IDEAS home Printed from https://ideas.repec.org/a/vrs/poicbe/v16y2022i1p1219-1236n2.html
   My bibliography  Save this article

DR and Aggregators status in CSE Europe

Author

Listed:
  • Puskás-Tompos András

    (The Bucharest University of Economic Studies, Bucharest, Romania)

Abstract

Global warming is one of the biggest challenges of our times. This phenomenon is largely due to the emissions coming from the burning of polluting fossil fuels in the process of electricity generation. In 2019 generation of electricity and heat, together with transportation accounted for more than two thirds of total emissions from fuel combustion. In addition, these sectors were mainly responsible for most of the global growth since 2010. According to the EU’s green vision, Member States have to decrease their CO2 emissions by 55% until 2030, compared to levels from 1990 and by 2050 they have to become carbon neutral. In recent years we could observe positive trends in the increase of green energy generation. The only issue is that by phasing out dispatchable polluting generation and adding non-dispatchable generation units to the electricity grids more demand flexibility is needed. Low-cost solutions to generate the mandatory flexibility necessary for system stability and reliability are Demand Response (DR) programs. The implementation of DR programs usually is made via a new market participant and new service provider entitled aggregators. Aggregators’ main role is to manage directly or indirectly end consumers’ electricity consumption flexibility. Electricity consumers can obtain incentives or can pay less for their electricity bills if they agree to shift or curtail their electricity consumption. In order to promote DR programs, as well as to increase the contribution of aggregators, the EU supports these programs through Directives. Energy Efficiency Directive 2012/27/EU encourages implementation of DR in energy markets, while Directive (EU) 2019/944 defines the independent aggregator. Further, to support these programs, a large-scale smart metre rollout is going on in EU countries. The objective of current research is to analyse the implementation level of DR in Central and South East (CSE) Europe, as well as to provide a comparative analysis in regards of smart metres rollout in developed countries versus those under development. In order to test the hypothesis, during the research the author used qualitative analysis methods such as comparative studies, desk research and case studies. The novelty of this research consists in the presentation of DR programs and aggregators development together with current state in CSE Europe.

