IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i19p6913-d921064.html
   My bibliography  Save this article

Remuneration Sensitivity Analysis in Prosumer and Aggregator Strategies by Controlling Electric Vehicle Chargers

Author

Listed:
  • Cesar Diaz-Londono

    (Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy
    Departamento de Electronica, Pontificia Universidad Javeriana, Bogota 110321, Colombia)

  • José Vuelvas

    (Departamento de Electronica, Pontificia Universidad Javeriana, Bogota 110321, Colombia)

  • Giambattista Gruosso

    (Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy)

  • Carlos Adrian Correa-Florez

    (Departamento de Electronica, Pontificia Universidad Javeriana, Bogota 110321, Colombia)

Abstract

The efficient use of energy resources is profoundly changing power grid regulation and policy. New forms of power generation coupled with storage and the presence of new, increasingly flexible loads such as electric vehicles enable the development of multi-agent planning systems based on new forms of interaction. For instance, consumers can take advantage of flexibility by interacting directly with the grid or through aggregators that bridge the gap between these end-users and traditional centralised markets. This paper aims to provide insight into the benefits for aggregators and end-users from a financial perspective by proposing a methodology that can be applied to different scenarios. End-users may provide flexibility services related to private vehicle charging stations or battery storage systems. The paper will analyse different remuneration levels for end-users by highlighting the most beneficial scenarios for aggregators and end-users and providing evidence on potential conflict of interests. The numerical results show that some consumers may benefit more from aggregation. This is because if taken individually, consumption habits do not allow the same flexibility when considering clusters of consumers with different behaviour. It is also shown that there are cases in which consumers do not seem to benefit from the presence of intermediate parties. We provide extensive numerical results to gain insight for better decision making.

Suggested Citation

  • Cesar Diaz-Londono & José Vuelvas & Giambattista Gruosso & Carlos Adrian Correa-Florez, 2022. "Remuneration Sensitivity Analysis in Prosumer and Aggregator Strategies by Controlling Electric Vehicle Chargers," Energies, MDPI, vol. 15(19), pages 1-24, September.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:19:p:6913-:d:921064
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/19/6913/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/19/6913/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cohen, Jed J. & Azarova, Valeriya & Kollmann, Andrea & Reichl, Johannes, 2021. "Preferences for community renewable energy investments in Europe," Energy Economics, Elsevier, vol. 100(C).
    2. Cátia Silva & Pedro Faria & Zita Vale, 2019. "Multi-Period Observation Clustering for Tariff Definition in a Weekly Basis Remuneration of Demand Response," Energies, MDPI, vol. 12(7), pages 1-24, April.
    3. Cesar Diaz-Londono & Luigi Colangelo & Fredy Ruiz & Diego Patino & Carlo Novara & Gianfranco Chicco, 2019. "Optimal Strategy to Exploit the Flexibility of an Electric Vehicle Charging Station," Energies, MDPI, vol. 12(20), pages 1-29, October.
    4. Wu, Ying & Wu, Yanpeng & Cimen, Halil & Vasquez, Juan C. & Guerrero, Josep M., 2022. "Towards collective energy Community: Potential roles of microgrid and blockchain to go beyond P2P energy trading," Applied Energy, Elsevier, vol. 314(C).
    5. Vuelvas, José & Ruiz, Fredy & Gruosso, Giambattista, 2018. "Limiting gaming opportunities on incentive-based demand response programs," Applied Energy, Elsevier, vol. 225(C), pages 668-681.
    6. Ramos, Ariana & De Jonghe, Cedric & Gómez, Virginia & Belmans, Ronnie, 2016. "Realizing the smart grid's potential: Defining local markets for flexibility," Utilities Policy, Elsevier, vol. 40(C), pages 26-35.
    7. Venizelou, Venizelos & Philippou, Nikolas & Hadjipanayi, Maria & Makrides, George & Efthymiou, Venizelos & Georghiou, George E., 2018. "Development of a novel time-of-use tariff algorithm for residential prosumer price-based demand side management," Energy, Elsevier, vol. 142(C), pages 633-646.
    8. Iazzolino, Gianpaolo & Sorrentino, Nicola & Menniti, Daniele & Pinnarelli, Anna & De Carolis, Monica & Mendicino, Luca, 2022. "Energy communities and key features emerged from business models review," Energy Policy, Elsevier, vol. 165(C).
    9. Shojaabadi, Saeed & Talavat, Vahid & Galvani, Sadjad, 2022. "A game theory-based price bidding strategy for electric vehicle aggregators in the presence of wind power producers," Renewable Energy, Elsevier, vol. 193(C), pages 407-417.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zahid Ullah & Kaleem Ullah & Cesar Diaz-Londono & Giambattista Gruosso & Abdul Basit, 2023. "Enhancing Grid Operation with Electric Vehicle Integration in Automatic Generation Control," Energies, MDPI, vol. 16(20), pages 1-18, October.
    2. Fei Zeng & Zhinong Wei & Guoqiang Sun & Mingshen Wang & Haiteng Han, 2023. "Frequency Regulation of Electric Vehicle Aggregator Considering User Requirements with Limited Data Collection," Energies, MDPI, vol. 16(2), pages 1-21, January.
    3. Corneliu Marinescu, 2022. "Progress in the Development and Implementation of Residential EV Charging Stations Based on Renewable Energy Sources," Energies, MDPI, vol. 16(1), pages 1-31, December.

