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Optimization of DC, AC, and Hybrid AC/DC Microgrid-Based IoT Systems: A Review

Author

Listed:
  • Belqasem Aljafari

    (Department of Electrical Engineering, Najran University, Najran 11001, Saudi Arabia)

  • Subramanian Vasantharaj

    (School of Electrical Engineering, Vellore Institute of Technology, Vellore City 632014, India)

  • Vairavasundaram Indragandhi

    (School of Electrical Engineering, Vellore Institute of Technology, Vellore City 632014, India)

  • Rhanganath Vaibhav

    (School of Mechanical Engineering, Vellore Institute of Technology, Vellore City 632014, India)

Abstract

Smart microgrids, as the foundations of the future smart grid, combine distinct Internet of Things (IoT) designs and technologies for applications that are designed to create, regulate, monitor, and protect the microgrid (MG), particularly as the IoT develops and evolves on a daily basis. A smart MG is a small grid that may operate individually or in tandem with the electric grid, and it is ideal for institutional, commercial, and industrial consumers, as well as urban and rural societies. A MG can operate in two methods (stand-alone and grid-connected), with the ability to transition between modes due to local grid faults, planned maintenance, expansions, deficits and failures in the host system, and other factors. Energy storage is the process of storing and converting energy that can be used for a variety of purposes, including voltage and frequency management, power backup, and cost optimization. IoT is designed to deliver solutions for optimal energy management, security protocols, control methods, and applications in the MG, with numerous distributed energy resources (DER) and interconnected loads. The use of IoT architecture for MG operations and controls is discussed in this research. With the use of power grid equipment and IoT-enabled technology, MGs are enabling local networks to give additional services on top of the essential supply of electricity to local networks that operate simultaneously or independently from the regional grid. Additionally, this review shows how hybrid AC/DC MGs are advantageous compared to AC and DC MGs. The state-of-the-art optimization techniques and trends in hybrid MG research are included in this work.

