IMPROVED PSO ALGORITHM APPLICATION RESEARCH FOR NEW ENERGY CONSUMPTION IN MICROGRID COMBINATION OPTIMISATION MODEL, 1-11.

Guodong Wu, Diangang Hu, Lijuan Liu, and Guangqing Bao

References

  1. [1] B. Zhou, J. Zou, and C.Y. Chung, Multi-microgrid energymanagement systems: architecture, communication, andscheduling strategies, Journal of Modern Power Systems andClean Energy, 9(3), 2021, 463–476.
  2. [2] K. Rajesh and R. Jenitha, Radial basis function neural networkMPPT controller-based microgrid for hybrid stand-aloneenergy system used for irrigation, Circuit World, 49(2), 2023,251–266.
  3. [3] T. Le and B.L.N. Phung, Load shedding in microgrids withconsideration of voltage quality improvement, Engineering,Technology and Applied Science Research, 11(1), 2021,6680–6686.
  4. [4] C. Ndukwe, M.T. Iqbal, and X. Liang, LoRa-based communi-cation system for data transfer in microgrids, AIMS Electronicsand Electrical Engineering, 4(3), 2020, 303–325.
  5. [5] C. Cepeda, C. Orozco, and W. Percybrooks, Intelligent faultdetection system for microgrids, Energies, 13(5), 2020, 1223.
  6. [6] D. An, Q. Yang, and W. Yu, LoPrO: Location privacy-preserving Online auction scheme for electric vehicles jointbidding and charging, Future Generation Computer Systems,107(6), 2020, 394–407.
  7. [7] E. Masuda, Y. Matsuda, and Y. Wakasa, Solution to DC optimalpower flow problems with demand response via distributedasynchronous primal-dual algorithms, SICE Journal ofControl Measurement and System Integration, 13(3), 2020,66–72.
  8. [8] S. Ghaemi and J. Salehi, Assessment of flexibility indexintegration into the expansion planning of clean powerresources and energy storage systems in modern distributionnetwork using benders decomposition, IET Renewable PowerGeneration, 14(2), 2020, 231–242.
  9. [9] R. Krishna, H. Sathish, and N. Zhou, Forecasting uncertaintyparameters of virtual power plants using decision treealgorithm, Electric Power Components and Systems, 51(16),2023, 1756–1769.
  10. [10] S. Zeinal-Kheiri, S. Ghassem-Zadeh, and A.M. Shotorbani,Real-time energy management in a microgrid with renewablegeneration, energy storages, flexible loads and combined heatand power units using Lyapunov optimisation, IET RenewablePower Generation, 14(4), 2020, 526–538.
  11. [11] X. Wu, Y. Yang, S. Han, Z. Zhao, P. Fang, and Q. Gao, Multi-objective optimization method for nuclear reactor radiationshielding design based on PSO algorithm, Annals of NuclearEnergy, 160, 2021, 108404.1–108404.12.
  12. [12] M. Abbaszadeh, S. Soltani-Mohammadi, and A.N. Ahmed.Optimization of support vector machine parameters in modelingof IJU deposit mineralization and alteration zones usingparticle swarm optimization algorithm and grid search method.Computers & Geosciences, 165, 2022, 105140.1–105140.13.
  13. [13] Y. Chen, Z. Ding, M. Zhang, J. Zhou, M. Li, M. Zhao, and J.Wang, Metasurface parameter optimization of Fano resonancebased on a BP-PSO algorithm, Applied Optics,60(29), 2021,9200–9204.
  14. [14] S. Singh, P. Chauhan, and N.J. Singh, Capacity optimization ofgrid connected solar/fuel cell energy system using hybrid ABC-PSO algorithm, International Journal of Hydrogen Energy,45(16), 2020, 10070–10088.
  15. [15] A.M. Shaaban, C. Anitescu, E. Atroshchenko, and T. Rabczuk,Shape optimization by conventional and extended isogeometricboundary element method with PSO for two-dimensionalHelmholtz acoustic problems, Engineering Analysis withBoundary Elements, 113, 2020, 156–169.
  16. [16] M. Ren, X. Huang, X. Zhu, and L. Shao, Optimized PSOalgorithm based on the simplicial algorithm of fixed pointtheory, Applied Intelligence, 50(7), 2020, 2009–2024.
  17. [17] M.A. Memon, M. Daula, S. Mekhilef, and M. Mubin,Asynchronous particle swarm optimization-genetic algorithm(APSO-GA) based selective harmonic elimination in a cascadedH-bridge multilevel inverter, IEEE Transactions on IndustrialElectronics, 69(2), 2022, 1477–1487.