Suggested Citation

  • Puskás-Tompos András, 2022. "DR and Aggregators status in CSE Europe," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 16(1), pages 1219-1236, August.
    • Handle: RePEc:vrs:poicbe:v:16:y:2022:i:1:p:1219-1236:n:2
    DOI: 10.2478/picbe-2022-0112
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/picbe-2022-0112
    Download Restriction: no
    File URL: https://libkey.io/10.2478/picbe-2022-0112?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jordehi, A. Rezaee, 2019. "Optimisation of demand response in electric power systems, a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 308-319.
    2. Adrian Tantau & András Puskás-Tompos & Laurentiu Fratila & Costel Stanciu, 2021. "Acceptance of Demand Response and Aggregators as a Solution to Optimize the Relation between Energy Producers and Consumers in order to Increase the Amount of Renewable Energy in the Grid," Energies, MDPI, vol. 14(12), pages 1-19, June.
    3. Nie, Pu-yan & Chen, Zi-rui & Wang, Chan & Chen, Xiao-ling, 2019. "Innovation analysis under trading energy efficiency," Energy, Elsevier, vol. 186(C).
    4. Good, Nicholas, 2019. "Using behavioural economic theory in modelling of demand response," Applied Energy, Elsevier, vol. 239(C), pages 107-116.
    5. Lu, Xiaoxing & Li, Kangping & Xu, Hanchen & Wang, Fei & Zhou, Zhenyu & Zhang, Yagang, 2020. "Fundamentals and business model for resource aggregator of demand response in electricity markets," Energy, Elsevier, vol. 204(C).
    6. Okur, Özge & Voulis, Nina & Heijnen, Petra & Lukszo, Zofia, 2019. "Aggregator-mediated demand response: Minimizing imbalances caused by uncertainty of solar generation," Applied Energy, Elsevier, vol. 247(C), pages 426-437.
    7. Alam, Muhammad Raisul & St-Hilaire, Marc & Kunz, Thomas, 2019. "Peer-to-peer energy trading among smart homes," Applied Energy, Elsevier, vol. 238(C), pages 1434-1443.
    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. Puskás-Tompos András, 2020. "Energy Trading Perspectives in the Digital Era," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 14(1), pages 16-27, July.
    2. Adrian Tantau & András Puskás-Tompos & Laurentiu Fratila & Costel Stanciu, 2021. "Acceptance of Demand Response and Aggregators as a Solution to Optimize the Relation between Energy Producers and Consumers in order to Increase the Amount of Renewable Energy in the Grid," Energies, MDPI, vol. 14(12), pages 1-19, June.
    3. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N., 2022. "Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    4. Adrian Tantau & András Puskás-Tompos & Costel Stanciu & Laurentiu Fratila & Catalin Curmei, 2021. "Key Factors Which Contribute to the Participation of Consumers in Demand Response Programs and Enable the Proliferation of Renewable Energy Sources," Energies, MDPI, vol. 14(24), pages 1-22, December.
    5. Montuori, Lina & Alcázar-Ortega, Manuel, 2021. "Demand response strategies for the balancing of natural gas systems: Application to a local network located in The Marches (Italy)," Energy, Elsevier, vol. 225(C).
    6. Marina Bertolini & Gregorio Morosinotto, 2023. "Business Models for Energy Community in the Aggregator Perspective: State of the Art and Research Gaps," Energies, MDPI, vol. 16(11), pages 1-26, June.
    7. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N. & Burmester, Daniel, 2021. "Strategic design optimisation of multi-energy-storage-technology micro-grids considering a two-stage game-theoretic market for demand response aggregation," Applied Energy, Elsevier, vol. 287(C).
    8. Puskás-Tompos András & Tantau Adrian, 2021. "The role of Aggregators in DSM in the context of Business Digitization," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 15(1), pages 480-493, December.
    9. Gržanić, M. & Capuder, T. & Zhang, N. & Huang, W., 2022. "Prosumers as active market participants: A systematic review of evolution of opportunities, models and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    10. Seatle, Madeleine & McPherson, Madeleine, 2024. "Residential demand response program modelling to compliment grid composition and changes in energy efficiency," Energy, Elsevier, vol. 290(C).
    11. Matthew Gough & Sérgio F. Santos & Mohammed Javadi & Rui Castro & João P. S. Catalão, 2020. "Prosumer Flexibility: A Comprehensive State-of-the-Art Review and Scientometric Analysis," Energies, MDPI, vol. 13(11), pages 1-32, May.
    12. Chen, Xiaodong & Ge, Xinxin & Sun, Rongfu & Wang, Fei & Mi, Zengqiang, 2024. "A SVM based demand response capacity prediction model considering internal factors under composite program," Energy, Elsevier, vol. 300(C).
    13. Kong, Xiangyu & Kong, Deqian & Yao, Jingtao & Bai, Linquan & Xiao, Jie, 2020. "Online pricing of demand response based on long short-term memory and reinforcement learning," Applied Energy, Elsevier, vol. 271(C).
    14. Lin, Jin & Dong, Jun & Dou, Xihao & Liu, Yao & Yang, Peiwen & Ma, Tongtao, 2022. "Psychological insights for incentive-based demand response incorporating battery energy storage systems: A two-loop Stackelberg game approach," Energy, Elsevier, vol. 239(PC).
    15. Morales-España, Germán & Martínez-Gordón, Rafael & Sijm, Jos, 2022. "Classifying and modelling demand response in power systems," Energy, Elsevier, vol. 242(C).
    16. Ieva Pakere & Armands Gravelsins & Girts Bohvalovs & Liga Rozentale & Dagnija Blumberga, 2021. "Will Aggregator Reduce Renewable Power Surpluses? A System Dynamics Approach for the Latvia Case Study," Energies, MDPI, vol. 14(23), pages 1-21, November.
    17. McPherson, Madeleine & Stoll, Brady, 2020. "Demand response for variable renewable energy integration: A proposed approach and its impacts," Energy, Elsevier, vol. 197(C).
    18. Mousavi, Navid & Kothapalli, Ganesh & Habibi, Daryoush & Das, Choton K. & Baniasadi, Ali, 2020. "A novel photovoltaic-pumped hydro storage microgrid applicable to rural areas," Applied Energy, Elsevier, vol. 262(C).
    19. Park, Sung-Won & Zhang, Zhong & Li, Furong & Son, Sung-Yong, 2021. "Peer-to-peer trading-based efficient flexibility securing mechanism to support distribution system stability," Applied Energy, Elsevier, vol. 285(C).
    20. Reza Fachrizal & Joakim Munkhammar, 2020. "Improved Photovoltaic Self-Consumption in Residential Buildings with Distributed and Centralized Smart Charging of Electric Vehicles," Energies, MDPI, vol. 13(5), pages 1-19, March.

    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:vrs:poicbe:v:16:y:2022:i:1:p:1219-1236:n:2. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.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.