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Techno-Economic Green Optimization of Electrical Microgrid Using Swarm Metaheuristics

Author

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  • Khaled Guerraiche

    (LDREI Laboratory, Department of Electrical Engineering, Higher School of Electrical Engineering and Energetic of Oran, Oran 31000, Algeria)

  • Latifa Dekhici

    (LDREI Laboratory, Department of Electrical Engineering, Higher School of Electrical Engineering and Energetic of Oran, Oran 31000, Algeria
    Department of Computer Sciences, University of Sciences and the Technology of Oran (USTO-MB), Oran 31000, Algeria)

  • Eric Chatelet

    (UR InSyTE, Université de Technologie de Troyes, 12 Rue Marie Curie, CS 42060, 10004 Troyes, France)

  • Abdelkader Zeblah

    (Department of Electrical Engineering, Engineering Faculty, University of Sidi Bel Abbes, Sidi Bel Abbès 22000, Algeria)

Abstract

In electrical power engineering, elements such as reliability analysis, modeling, and optimization for complex systems are of the utmost importance. Although there exist myriad studies regarding reliability optimization with conventional methods, researchers are still seeking to find more efficient and accurate methods to address the issue of the redundancy allocation problem. To that effect, an ideal power energy management approach is put forward for the operation of a hybrid microgrid system with different kinds of productions. In the present study, we suggest three algorithms in order to optimize the series-parallel power energy system: the Firefly (FA), Bat (BA), and Interior Search (ISA) algorithms. Moreover, the reliability estimate of the system is solved with the Ushakov algorithm (UMGF). The components may completely fail, which decreases their performance rate. Furthermore, the optimization results are achieved using objective functions that include the total cost of the system, emission gases (NO X , SO 2 , and CO 2 ) of the power production from fuel cells, diesel generators, and gas turbines, and take into consideration the dependability indices. Devices used in power subsystems are characterized based on their dependabilities, performances, capital costs, and maintenance costs. Reliability hinges on a functioning system, which naturally entails meeting customer demand; as a result, it is influenced by the accumulated batch curve. This method provides an idea with regards to the economic cost optimization of microgrid systems. Finally, we present the results of numeric simulations.

Suggested Citation

  • Khaled Guerraiche & Latifa Dekhici & Eric Chatelet & Abdelkader Zeblah, 2023. "Techno-Economic Green Optimization of Electrical Microgrid Using Swarm Metaheuristics," Energies, MDPI, vol. 16(4), pages 1-19, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:1803-:d:1065412
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    References listed on IDEAS

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    1. He, Liangce & Lu, Zhigang & Zhang, Jiangfeng & Geng, Lijun & Zhao, Hao & Li, Xueping, 2018. "Low-carbon economic dispatch for electricity and natural gas systems considering carbon capture systems and power-to-gas," Applied Energy, Elsevier, vol. 224(C), pages 357-370.
    2. Mulleriyawage, U.G.K. & Shen, W.X., 2020. "Optimally sizing of battery energy storage capacity by operational optimization of residential PV-Battery systems: An Australian household case study," Renewable Energy, Elsevier, vol. 160(C), pages 852-864.
    3. Sonja Kallio & Monica Siroux, 2023. "Exergy and Exergy-Economic Approach to Evaluate Hybrid Renewable Energy Systems in Buildings," Energies, MDPI, vol. 16(3), pages 1-22, January.
    4. Du, Mengyu & Li, Yan-Fu, 2020. "An investigation of new local search strategies in memetic algorithm for redundancy allocation in multi-state series-parallel systems," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    5. Holger C. Hesse & Rodrigo Martins & Petr Musilek & Maik Naumann & Cong Nam Truong & Andreas Jossen, 2017. "Economic Optimization of Component Sizing for Residential Battery Storage Systems," Energies, MDPI, vol. 10(7), pages 1-19, June.
    6. Attar, Ahmad & Raissi, Sadigh & Khalili-Damghani, Kaveh, 2017. "A simulation-based optimization approach for free distributed repairable multi-state availability-redundancy allocation problems," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 177-191.
    7. Flores, Robert J. & Brouwer, Jacob, 2018. "Optimal design of a distributed energy resource system that economically reduces carbon emissions," Applied Energy, Elsevier, vol. 232(C), pages 119-138.
    8. Bao, Minglei & Ding, Yi & Yin, Xunhu & Shao, Changzheng & Ye, Chenjin, 2021. "Definitions and Reliability Evaluation of Multi-state Systems Considering State Transition Process and its Application for Gas Systems," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    9. Xu, Yue & Pi, Dechang & Yang, Shengxiang & Chen, Yang, 2021. "A novel discrete bat algorithm for heterogeneous redundancy allocation of multi-state systems subject to probabilistic common-cause failure," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    10. Wang, Rui & Li, Guozheng & Ming, Mengjun & Wu, Guohua & Wang, Ling, 2017. "An efficient multi-objective model and algorithm for sizing a stand-alone hybrid renewable energy system," Energy, Elsevier, vol. 141(C), pages 2288-2299.
    11. Liu, Mingli & Wang, Dan & Zhao, Jiangbin & Si, Shubin, 2022. "Importance measure construction and solving algorithm oriented to the cost-constrained reliability optimization model," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    12. Yeh, Wei-Chang, 2022. "BAT-based algorithm for finding all Pareto solutions of the series-parallel redundancy allocation problem with mixed components," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    13. Khaled Guerraiche & Latifa Dekhici & Eric Chatelet & Abdelkader Zeblah, 2021. "Multi-Objective Electrical Power System Design Optimization Using a Modified Bat Algorithm," Energies, MDPI, vol. 14(13), pages 1-19, July.
    14. Eryilmaz, Serkan, 2018. "Reliability analysis of multi-state system with three-state components and its application to wind energy," Reliability Engineering and System Safety, Elsevier, vol. 172(C), pages 58-63.
    15. Korjani, Saman & Casu, Fabio & Damiano, Alfonso & Pilloni, Virginia & Serpi, Alessandro, 2022. "An online energy management tool for sizing integrated PV-BESS systems for residential prosumers," Applied Energy, Elsevier, vol. 313(C).
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    Cited by:

    1. Mahmoud A. Elsadd & Ahmed F. Zobaa & Heba A. Khattab & Ahmed M. Abd El Aziz & Tamer Fetouh, 2023. "Communicationless Overcurrent Relays Coordination for Active Distribution Network Considering Fault Repairing Periods," Energies, MDPI, vol. 16(23), pages 1-32, November.
    2. Seyed Mohammad Sharifhosseini & Taher Niknam & Mohammad Hossein Taabodi & Habib Asadi Aghajari & Ehsan Sheybani & Giti Javidi & Motahareh Pourbehzadi, 2024. "Investigating Intelligent Forecasting and Optimization in Electrical Power Systems: A Comprehensive Review of Techniques and Applications," Energies, MDPI, vol. 17(21), pages 1-35, October.

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