Suggested Citation

  • Belqasem Aljafari & Subramanian Vasantharaj & Vairavasundaram Indragandhi & Rhanganath Vaibhav, 2022. "Optimization of DC, AC, and Hybrid AC/DC Microgrid-Based IoT Systems: A Review," Energies, MDPI, vol. 15(18), pages 1-30, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:18:p:6813-:d:917961
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    as
    1. Akorede, Mudathir Funsho & Hizam, Hashim & Pouresmaeil, Edris, 2010. "Distributed energy resources and benefits to the environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(2), pages 724-734, February.
    2. Zhou, Wei & Lou, Chengzhi & Li, Zhongshi & Lu, Lin & Yang, Hongxing, 2010. "Current status of research on optimum sizing of stand-alone hybrid solar-wind power generation systems," Applied Energy, Elsevier, vol. 87(2), pages 380-389, February.
    3. Mohammadi, Sirus & Mozafari, Babak & Solimani, Soodabeh & Niknam, Taher, 2013. "An Adaptive Modified Firefly Optimisation Algorithm based on Hong's Point Estimate Method to optimal operation management in a microgrid with consideration of uncertainties," Energy, Elsevier, vol. 51(C), pages 339-348.
    4. Irina Albãstroiu & Calcedonia Enache & Andrei Cepoi & Adrian Istrate & Teodora Liliana Andrei, 2021. "Adopting IoT-Based Solutions for Smart Homes. The Perspective of the Romanian Users," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(57), pages 325-325.
    5. Hirsch, Adam & Parag, Yael & Guerrero, Josep, 2018. "Microgrids: A review of technologies, key drivers, and outstanding issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 402-411.
    6. Khalid, M. & Savkin, A.V., 2014. "Minimization and control of battery energy storage for wind power smoothing: Aggregated, distributed and semi-distributed storage," Renewable Energy, Elsevier, vol. 64(C), pages 105-112.
    7. Ma, Xiandong & Wang, Yifei & Qin, Jianrong, 2013. "Generic model of a community-based microgrid integrating wind turbines, photovoltaics and CHP generations," Applied Energy, Elsevier, vol. 112(C), pages 1475-1482.
    8. Azaza, Maher & Wallin, Fredrik, 2017. "Multi objective particle swarm optimization of hybrid micro-grid system: A case study in Sweden," Energy, Elsevier, vol. 123(C), pages 108-118.
    9. Liu, Hui & Chen, Chao, 2019. "Data processing strategies in wind energy forecasting models and applications: A comprehensive review," Applied Energy, Elsevier, vol. 249(C), pages 392-408.
    10. Fuentes, M. & Vivar, M. & Hosein, H. & Aguilera, J. & Muñoz-Cerón, E., 2018. "Lessons learned from the field analysis of PV installations in the Saharawi refugee camps after 10 years of operation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 100-109.
    11. Vahidinasab, Vahid, 2014. "Optimal distributed energy resources planning in a competitive electricity market: Multiobjective optimization and probabilistic design," Renewable Energy, Elsevier, vol. 66(C), pages 354-363.
    12. Kirubakaran, A. & Jain, Shailendra & Nema, R.K., 2009. "A review on fuel cell technologies and power electronic interface," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(9), pages 2430-2440, December.
    13. Abu-Sharkh, S. & Arnold, R.J. & Kohler, J. & Li, R. & Markvart, T. & Ross, J.N. & Steemers, K. & Wilson, P. & Yao, R., 2006. "Can microgrids make a major contribution to UK energy supply?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(2), pages 78-127, April.
    14. Zhang, Xiongwen & Tan, Siew-Chong & Li, Guojun & Li, Jun & Feng, Zhenping, 2013. "Components sizing of hybrid energy systems via the optimization of power dispatch simulations," Energy, Elsevier, vol. 52(C), pages 165-172.
    15. Shaukat, N. & Ali, S.M. & Mehmood, C.A. & Khan, B. & Jawad, M. & Farid, U. & Ullah, Z. & Anwar, S.M. & Majid, M., 2018. "A survey on consumers empowerment, communication technologies, and renewable generation penetration within Smart Grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1453-1475.
    16. Maheri, Alireza, 2014. "Multi-objective design optimisation of standalone hybrid wind-PV-diesel systems under uncertainties," Renewable Energy, Elsevier, vol. 66(C), pages 650-661.
    17. Grigorios Kakkavas & Despoina Gkatzioura & Vasileios Karyotis & Symeon Papavassiliou, 2020. "A Review of Advanced Algebraic Approaches Enabling Network Tomography for Future Network Infrastructures," Future Internet, MDPI, vol. 12(2), pages 1-27, January.
    18. Cassola, Federico & Burlando, Massimiliano, 2012. "Wind speed and wind energy forecast through Kalman filtering of Numerical Weather Prediction model output," Applied Energy, Elsevier, vol. 99(C), pages 154-166.