    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. Nuñez-Jimenez, Alejandro & Mehta, Prakhar & Griego, Danielle, 2023. "Let it grow: How community solar policy can increase PV adoption in cities," Energy Policy, Elsevier, vol. 175(C).
    2. 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.
    3. Barbara Antonioli Mantegazzini & C?dric Clastres & Laura Wangen, 2022. "Energy communities in Europe: An overview of issues and regulatory and economic solutions," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2022(2), pages 5-23.
    4. Ziras, Charalampos & Heinrich, Carsten & Bindner, Henrik W., 2021. "Why baselines are not suited for local flexibility markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    5. Zhaoming Yang & Qi Xiang & Yuxuan He & Shiliang Peng & Michael Havbro Faber & Enrico Zio & Lili Zuo & Huai Su & Jinjun Zhang, 2023. "Resilience of Natural Gas Pipeline System: A Review and Outlook," Energies, MDPI, vol. 16(17), pages 1-19, August.
    6. D'Adamo, Idiano & Mammetti, Marco & Ottaviani, Dario & Ozturk, Ilhan, 2023. "Photovoltaic systems and sustainable communities: New social models for ecological transition. The impact of incentive policies in profitability analyses," Renewable Energy, Elsevier, vol. 202(C), pages 1291-1304.
    7. Sima, Catalina Alexandra & Popescu, Claudia Laurenta & Popescu, Mihai Octavian & Roscia, Mariacristina & Seritan, George & Panait, Cornel, 2022. "Techno-economic assessment of university energy communities with on/off microgrid," Renewable Energy, Elsevier, vol. 193(C), pages 538-553.
    8. Jicheng Liu & Fangqiu Xu & Shuaishuai Lin & Hua Cai & Suli Yan, 2018. "A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm Optimization," Energies, MDPI, vol. 11(12), pages 1-22, November.
    9. Aliakbari Sani, Sajad & Bahn, Olivier & Delage, Erick, 2022. "Affine decision rule approximation to address demand response uncertainty in smart Grids’ capacity planning," European Journal of Operational Research, Elsevier, vol. 303(1), pages 438-455.
    10. Vladimir Z. Gjorgievski & Nikolas G. Chatzigeorgiou & Venizelos Venizelou & Georgios C. Christoforidis & George E. Georghiou & Grigoris K. Papagiannis, 2020. "Evaluation of Load Matching Indicators in Residential PV Systems-the Case of Cyprus," Energies, MDPI, vol. 13(8), pages 1-18, April.
    11. Sulaima, Mohamad Fani & Dahlan, Nofri Yenita & Yasin, Zuhaila Mat & Rosli, Marlinda Mohd & Omar, Zulkiflee & Hassan, Mohammad Yusri, 2019. "A review of electricity pricing in peninsular Malaysia: Empirical investigation about the appropriateness of Enhanced Time of Use (ETOU) electricity tariff," Renewable and Sustainable Energy Reviews, Elsevier, vol. 110(C), pages 348-367.
    12. Fontecha, John E. & Nikolaev, Alexander & Walteros, Jose L. & Zhu, Zhenduo, 2022. "Scientists wanted? A literature review on incentive programs that promote pro-environmental consumer behavior: Energy, waste, and water," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
    13. Heilmann, Erik, 2023. "The impact of transparency policies on local flexibility markets in electric distribution networks," Utilities Policy, Elsevier, vol. 83(C).
    14. Andruszkiewicz, Jerzy & Lorenc, Józef & Weychan, Agnieszka, 2020. "Seasonal variability of price elasticity of demand of households using zonal tariffs and its impact on hourly load of the power system," Energy, Elsevier, vol. 196(C).
    15. Mousa Mohammed Khubrani & Shadab Alam, 2023. "Blockchain-Based Microgrid for Safe and Reliable Power Generation and Distribution: A Case Study of Saudi Arabia," Energies, MDPI, vol. 16(16), pages 1-34, August.
    16. Marco Badami & Gabriele Fambri & Salvatore Mancò & Mariapia Martino & Ioannis G. Damousis & Dimitrios Agtzidis & Dimitrios Tzovaras, 2019. "A Decision Support System Tool to Manage the Flexibility in Renewable Energy-Based Power Systems," Energies, MDPI, vol. 13(1), pages 1-16, December.
    17. Marius Buchmann, 2019. "How decentralization drives a change of the institutional framework on the distribution grid level in the electricity sector – the case of local congestion markets," Bremen Energy Working Papers 0031, Bremen Energy Research.
    18. Kubli, Merla & Puranik, Sanket, 2023. "A typology of business models for energy communities: Current and emerging design options," Renewable and Sustainable Energy Reviews, Elsevier, vol. 176(C).
    19. Palm, J. & Kojonsaari, A.-R. & Öhrlund, I. & Fowler, N. & Bartusch, C., 2023. "Drivers and barriers to participation in Sweden's local flexibility markets for electricity," Utilities Policy, Elsevier, vol. 82(C).
    20. Lago, Jesus & Poplavskaya, Ksenia & Suryanarayana, Gowri & De Schutter, Bart, 2021. "A market framework for grid balancing support through imbalances trading," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(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:15:y:2022:i:19:p:6913-:d:921064. 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.