IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i8p1987-d160965.html
   My bibliography  Save this article

Distributed Energy Resources Scheduling and Aggregation in the Context of Demand Response Programs

Author

Listed:
  • Pedro Faria

    (GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, 4200-072 Porto, Portugal
    IPP—Polytechnic Institute of Porto, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal)

  • João Spínola

    (GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, 4200-072 Porto, Portugal
    IPP—Polytechnic Institute of Porto, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal)

  • Zita Vale

    (IPP—Polytechnic Institute of Porto, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal)

Abstract

Distributed energy resources can contribute to an improved operation of power systems, improving economic and technical efficiency. However, aggregation of resources is needed to make these resources profitable. The present paper proposes a methodology for distributed resources management by a Virtual Power Player (VPP), addressing the resources scheduling, aggregation and remuneration based on the aggregation made. The aggregation is made using K -means algorithm. The innovative aspect motivating the present paper relies on the remuneration definition considering multiple scenarios of operation, by performing a multi-observation clustering. Resources aggregation and remuneration profiles are obtained for 2592 operation scenarios, considering 548 distributed generators, 20,310 consumers, and 10 suppliers.

Suggested Citation

  • Pedro Faria & João Spínola & Zita Vale, 2018. "Distributed Energy Resources Scheduling and Aggregation in the Context of Demand Response Programs," Energies, MDPI, vol. 11(8), pages 1-17, July.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:8:p:1987-:d:160965
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/8/1987/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/8/1987/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Herrero, Ignacio & Rodilla, Pablo & Batlle, Carlos, 2015. "Electricity market-clearing prices and investment incentives: The role of pricing rules," Energy Economics, Elsevier, vol. 47(C), pages 42-51.
    2. Behboodi, Sahand & Chassin, David P. & Crawford, Curran & Djilali, Ned, 2016. "Renewable resources portfolio optimization in the presence of demand response," Applied Energy, Elsevier, vol. 162(C), pages 139-148.
    3. Balkhair, Khaled S. & Rahman, Khalil Ur, 2017. "Sustainable and economical small-scale and low-head hydropower generation: A promising alternative potential solution for energy generation at local and regional scale," Applied Energy, Elsevier, vol. 188(C), pages 378-391.
    4. Chassin, David P. & Rondeau, Daniel, 2016. "Aggregate modeling of fast-acting demand response and control under real-time pricing," Applied Energy, Elsevier, vol. 181(C), pages 288-298.
    5. Faria, P. & Vale, Z., 2011. "Demand response in electrical energy supply: An optimal real time pricing approach," Energy, Elsevier, vol. 36(8), pages 5374-5384.
