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A smart load management system based on the grasshopper optimization algorithm using the under-frequency load shedding approach

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  • Talaat, M.
  • Hatata, A.Y.
  • Alsayyari, Abdulaziz S.
  • Alblawi, Adel

Abstract

Load management represents one of the main constraints when considering smart grids. In addition, load management is a significant challenge for power system security operations. The smart techniques in load management endow the system with the ability to restore its normal or stable operation after being subjected to any disturbances. When the load exceeds the generation, the system stability is affected, which leads to cascade outages and shutdown of the major parts of the power system, causing the frequency decay effect. Fast load shedding (LS) is the best way to avoid cascading outages and power system blackouts. This paper proposes an innovative, accurate, reliable and fast under-frequency load shedding (UFLS) technique based on the grasshopper optimization algorithm (GOA). LS is considered in this research as a constrained optimization problem. The objective function is to minimize the amount of load shed while maximizing the lowest swing frequency at all stages. To validate the proposed GOA-based UFLS, a comparison with adaptive, particle swarm optimization (PSO) and genetic algorithm (GA) UFLS is carried out for different disturbances. Two different case study systems are considered to test the accuracy and reliability of the proposed algorithm: the IEEE 9-bus and 39-bus systems. The proposed GOA and PSO are coded using the MATLAB environment. Different operating cases involving outage of multiple generators and increasing load are implemented to validate the proposed GOA. The DigSilent power factory software is used as a platform for simulating the power system under study when subjected to different disturbance levels. The results verify the accuracy and reliability of GOA in minimizing the amount of load shed and maximizing the lowest swing frequency while satisfying the constraints. Moreover, GOA achieves a faster solution than PSO and GA.

Suggested Citation

  • Talaat, M. & Hatata, A.Y. & Alsayyari, Abdulaziz S. & Alblawi, Adel, 2020. "A smart load management system based on the grasshopper optimization algorithm using the under-frequency load shedding approach," Energy, Elsevier, vol. 190(C).
    • Handle: RePEc:eee:energy:v:190:y:2020:i:c:s0360544219321188
    DOI: 10.1016/j.energy.2019.116423
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    as
    1. Azzolini, Joseph A. & Tao, Meng, 2018. "A control strategy for improved efficiency in direct-coupled photovoltaic systems through load management," Applied Energy, Elsevier, vol. 231(C), pages 926-936.
    2. Chapaloglou, Spyridon & Nesiadis, Athanasios & Iliadis, Petros & Atsonios, Konstantinos & Nikolopoulos, Nikos & Grammelis, Panagiotis & Yiakopoulos, Christos & Antoniadis, Ioannis & Kakaras, Emmanuel, 2019. "Smart energy management algorithm for load smoothing and peak shaving based on load forecasting of an island’s power system," Applied Energy, Elsevier, vol. 238(C), pages 627-642.
    3. Yu, Dongmin & liu, Huanan & Bresser, Charis, 2018. "Peak load management based on hybrid power generation and demand response," Energy, Elsevier, vol. 163(C), pages 969-985.
    4. Craparo, E.M. & Sprague, J.G., 2019. "Integrated supply- and demand-side energy management for expeditionary environmental control," Applied Energy, Elsevier, vol. 233, pages 352-366.
    5. Talaat, M. & Farahat, M.A. & Elkholy, M.H., 2019. "Renewable power integration: Experimental and simulation study to investigate the ability of integrating wave, solar and wind energies," Energy, Elsevier, vol. 170(C), pages 668-682.
    6. Mehdizadeh, Ali & Taghizadegan, Navid & Salehi, Javad, 2018. "Risk-based energy management of renewable-based microgrid using information gap decision theory in the presence of peak load management," Applied Energy, Elsevier, vol. 211(C), pages 617-630.
    7. Touqeer Ahmed Jumani & Mohd Wazir Mustafa & Madihah Md Rasid & Nayyar Hussain Mirjat & Zohaib Hussain Leghari & M. Salman Saeed, 2018. "Optimal Voltage and Frequency Control of an Islanded Microgrid Using Grasshopper Optimization Algorithm," Energies, MDPI, vol. 11(11), pages 1-20, November.
    8. Parra, David & Norman, Stuart A. & Walker, Gavin S. & Gillott, Mark, 2017. "Optimum community energy storage for renewable energy and demand load management," Applied Energy, Elsevier, vol. 200(C), pages 358-369.
    9. Yu, Dongmin & Zhu, Haoming & Han, Wenqi & Holburn, Daniel, 2019. "Dynamic multi agent-based management and load frequency control of PV/Fuel cell/ wind turbine/ CHP in autonomous microgrid system," Energy, Elsevier, vol. 173(C), pages 554-568.
    10. Yu, Mengmeng & Lu, Renzhi & Hong, Seung Ho, 2016. "A real-time decision model for industrial load management in a smart grid," Applied Energy, Elsevier, vol. 183(C), pages 1488-1497.
    11. Thakur, Jagruti & Chakraborty, Basab, 2016. "Demand side management in developing nations: A mitigating tool for energy imbalance and peak load management," Energy, Elsevier, vol. 114(C), pages 895-912.
    12. Barman, Mayur & Dev Choudhury, N.B. & Sutradhar, Suman, 2018. "A regional hybrid GOA-SVM model based on similar day approach for short-term load forecasting in Assam, India," Energy, Elsevier, vol. 145(C), pages 710-720.
    13. Liu, Hui & Wang, Bin & Wang, Ni & Wu, Qiuwei & Yang, Yude & Wei, Hua & Li, Canbing, 2018. "Enabling strategies of electric vehicles for under frequency load shedding," Applied Energy, Elsevier, vol. 228(C), pages 843-851.
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    2. Talaat, M. & Farahat, M.A. & Mansour, Noura & Hatata, A.Y., 2020. "Load forecasting based on grasshopper optimization and a multilayer feed-forward neural network using regressive approach," Energy, Elsevier, vol. 196(C).
    3. Antans Sauhats & Andrejs Utans & Jurijs Silinevics & Gatis Junghans & Dmitrijs Guzs, 2021. "Enhancing Power System Frequency with a Novel Load Shedding Method Including Monitoring of Synchronous Condensers’ Power Injections," Energies, MDPI, vol. 14(5), pages 1-21, March.
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    6. Hazwani Mohd Rosli & Hazlie Mokhlis & Nurulafiqah Nadzirah Mansor & Norazliani Md Sapari & Syahirah Abd Halim & Li Wang & Mohamad Fani Sulaima, 2023. "A Binary Archimedes Optimization Algorithm and Weighted Sum Method for UFLS in Islanded Distribution Systems Considering the Stability Index and Load Priority," Energies, MDPI, vol. 16(13), pages 1-21, July.
    7. Santiago Bustamante-Mesa & Jorge W. Gonzalez-Sanchez & Sergio D. Saldarriaga-Zuluaga & Jesús M. López-Lezama & Nicolás Muñoz-Galeano, 2024. "Data for Optimal Estimation of Under-Frequency Load Shedding Scheme Parameters by Considering Virtual Inertia Injection," Data, MDPI, vol. 9(6), pages 1-8, June.
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