    19. Senthil Kumar, J. & Charles Raja, S. & Jeslin Drusila Nesamalar, J. & Venkatesh, P., 2018. "Optimizing renewable based generations in AC/DC microgrid system using hybrid Nelder-Mead – Cuckoo Search algorithm," Energy, Elsevier, vol. 158(C), pages 204-215.
    20. Ekren, Orhan & Ekren, Banu Yetkin, 2008. "Size optimization of a PV/wind hybrid energy conversion system with battery storage using response surface methodology," Applied Energy, Elsevier, vol. 85(11), pages 1086-1101, November.
    21. Javed, Muhammad Shahzad & Song, Aotian & Ma, Tao, 2019. "Techno-economic assessment of a stand-alone hybrid solar-wind-battery system for a remote island using genetic algorithm," Energy, Elsevier, vol. 176(C), pages 704-717.
    22. Walter Gil-González & Oscar Danilo Montoya & Luis Fernando Grisales-Noreña & Fernando Cruz-Peragón & Gerardo Alcalá, 2020. "Economic Dispatch of Renewable Generators and BESS in DC Microgrids Using Second-Order Cone Optimization," Energies, MDPI, vol. 13(7), pages 1-15, April.
    23. Elma, Onur & Selamogullari, Ugur Savas, 2012. "A comparative sizing analysis of a renewable energy supplied stand-alone house considering both demand side and source side dynamics," Applied Energy, Elsevier, vol. 96(C), pages 400-408.
    24. Muhammad Omer Khan & Saeed Zaman Jamali, & Chul-Ho Noh & Gi-Hyeon Gwon & Chul-Hwan Kim, 2018. "A Load Flow Analysis for AC/DC Hybrid Distribution Network Incorporated with Distributed Energy Resources for Different Grid Scenarios," Energies, MDPI, vol. 11(2), pages 1-15, February.
    25. Gerber, Daniel L. & Liou, Richard & Brown, Richard, 2019. "Energy-saving opportunities of direct-DC loads in buildings," Applied Energy, Elsevier, vol. 248(C), pages 274-287.
    26. Touqeer Ahmed Jumani & Mohd Wazir Mustafa & Nawaf N. Hamadneh & Samer H. Atawneh & Madihah Md. Rasid & Nayyar Hussain Mirjat & Muhammad Akram Bhayo & Ilyas Khan, 2020. "Computational Intelligence-Based Optimization Methods for Power Quality and Dynamic Response Enhancement of ac Microgrids," Energies, MDPI, vol. 13(16), pages 1-22, August.
    27. Salameh, Tareq & Ghenai, Chaouki & Merabet, Adel & Alkasrawi, Malek, 2020. "Techno-economical optimization of an integrated stand-alone hybrid solar PV tracking and diesel generator power system in Khorfakkan, United Arab Emirates," Energy, Elsevier, vol. 190(C).
    28. Abdelkader, Abbassi & Rabeh, Abbassi & Mohamed Ali, Dami & Mohamed, Jemli, 2018. "Multi-objective genetic algorithm based sizing optimization of a stand-alone wind/PV power supply system with enhanced battery/supercapacitor hybrid energy storage," Energy, Elsevier, vol. 163(C), pages 351-363.
    29. Lucheroni, Carlo & Boland, John & Ragno, Costantino, 2019. "Scenario generation and probabilistic forecasting analysis of spatio-temporal wind speed series with multivariate autoregressive volatility models," Applied Energy, Elsevier, vol. 239(C), pages 1226-1241.
    30. Zhang, Jie & Draxl, Caroline & Hopson, Thomas & Monache, Luca Delle & Vanvyve, Emilie & Hodge, Bri-Mathias, 2015. "Comparison of numerical weather prediction based deterministic and probabilistic wind resource assessment methods," Applied Energy, Elsevier, vol. 156(C), pages 528-541.
    31. Zuluaga, Carlos D. & Álvarez, Mauricio A. & Giraldo, Eduardo, 2015. "Short-term wind speed prediction based on robust Kalman filtering: An experimental comparison," Applied Energy, Elsevier, vol. 156(C), pages 321-330.
    32. Dusonchet, L. & Telaretti, E., 2015. "Comparative economic analysis of support policies for solar PV in the most representative EU countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 986-998.
    33. Abbes, Dhaker & Martinez, André & Champenois, Gérard, 2014. "Life cycle cost, embodied energy and loss of power supply probability for the optimal design of hybrid power systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 98(C), pages 46-62.
    34. Neef, H.-J., 2009. "International overview of hydrogen and fuel cell research," Energy, Elsevier, vol. 34(3), pages 327-333.
    35. Zhang, Shuwei & Bauer, Nico & Luderer, Gunnar & Kriegler, Elmar, 2014. "Role of technologies in energy-related CO2 mitigation in China within a climate-protection world: A scenarios analysis using REMIND," Applied Energy, Elsevier, vol. 115(C), pages 445-455.
    36. Perera, A.T.D. & Attalage, R.A. & Perera, K.K.C.K. & Dassanayake, V.P.C., 2013. "A hybrid tool to combine multi-objective optimization and multi-criterion decision making in designing standalone hybrid energy systems," Applied Energy, Elsevier, vol. 107(C), pages 412-425.
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