tariff systems in current practices mostly consist of volumetric charges. Hence, the reduction of the energy purchased from the distribution network jeopardizes the ability of the tariff system to ensure recovery of the total regulated costs. Although various works have captured this concern, most proposals present significant mathematical complexity, contrasting with the simplicity of current practices and limiting its regulatory applicability. This work develops a tariff system that captures the basic elements of distribution systems, trying to maintain the simplicity of current practices, ensuring recovery of the total regulated cost under the penetration of distributed generation, and incentivizing through price signals operational efficiency. A simulation will be presented to discuss numerical results.

Suggested Citation

  • Javier Borquez & Hector Chavez & Karina A. Barbosa & Marcela Jamett & Rodrigo Acuna, 2020. "A Simple Distribution Energy Tariff under the Penetration of DG," Energies, MDPI, vol. 13(8), pages 1-17, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:8:p:1910-:d:345218
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/8/1910/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/8/1910/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Langlois-Bertrand, Simon & Pineau, Pierre-Olivier, 2018. "Pricing the transition: Empirical evidence on the evolution of electricity rate structures in North America," Energy Policy, Elsevier, vol. 117(C), pages 184-197.
    2. Belton, Cameron A. & Lunn, Peter D., 2020. "Smart choices? An experimental study of smart meters and time-of-use tariffs in Ireland," Energy Policy, Elsevier, vol. 140(C).
    3. Cambini, Carlo & Soroush, Golnoush, 2019. "Designing grid tariffs in the presence of distributed generation," Utilities Policy, Elsevier, vol. 61(C).
    4. Nijhuis, M. & Gibescu, M. & Cobben, J.F.G., 2017. "Analysis of reflectivity & predictability of electricity network tariff structures for household consumers," Energy Policy, Elsevier, vol. 109(C), pages 631-641.
    5. Alfredo Nespoli & Emanuele Ogliari & Sonia Leva & Alessandro Massi Pavan & Adel Mellit & Vanni Lughi & Alberto Dolara, 2019. "Day-Ahead Photovoltaic Forecasting: A Comparison of the Most Effective Techniques," Energies, MDPI, vol. 12(9), pages 1-15, April.
    6. Shirazi, Elham & Jadid, Shahram, 2017. "Cost reduction and peak shaving through domestic load shifting and DERs," Energy, Elsevier, vol. 124(C), pages 146-159.
    7. Layer, Patrick & Feurer, Sven & Jochem, Patrick, 2017. "Perceived price complexity of dynamic energy tariffs: An investigation of antecedents and consequences," Energy Policy, Elsevier, vol. 106(C), pages 244-254.
    8. Picciariello, Angela & Vergara, Claudio & Reneses, Javier & Frías, Pablo & Söder, Lennart, 2015. "Electricity distribution tariffs and distributed generation: Quantifying cross-subsidies from consumers to prosumers," Utilities Policy, Elsevier, vol. 37(C), pages 23-33.
    9. Beaufils, Timothé & Pineau, Pierre-Olivier, 2019. "Assessing the impact of residential load profile changes on electricity distribution utility revenues under alternative rate structures," Utilities Policy, Elsevier, vol. 61(C).
    10. Y, Kiguchi & Y, Heo & M, Weeks & R, Choudhary, 2019. "Predicting intra-day load profiles under time-of-use tariffs using smart meter data," Energy, Elsevier, vol. 173(C), pages 959-970.
    11. Diagne, Maimouna & David, Mathieu & Lauret, Philippe & Boland, John & Schmutz, Nicolas, 2013. "Review of solar irradiance forecasting methods and a proposition for small-scale insular grids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 65-76.
    12. Schittekatte, Tim & Momber, Ilan & Meeus, Leonardo, 2018. "Future-proof tariff design: Recovering sunk grid costs in a world where consumers are pushing back," Energy Economics, Elsevier, vol. 70(C), pages 484-498.
    Full references (including those not matched with items on IDEAS)

