Energy Management Strategies

Community and (Non)-Residential Energy Management Strategies Considering Virtual Power Plant and Multi-Carriers Systems

Summary

The implementation of so-called intelligent mechanisms for the management of the behavior of different consumers connected to an electricity distribution system, or even the efficient management of loads, has received increasing attention due to the needs
and the advent of new loads, or distributed production systems, not designed originally to be implemented in the grid, such as electric vehicles (EVs) or the renewable microgeneration. Also, related with the reliability of power systems, a Virtual Power Plant (VPP) is a
network of power generating units as well as flexible consumers and storage systems. The main aim of a VPP is to coordinate its component to provide a reliable overall power supply and optimally participate in the energy market. While several studies have been
conducted for optimal participation of virtual power plants in the electricity market, few works study VPPs in the multi-carrier energy systems (MCES) where multiple energy sectors are coupled with each other to deliver cost-effective energy services to end users.
Considering the last trends of research, and to cope with the emergency needs of decarbonization of power systems, with higher renewable integration, the main research aims to propose new solutions considering the active participation of end-users, integrate
new markets and strategies to increase the flexibility, resilience, and robustness of power systems in a smart grid (SG) paradigm facing the high integration as well of EVs, developing some solutions that also maximize the profit or comfort in all the market players involved.

Research Group: Digital Transformation and Innovation in Organisations (DTIO)

Sustainable Development Goals

7. Affordable and Clean Energy

9. Industry, Innovation and Infrastructure

11. Sustainable Cities and Communities

12. Responsible Production and Consumption

13. Climate Action

Responsible Researcher

Gerardo Silva

Orcid Envelope

Other Researchers

Sérgio Santos

UPT-REMIT, Portugal

Orcid Envelope

João P.S. Catalão

FEUP-SYSTEC, Portugal

Orcid Envelope

João C.O. Matias

UA-GOVCOPP, Portugal

Orcid Envelope

Miadreza Shafie-khah

UVaasa, Finland

Orcid Envelope

Mohammad S. Javadi

INESC-TEC, Portugal

Orcid Envelope

Mohamed Lotfi

SYSTEC-ARISE, Clean Watt, Portugal

Orcid Envelope

Farideh Ghanavati

UA-GOVCOPP, Portugal

Orcid Envelope

Publications

  • Gough, M., Santos, S. F., Almeida, A., Lotfi, M., Javadi, M. S., Fitiwi, D. Z., Osório, G. J., Castro, R., & Catalão, J. P. S. (2022). Blockchain-based transactive energy framework for connected virtual power plants. IEEE Transactions on Industry Applications, 58(1), 986-995. doi: 10.1109/TIA.2021.3131537. http://hdl.handle.net/11328/3913

    Gough, M., Santos, S. F., Lotfi, M., Javadi, M., Osório, G. J., Ashraf, P., Castro, R., & Catalão, J. P. S. (2022). Operation of a technical virtual power plant considering diverse distributed energy resources. IEEE Transactions on Industry Applications, 58(2), 2547-2558. https://doi.org/10.1109/TIA.2022.3143479. http://hdl.handle.net/11328/4063

    Vahid-Ghavidel, M., Javadi, M. S., Santos, S. F., Gough, M., Shafie-khah, M., & Catalão, J. P. S. (2023). Energy storage system impact on the operation of a demand response aggregator. Journal of Energy Storage, 64(107222), 1-9. https://doi.org/10.1016/j.est.2023.107222
    http://hdl.handle.net/11328/4951

    Vahid-Ghavidel, M., Shafie-khah, M., Javadi, M. S., Santos, S. F., Gough, M., Quijano, D. A., & Catalão, J. P. S. (2023). Hybrid IGDT-stochastic self-scheduling of a distributed energy resources aggregator in a multi-energy system. Energy, 265(126289), 1-13. http://hdl.handle.net/11328/4952

    Ferreira, P., Rocha, A., Araujo, M., Afonso, J. L., Antunes, C. H., Lopes, M. A. R., Osório, G. J., Catalão, J. P. S., & Lopes, J. P. (2023). Assessing the societal impact of smart grids: outcomes of a collaborative research project. Technology in Society, 72(102164), 1-14. https://doi.org/10.1016/j.techsoc.2022.102164
    http://hdl.handle.net/11328/4943