    6. Gonzalez-Salazar, Miguel Angel & Venturini, Mauro & Poganietz, Witold-Roger & Finkenrath, Matthias & Kirsten, Trevor & Acevedo, Helmer & Spina, Pier Ruggero, 2016. "Development of a technology roadmap for bioenergy exploitation including biofuels, waste-to-energy and power generation & CHP," Applied Energy, Elsevier, vol. 180(C), pages 338-352.
    7. Siano, Pierluigi & Sarno, Debora, 2016. "Assessing the benefits of residential demand response in a real time distribution energy market," Applied Energy, Elsevier, vol. 161(C), pages 533-551.
    8. Wang, Ge & Zhang, Qi & Li, Hailong & McLellan, Benjamin C. & Chen, Siyuan & Li, Yan & Tian, Yulu, 2017. "Study on the promotion impact of demand response on distributed PV penetration by using non-cooperative game theoretical analysis," Applied Energy, Elsevier, vol. 185(P2), pages 1869-1878.
    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. Tomasz Sikorski & Michal Jasiński & Edyta Ropuszyńska-Surma & Magdalena Węglarz & Dominika Kaczorowska & Paweł Kostyla & Zbigniew Leonowicz & Robert Lis & Jacek Rezmer & Wilhelm Rojewski & Marian Sobi, 2020. "A Case Study on Distributed Energy Resources and Energy-Storage Systems in a Virtual Power Plant Concept: Technical Aspects," Energies, MDPI, vol. 13(12), pages 1-30, June.
    2. Libor Dražan & René Križan & Miroslav Popela, 2021. "Design and Testing of a Low-Tech DEW Generator for Determining Electromagnetic Immunity of Standard Electronic Circuits," Energies, MDPI, vol. 14(11), pages 1-15, May.
    3. Saeid Esmaeili & Amjad Anvari-Moghaddam & Shahram Jadid, 2019. "Optimal Operational Scheduling of Reconfigurable Multi-Microgrids Considering Energy Storage Systems," Energies, MDPI, vol. 12(9), pages 1-23, May.
    4. 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.
    5. Hongwei Li & Qing Xu & Shitao Wang & Huihui Song, 2022. "Peak Shaving Methods of Distributed Generation Clusters Using Dynamic Evaluation and Self-Renewal Mechanism," Energies, MDPI, vol. 15(19), pages 1-17, September.
    6. Michał Jasiński & Tomasz Sikorski & Dominika Kaczorowska & Jacek Rezmer & Vishnu Suresh & Zbigniew Leonowicz & Paweł Kostyła & Jarosław Szymańda & Przemysław Janik & Jacek Bieńkowski & Przemysław Prus, 2021. "A Case Study on a Hierarchical Clustering Application in a Virtual Power Plant: Detection of Specific Working Conditions from Power Quality Data," Energies, MDPI, vol. 14(4), pages 1-13, February.
    7. Konstantinos Kotsalos & Ismael Miranda & Nuno Silva & Helder Leite, 2019. "A Horizon Optimization Control Framework for the Coordinated Operation of Multiple Distributed Energy Resources in Low Voltage Distribution Networks," Energies, MDPI, vol. 12(6), pages 1-27, March.
    8. Pedro Faria & Zita Vale, 2019. "Distributed Energy Resources Management 2018," Energies, MDPI, vol. 13(1), pages 1-4, December.
    9. Abdul Rehman Yasin & Muhammad Ashraf & Aamer Iqbal Bhatti, 2018. "Fixed Frequency Sliding Mode Control of Power Converters for Improved Dynamic Response in DC Micro-Grids," Energies, MDPI, vol. 11(10), pages 1-18, October.
    10. Filipe Marangoni & Leandro Magatão & Lúcia Valéria Ramos de Arruda, 2020. "Demand Response Optimization Model to Energy and Power Expenses Analysis and Contract Revision," Energies, MDPI, vol. 13(11), pages 1-23, June.