    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. Vaughan, Jim & Doumen, Sjoerd C. & Kok, Koen, 2023. "Empowering tomorrow, controlling today: A multi-criteria assessment of distribution grid tariff designs," Applied Energy, Elsevier, vol. 341(C).
    2. Timothé Beaufils & Pierre-Olivier Pineau, 2018. "Structures tarifaires et spirale de la mort : État des lieux des pratiques de tarification dans la distribution d’électricité résidentielle," CIRANO Working Papers 2018s-27, CIRANO.
    3. Beaufils, Timothé & Pineau, Pierre-Olivier, 2019. "Assessing the impact of residential load profile changes on electricity distribution utility revenues under alternative rate structures," Utilities Policy, Elsevier, vol. 61(C).
    4. Stute, Judith & Klobasa, Marian, 2024. "How do dynamic electricity tariffs and different grid charge designs interact? - Implications for residential consumers and grid reinforcement requirements," Energy Policy, Elsevier, vol. 189(C).
    5. Ahmed, R. & Sreeram, V. & Mishra, Y. & Arif, M.D., 2020. "A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    6. John Boland & Sleiman Farah & Lei Bai, 2022. "Forecasting of Wind and Solar Farm Output in the Australian National Electricity Market: A Review," Energies, MDPI, vol. 15(1), pages 1-18, January.
    7. Cambini, Carlo & Soroush, Golnoush, 2019. "Designing grid tariffs in the presence of distributed generation," Utilities Policy, Elsevier, vol. 61(C).
    8. Clastres, Cédric & Percebois, Jacques & Rebenaque, Olivier & Solier, Boris, 2019. "Cross subsidies across electricity network users from renewable self-consumption," Utilities Policy, Elsevier, vol. 59(C), pages 1-1.
    9. Bovera, Filippo & Delfanti, Maurizio & Fumagalli, Elena & Lo Schiavo, Luca & Vailati, Riccardo, 2021. "Regulating electricity distribution networks under technological and demand uncertainty," Energy Policy, Elsevier, vol. 149(C).
    10. Günther, Claudia & Schill, Wolf-Peter & Zerrahn, Alexander, 2021. "Prosumage of solar electricity: Tariff design, capacity investments, and power sector effects," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 152.
    11. Peter Cappers & Andrew Satchwell & Will Gorman & Javier Reneses, 2019. "Financial Impacts of Net-Metered Distributed PV on a Prototypical Western Utility’s Shareholders and Ratepayers," Energies, MDPI, vol. 12(24), pages 1-19, December.
    12. Ren, Xiaoying & Zhang, Fei & Zhu, Honglu & Liu, Yongqian, 2022. "Quad-kernel deep convolutional neural network for intra-hour photovoltaic power forecasting," Applied Energy, Elsevier, vol. 323(C).
    13. Lyu, Yuan & He, Yongxiu & Zhou, Jinghan & Xie, Yuxin, 2023. "Prosumer standby fee design: Solving the inequity problem of China's county-wide photovoltaic project promotion," Renewable Energy, Elsevier, vol. 207(C), pages 309-320.
    14. Gunkel, Philipp Andreas & Bergaentzlé, Claire-Marie & Keles, Dogan & Scheller, Fabian & Jacobsen, Henrik Klinge, 2023. "Grid tariff designs to address electrification and their allocative impacts," Utilities Policy, Elsevier, vol. 85(C).
    15. Bergaentzlé, Claire & Jensen, Ida Græsted & Skytte, Klaus & Olsen, Ole Jess, 2019. "Electricity grid tariffs as a tool for flexible energy systems: A Danish case study," Energy Policy, Elsevier, vol. 126(C), pages 12-21.
    16. Christoph Schick & Nikolai Klempp & Kai Hufendiek, 2021. "Impact of Network Charge Design in an Energy System with Large Penetration of Renewables and High Prosumer Shares," Energies, MDPI, vol. 14(21), pages 1-26, October.
    17. Bjarghov, Sigurd & Farahmand, Hossein & Doorman, Gerard, 2022. "Capacity subscription grid tariff efficiency and the impact of uncertainty on the subscribed level," Energy Policy, Elsevier, vol. 165(C).
    18. Hannes Schwarz & Valentin Bertsch & Wolf Fichtner, 2018. "Two-stage stochastic, large-scale optimization of a decentralized energy system: a case study focusing on solar PV, heat pumps and storage in a residential quarter," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(1), pages 265-310, January.
    19. Peter M. Schwarz, Nathan Duma, and Ercument Camadan, 2023. "Compensating Solar Prosumers Using Buy-All, Sell-All as an Alternative to Net Metering and Net Purchasing: Total Use, Rebound, and Cross Subsidization," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    20. Lyu, Yuan & He, Yongxiu & Li, Shanzi & Zhou, Jinghan & Tian, BingYing, 2024. "Channeling approach of prosumer connection costs considering regional differences in China — Evolutionary game among distributed photovoltaic entities," Energy, Elsevier, vol. 289(C).

    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:gam:jeners:v:13:y:2020:i:8:p:1910-:d:345218. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.