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A Review on Optimal Control for the Smart Grid Electrical Substation Enhancing Transition Stability

Author

Listed:
  • Wilson Pavon

    (Department of Electrical Engineering, Universidad Politécnica Salesiana, Quito EC170146, Ecuador)

  • Esteban Inga

    (Department of Electrical Engineering, Universidad Politécnica Salesiana, Quito EC170146, Ecuador)

  • Silvio Simani

    (Engineering Department, Università degli Studi di Ferrara, 050031 Ferrara, Italy)

  • Maddalena Nonato

    (Engineering Department, Università degli Studi di Ferrara, 050031 Ferrara, Italy)

Abstract

This paper is a research article for finding the optimal control of smart power substations for improving the network parameters and reliability. The included papers are the most essential and main studies in the field, which propose a different approach to reach the best performance in electrical power systems. The parameters for improvement are the ability for tracking of the reference signal, stabilizing the system, reducing the error in steady state and controlling the behavior in transient state. The research focuses with the reaching a better transient stability considering voltage and frequency dynamic parameters. The optimal model for the control is focused on minimizing energy consumption but maintaining the controllable parameters, exploring some optimization techniques to find the optimal control, with of aim of minimizing the response time, the energy consumption, and maximizing the reliability by means of improving the controller to be more robust.

Suggested Citation

  • Wilson Pavon & Esteban Inga & Silvio Simani & Maddalena Nonato, 2021. "A Review on Optimal Control for the Smart Grid Electrical Substation Enhancing Transition Stability," Energies, MDPI, vol. 14(24), pages 1-15, December.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:24:p:8451-:d:702603
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    References listed on IDEAS