    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. Märkle-Huß, Joscha & Feuerriegel, Stefan & Neumann, Dirk, 2018. "Large-scale demand response and its implications for spot prices, load and policies: Insights from the German-Austrian electricity market," Applied Energy, Elsevier, vol. 210(C), pages 1290-1298.
    2. Qi, Wei & Shen, Bo & Zhang, Hongcai & Shen, Zuo-Jun Max, 2017. "Sharing demand-side energy resources - A conceptual design," Energy, Elsevier, vol. 135(C), pages 455-465.
    3. Behboodi, Sahand & Chassin, David P. & Djilali, Ned & Crawford, Curran, 2017. "Interconnection-wide hour-ahead scheduling in the presence of intermittent renewables and demand response: A surplus maximizing approach," Applied Energy, Elsevier, vol. 189(C), pages 336-351.
    4. Zheng, Yingying & Jenkins, Bryan M. & Kornbluth, Kurt & Kendall, Alissa & Træholt, Chresten, 2018. "Optimization of a biomass-integrated renewable energy microgrid with demand side management under uncertainty," Applied Energy, Elsevier, vol. 230(C), pages 836-844.
    5. Hui, Hongxun & Ding, Yi & Liu, Weidong & Lin, You & Song, Yonghua, 2017. "Operating reserve evaluation of aggregated air conditioners," Applied Energy, Elsevier, vol. 196(C), pages 218-228.
    6. Behboodi, Sahand & Chassin, David P. & Djilali, Ned & Crawford, Curran, 2018. "Transactive control of fast-acting demand response based on thermostatic loads in real-time retail electricity markets," Applied Energy, Elsevier, vol. 210(C), pages 1310-1320.
    7. 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).
    8. Hu, Ming-Che & Lu, Su-Ying & Chen, Yen-Haw, 2016. "Stochastic–multiobjective market equilibrium analysis of a demand response program in energy market under uncertainty," Applied Energy, Elsevier, vol. 182(C), pages 500-506.
    9. Innocent Kamwa & Leila Bagherzadeh & Atieh Delavari, 2023. "Integrated Demand Response Programs in Energy Hubs: A Review of Applications, Classifications, Models and Future Directions," Energies, MDPI, vol. 16(11), pages 1-21, May.
    10. Yu, Mengmeng & Hong, Seung Ho, 2017. "Incentive-based demand response considering hierarchical electricity market: A Stackelberg game approach," Applied Energy, Elsevier, vol. 203(C), pages 267-279.
    11. Jun Dong & Rong Li & Hui Huang, 2018. "Performance Evaluation of Residential Demand Response Based on a Modified Fuzzy VIKOR and Scalable Computing Method," Energies, MDPI, vol. 11(5), pages 1-27, April.
    12. Fan, Songli & Ai, Qian & Piao, Longjian, 2018. "Bargaining-based cooperative energy trading for distribution company and demand response," Applied Energy, Elsevier, vol. 226(C), pages 469-482.
    13. Jiang, Bo & Muzhikyan, Aramazd & Farid, Amro M. & Youcef-Toumi, Kamal, 2017. "Demand side management in power grid enterprise control: A comparison of industrial & social welfare approaches," Applied Energy, Elsevier, vol. 187(C), pages 833-846.
    14. Xie, Dunjian & Hui, Hongxun & Ding, Yi & Lin, Zhenzhi, 2018. "Operating reserve capacity evaluation of aggregated heterogeneous TCLs with price signals," Applied Energy, Elsevier, vol. 216(C), pages 338-347.
    15. Wang, Jianxiao & Zhong, Haiwang & Lai, Xiaowen & Xia, Qing & Shu, Chang & Kang, Chongqing, 2017. "Distributed real-time demand response based on Lagrangian multiplier optimal selection approach," Applied Energy, Elsevier, vol. 190(C), pages 949-959.
    16. Du, Y.F. & Jiang, L. & Li, Y.Z. & Counsell, J. & Smith, J.S., 2016. "Multi-objective demand side scheduling considering the operational safety of appliances," Applied Energy, Elsevier, vol. 179(C), pages 864-874.
    17. Wang, Jianxiao & Zhong, Haiwang & Ma, Ziming & Xia, Qing & Kang, Chongqing, 2017. "Review and prospect of integrated demand response in the multi-energy system," Applied Energy, Elsevier, vol. 202(C), pages 772-782.
    18. Kan, Kan & Zhang, Qingying & Xu, Zhe & Zheng, Yuan & Gao, Qiang & Shen, Lian, 2022. "Energy loss mechanism due to tip leakage flow of axial flow pump as turbine under various operating conditions," Energy, Elsevier, vol. 255(C).
    19. Hu, Maomao & Xiao, Fu & Wang, Lingshi, 2017. "Investigation of demand response potentials of residential air conditioners in smart grids using grey-box room thermal model," Applied Energy, Elsevier, vol. 207(C), pages 324-335.
    20. Arshad, Muhammad & Bano, Ijaz & Khan, Nasrullah & Shahzad, Mirza Imran & Younus, Muhammad & Abbas, Mazhar & Iqbal, Munawar, 2018. "Electricity generation from biogas of poultry waste: An assessment of potential and feasibility in Pakistan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1241-1246.

    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:11:y:2018:i:8:p:1987-:d:160965. 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.