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Innovative network pricing to support the transition to a smart grid in a low-carbon economy

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  • Faerber, Laura Antonia
  • Balta-Ozkan, Nazmiye
  • Connor, Peter M.

Abstract

This paper outlines how current distribution network pricing can be revised to enable transition to a smart grid in a low-carbon economy. Using insights from expert interviews, it highlights multiple trade-offs between innovative pricing approaches and regulatory principles which might be resolved by a political decision on how the costs should be recovered or socialised. It then identifies four essentials for a successful implementation of a new mechanism: (i) Closer collaboration between TSO and DNO/DSO concerning local dispatch to improve system efficiency. (ii) Installation of smart meters to collect data providing information about the actual contribution to the grid utilisation of each customer. (iii) Intensified cooperation between supplier and DNO/DSO to pass-through the price signal on the electricity bill. (iv) A legislative framework to facilitate data sharing and data management and communication among network stakeholders – essentially a relaxation of current privacy legislation as an enabler for new approaches to network management, and potentially to reduce costs to the consumer. This suggests the focus for future network pricing should be on services and functions provided by the grid rather than on the commodity power itself.

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  • Faerber, Laura Antonia & Balta-Ozkan, Nazmiye & Connor, Peter M., 2018. "Innovative network pricing to support the transition to a smart grid in a low-carbon economy," Energy Policy, Elsevier, vol. 116(C), pages 210-219.
  • Handle: RePEc:eee:enepol:v:116:y:2018:i:c:p:210-219
    DOI: 10.1016/j.enpol.2018.02.010
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    2. Diestelmeier, Lea, 2019. "Changing power: Shifting the role of electricity consumers with blockchain technology – Policy implications for EU electricity law," Energy Policy, Elsevier, vol. 128(C), pages 189-196.
    3. Marques, Vítor & Costa, Paulo Moisés & Bento, Nuno, 2022. "Greater than the sum: On regulating innovation in electricity distribution networks with externalities," Utilities Policy, Elsevier, vol. 79(C).
    4. Neetzow, Paul & Mendelevitch, Roman & Siddiqui, Sauleh, 2019. "Modeling coordination between renewables and grid: Policies to mitigate distribution grid constraints using residential PV-battery systems," Energy Policy, Elsevier, vol. 132(C), pages 1017-1033.
    5. Kozera, Agnieszka & Satoła, Łukasz & Standar, Aldona & Dworakowska-Raj, Małgorzata, 2022. "Regional diversity of low-carbon investment support from EU funds in the 2014–2020 financial perspective based on the example of Polish municipalities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    6. Liu, Yong, 2019. "Enacting a low-carbon economy: Policies and distrust between government employees and enterprises in China," Energy Policy, Elsevier, vol. 130(C), pages 130-138.
    7. Satoshi Nakano & Ayu Washizu, 2021. "Analysis of inter-regional effects caused by the wide-area operation of the power grid in Japan: an implication for carbon pricing schemes," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 23(3), pages 535-556, July.
    8. Miguel Manuel de Villena & Raphael Fonteneau & Axel Gautier & Damien Ernst, 2019. "Evaluating the Evolution of Distribution Networks under Different Regulatory Frameworks with Multi-Agent Modelling," Energies, MDPI, vol. 12(7), pages 1-15, March.
    9. Mirzania, Pegah & Balta-Ozkan, Nazmiye & Ford, Andy, 2020. "An innovative viable model for community-owned solar PV projects without FIT: Comprehensive techno-economic assessment," Energy Policy, Elsevier, vol. 146(C).
    10. Hongyan Ma, 2021. "The role of clustering algorithm-based big data processing in information economy development," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-14, March.
    11. 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.
    12. Xuefeng Liu & Li Ma, 2023. "Sustainable Development of Business Economy Based on Big Data Algorithm under the Background of Low-Carbon Economy," Sustainability, MDPI, vol. 15(7), pages 1-16, March.

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