    Ramírez-López, S., Gutiérrez-Alcaraz, G., Gough, M., Javadi, M. S., Osório, G. J., & Catalão, J. P. S. (2023).Bi-Level approach for flexibility provision by prosumers in distribution networks. IEEE Transactions on Industry Applications, (Published online: 08 november 2023), 1-10. 10.1109/TIA.2023.3330683. UPT. https://hdl.handle.net/11328/5311

    Monteiro, V., Moreira, C. L., Peças-Lopes, J., Antunes, C. H., Osório, G. J., Catalão, J. P. S., & Afonso, J. L. (2023). A novel three-phase multi-objective unified power quality conditioner. IEEE Transactions on Industrial Electronics, (Published online: 06 february 2023), 1-12. https://doi.org/10.1109/TIE.2023.3241380
    http://hdl.handle.net/11328/4937

    Gough, M., Santos, S. F., Almeida, A., Lotfi, M., Javadi, M. S., Fitiwi, D. Z., Osório, G. J., Castro, R., & Catalão, J. P. S. (2022). Blockchain-based transactive energy framework for connected virtual power plants. IEEE Transactions on Industry Applications, 58(1), 986-995. doi: 10.1109/TIA.2021.3131537. http://hdl.handle.net/11328/3913

    Gough, M., Santos, S. F., Lotfi, M., Javadi, M., Osório, G. J., Ashraf, P., Castro, R., & Catalão, J. P. S. (2022). Operation of a technical virtual power plant considering diverse distributed energy resources. IEEE Transactions on Industry Applications, 58(2), 2547-2558. https://doi.org/10.1109/TIA.2022.3143479
    http://hdl.handle.net/11328/4063

    Jalali, S. M. J., Arora, P., Panigrahi, B. K., Khosravi, A., Najavandi, S., Osório, G. J., & Catalão, J. P. S. (2022). An advanced deep neuroevolution model for probabilistic load forecasting. Electric Power Systems Research, 211(Article ID 108351), 1-7. https://doi.org/10.1016/j.epsr.2022.108351
    Repositório Institucional UPT. http://hdl.handle.net/11328/4374

    Jalali, S. M. J., Osório, G. J., Ahmadian, S., Lotfi, M, Campos, V. M. A, Shafie-khah, M., Khosravi, A., & Catalão, J. P. S. (2022). A new hybrid deep neural architectural search based ensemble reinforcement learning strategy for wind power forecasting. IEEE Transactions on Industry Applications, 58(1), 15-27. doi: 10.1109/TIA.2021.3126272. http://hdl.handle.net/11328/3914

    Lotfi, M., Osório, G. J., Javadi, M. S., El Moursi, M. S., Monteiro, C. & Catalão, J. P. S. (2022). A fully decentralized machine learning algorithm for optimal power flow with cooperative information exchange. International Journal of Electrical Power and Energy Systems, 139, 107990. https://doi.org/10.1016/j.ijepes.2022.107990
    http://hdl.handle.net/11328/4066

    Zhen, Z., Qiu, G., Mei, S., Wang, F., Zhang, X., Yin, R., Li, Y, Osório, G. J., Shafie-khah, M., & Catalão, J. P. S. (2022). An ultra-short-term wind speed forecasting model based on time scale recognition and dynamic adaptive nodeling. International Journal of Electrical Power & Energy Systems, 135(107502). Doi: 10.1016/j.ijepes.2021.107502. http://hdl.handle.net/11328/3707

    Javadi, M. S., Gough, M., Mansouri, S. A, Ahmarinejad, A., Nematbakhsh, E., Santos, S. F., & Catalão, J. P. S. (2022). A two-stage joint operation and planning model for sizing and siting of electrical energy storage devices considering demand response programs. International Journal of Electrical Power & Energy Systems, 138(107912), 1-15. https://doi.org/10.1016/j.ijepes.2021.107912
    http://hdl.handle.net/11328/4424

    Javadi, M. S., Gough, M., Nezhad, A. E., Santos, S. F., Shafie-khah, M., Catalão, J. P. S. (2022). Pool trading model within a local energy community considering flexible loads, photovoltaic generation and energy storage systems. Sustainable Cities and Society, 79(103747), 1-11. https://doi.org/10.1016/j.scs.2022.103747
    http://hdl.handle.net/11328/4425

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