  18. [18] X. Ji, B. Yang, and Q. Tang, Acoustic seabed classificationbased on multibeam echosounder backscatter data using thePSO-BP- adaboost algorithm: A case study from Jiaozhou Bay,China, IEEE Journal of Oceanic Engineering, 46(2), 2020,509–519.
  19. [19] Y. Yan, Z. Fan, G. Sun, and K. Tian, Diffractive optical elementdesign based on vector diffraction theory and improved PSO-SA algorithm, Optical Engineering, 62(2), 2023, 025103.1–025103.12.
  20. [20] V.B. Mazza, R. Bustamante, A.R.F.D.A. Martins, L.A.C.Teixeira, and B.F.D. Santos, Modelling and optimization of theferrous to ferric sulphate conversion with hydrogen peroxideusing polynomial-PSO and PSO-ANNs models, The CanadianJournal of Chemical Engineering, 100(12), 2022, 3653–3668.
  21. [21] M. Raeispour, H. Atrianfar, and H.R. Baghaee, Resilientdistributed control of BESSs and VSC-based microgridsconsidering switching topologies and nonuniform time-varyingdelays, IET Generation Transmission & Distribution, 14(22),2020, 5060–5071.
  22. [22] S.S. Bohra, Anvari-A. Moghaddam, and F. Blaabjerg, Multi-criteria planning of microgrids for rural electrification, Journalof Smart Environments and Green Computing, 1(2), 2021,120–134.
  23. [23] X. Ma, X. Zhang, and X. Zhao, Service coverage optimizationfor facility location: considering line-of-sight coverage in con-tinuous demand space, International Journal of GeographicalInformation Science, 37(7), 2023, 1496–1519.
  24. [24] N.H. Son, Solution stability to parametric distributedoptimal control problems with finite unilateral constraints,Evolution Equations and Control Theory, 11(4), 2022,1357–1372.
  25. [25] J. Zhai, M. Zhou, and J. Li, Decentralised and distributed day-ahead robust scheduling frameworks for bulk AC/DC hybridinterconnected systems with a high share of wind power, ElectricPower Systems Research, 201(6), 2021, 107492–107492.
  26. [26] L. Guo and N.M.M. Abdul, K. Wang, Design and implementa-tion of virtual laboratory for a microgrid with renewable energysources, Computer Applications in Engineering Education,30(2), 2022, 349–361.
  27. [27] Q. Hassan, M. Jaszczur, and S.A. Hafedh, Optimizing amicrogrid photovoltaic-fuel cell energy system at the highestrenewable fraction, International Journal of Hydrogen Energy,47(28), 2022, 13710–13731.10
  28. [28] A. Tabak, Fractional order frequency proportional-integral-derivative control of microgrid consisting of renewable energysources based on multi-objective grasshopper optimizationalgorithm, Transactions of the Institute of Measurement andControl, 44(2), 2022, 378–392.
  29. [29] H. Chen, W. Wang, X. Chen, and L. Qiu, Multi-objective reservoir operation using particle swarm optimizationwith adaptive random inertia weights, Water Science andEngineering, 13(02), 2020, 58–66.
  30. [30] X. Sun, W. Hu, and X. Xue, Multi-objective optimizationmodel for planning metro-based underground logistics systemnetwork: Nanjing case study, Journal of Industrial andManagement Optimization, 19(1), 2023, 170–196.
  31. [31] D. Gong and G. Li, Research on multi-objective optimizedtarget speed curve of subway operation based on ATO system,International Core Journal of Engineering, 6(2), 2020, 133–137.
  32. [32] Q. Huo and J. Guo, Multi-objective closed-loop logisticsnetwork model of fresh foods based on improved geneticalgorithm, Journal of Computer Applications, 40(5), 2020,1494–1500.
  33. [33] J. Zan, Research on robot path perception and optimizationtechnology based on whale optimization algorithm, Journalof Computational and Cognitive Engineering, 1(4), 2022,201–208.
  34. [34] M. Barma and U.M. Modibbo, Multiobjective mathematicaloptimization model for municipal solid waste management witheconomic analysis of reuse/recycling recovered waste materials,Journal of Computational and Cognitive Engineering, 1(3),2022, 122–137.

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