    as
    1. Vitale, F. & Rispoli, N. & Sorrentino, M. & Rosen, M.A. & Pianese, C., 2021. "On the use of dynamic programming for optimal energy management of grid-connected reversible solid oxide cell-based renewable microgrids," Energy, Elsevier, vol. 225(C).
    2. Adrienn Dineva & Amir Mosavi & Sina Faizollahzadeh Ardabili & Istvan Vajda & Shahaboddin Shamshirband & Timon Rabczuk & Kwok-Wing Chau, 2019. "Review of Soft Computing Models in Design and Control of Rotating Electrical Machines," Energies, MDPI, vol. 12(6), pages 1-28, March.
    3. Adia Khalid & Sheraz Aslam & Khursheed Aurangzeb & Syed Irtaza Haider & Mahmood Ashraf & Nadeem Javaid, 2018. "An Efficient Energy Management Approach Using Fog-as-a-Service for Sharing Economy in a Smart Grid," Energies, MDPI, vol. 11(12), pages 1-17, December.
    4. Alagoz, B. Baykant & Kaygusuz, Asim & Akcin, Murat & Alagoz, Serkan, 2013. "A closed-loop energy price controlling method for real-time energy balancing in a smart grid energy market," Energy, Elsevier, vol. 59(C), pages 95-104.
    5. Bischi, Aldo & Taccari, Leonardo & Martelli, Emanuele & Amaldi, Edoardo & Manzolini, Giampaolo & Silva, Paolo & Campanari, Stefano & Macchi, Ennio, 2014. "A detailed MILP optimization model for combined cooling, heat and power system operation planning," Energy, Elsevier, vol. 74(C), pages 12-26.
    6. Wen, Lulu & Zhou, Kaile & Li, Jun & Wang, Shanyong, 2020. "Modified deep learning and reinforcement learning for an incentive-based demand response model," Energy, Elsevier, vol. 205(C).
    7. Colak, Ilhami & Kabalci, Ersan & Fulli, Gianluca & Lazarou, Stavros, 2015. "A survey on the contributions of power electronics to smart grid systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 562-579.
    8. Stoppato, Anna & Cavazzini, Giovanna & Ardizzon, Guido & Rossetti, Antonio, 2014. "A PSO (particle swarm optimization)-based model for the optimal management of a small PV(Photovoltaic)-pump hydro energy storage in a rural dry area," Energy, Elsevier, vol. 76(C), pages 168-174.
    9. Bilal Naji Alhasnawi & Basil H. Jasim & Walid Issa & Amjad Anvari-Moghaddam & Frede Blaabjerg, 2020. "A New Robust Control Strategy for Parallel Operated Inverters in Green Energy Applications," Energies, MDPI, vol. 13(13), pages 1-31, July.
    10. Bingda Zhang & Yanjie Wu & Zhao Jin & Yang Wang, 2017. "A Real-Time Digital Solver for Smart Substation Based on Orders," Energies, MDPI, vol. 10(11), pages 1-16, November.
    11. Zhang, Yan & Meng, Fanlin & Wang, Rui & Kazemtabrizi, Behzad & Shi, Jianmai, 2019. "Uncertainty-resistant stochastic MPC approach for optimal operation of CHP microgrid," Energy, Elsevier, vol. 179(C), pages 1265-1278.
    12. Yang, Jun & Su, Changqi, 2021. "Robust optimization of microgrid based on renewable distributed power generation and load demand uncertainty," Energy, Elsevier, vol. 223(C).
    13. Jaume Miret & José Luís García de Vicuña & Ramón Guzmán & Antonio Camacho & Mohammad Moradi Ghahderijani, 2017. "A Flexible Experimental Laboratory for Distributed Generation Networks Based on Power Inverters," Energies, MDPI, vol. 10(10), pages 1-27, October.
    14. Guo, Chenyu & Wang, Xin & Zheng, Yihui & Zhang, Feng, 2022. "Real-time optimal energy management of microgrid with uncertainties based on deep reinforcement learning," Energy, Elsevier, vol. 238(PC).
    15. Mirakhorli, Amin & Dong, Bing, 2018. "Model predictive control for building loads connected with a residential distribution grid," Applied Energy, Elsevier, vol. 230(C), pages 627-642.
    16. Gomes, I.L.R. & Melicio, R. & Mendes, V.M.F., 2021. "A novel microgrid support management system based on stochastic mixed-integer linear programming," Energy, Elsevier, vol. 223(C).
    17. Marzal, Silvia & Salas, Robert & González-Medina, Raúl & Garcerá, Gabriel & Figueres, Emilio, 2018. "Current challenges and future trends in the field of communication architectures for microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3610-3622.
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    Cited by:

    1. Wilson Pavon & Esteban Inga & Silvio Simani & Matthew Armstrong, 2023. "Optimal Hierarchical Control for Smart Grid Inverters Using Stability Margin Evaluating Transient Voltage for Photovoltaic System," Energies, MDPI, vol. 16(5), pages 1-16, March.
    2. Marvin Lema & Wilson Pavon & Leony Ortiz & Ama Baduba Asiedu-Asante & Silvio Simani, 2022. "Controller Coordination Strategy for DC Microgrid Using Distributed Predictive Control Improving Voltage Stability," Energies, MDPI, vol. 15(15), pages 1-15, July.
    3. Francisco Durán & Wilson Pavón & Luis Ismael Minchala, 2024. "Forecast-Based Energy Management for Optimal Energy Dispatch in a Microgrid," Energies, MDPI, vol. 17(2), pages 1-21, January.
    4. Mohammed Said Jouda & Nihan Kahraman, 2022. "Improved Optimal Control of Transient Power Sharing in Microgrid Using H-Infinity Controller with Artificial Bee Colony Algorithm," Energies, MDPI, vol. 15(3), pages 1-26, January.
    5. Miroslaw Parol & Jacek Wasilewski & Tomasz Wojtowicz & Bartlomiej Arendarski & Przemyslaw Komarnicki, 2022. "Reliability Analysis of MV Electric Distribution Networks Including Distributed Generation and ICT Infrastructure," Energies, MDPI, vol. 15(14), pages 1-34, July.

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