Szczegóły
Tytuł artykułu
Spider monkey optimization (SMO) – lattice Levenberg–Marquardt recursive least squares based grid synchronization control scheme for a three-phase PV systemTytuł czasopisma
Archives of Control SciencesRocznik
2021Wolumin
vol. 31Numer
No 3Afiliacje
Dash, Dipak Kumar : Department of Electrical Engineering, Indian Institute of Technology (ISM), Dhanbad, India ; Sadhu, Pradip Kumar : Department of Electrical Engineering, Indian Institute of Technology (ISM), Dhanbad, India ; Subudhi, Bidyadhar : School of Electrical Sciences, Indian Institute of Technology Goa, GEC Campus, Farmagudi, Ponda-401403, Goa, IndiaAutorzy
Słowa kluczowe
solar PV array ; VSC ; SMO ; DC-DC converter ; lattice Levenberg–Marquardt recursive least squares ; hysteresis current controllerWydział PAN
Nauki TechniczneZakres
707-730Wydawca
Committee of Automatic Control and Robotics PASBibliografia
[1] I. Dincer: Renewable energy and sustainable development: a crucial review. Renewable and Sustainable Energy Reviews, 4(2), (2000), 157–175, DOI: 10.1016/S1364-0321(99)00011-8.[2] S. Gulkowski, J.V.M. Diez, J.A. Tejero, and G. Nofuentes: Computational modeling and experimental analysis of heterojunction with intrinsic thin-layer photovoltaic module under different environmental conditions. Energy, 172, (2019), 380–390, DOI: 10.1016/j.energy.2019.01.107.
[3] M. Bahrami, et al.: Hybrid maximum power point tracking algorithm with improved dynamic performance. Renewable Energy, 130, (2019), 982–991, DOI: 10.1016/j.renene.2018.07.020.
[4] K.V. Singh, Krishna, H. Bansal, and D. Singh: A comprehensive review on hybrid electric vehicles: architectures and components. Journal of Modern Transportation, 27, (2019), 1–31, DOI: 10.1007/s40534-019-0184-3.
[5] S. Pradhan, et al.: Performance Improvement of Grid-Integrated Solar PV System Using DNLMS Control Algorithm. IEEE Transactions on Industry Applications, 55(1), (2019), 78–91, DOI: 10.1109/TIA.2018.2863652.
[6] S. Negari and D. Xu: Utilizing a Lagrangian approach to compute maximum fault current in hybrid AC–DC distribution grids withMMCinterface. High Voltage, 4(1), (2019), 18–27, DOI: 10.1049/hve.2018.5087.
[7] V.T. Tran et al.: Mitigation of Solar PV Intermittency Using Ramp-Rate Control of Energy Buffer Unit. IEEE Transactions on Energy Conversion, 34(1), (2019), 435–445, DOI: 10.1109/TEC.2018.2875701.
[8] A. Kihal, et al.: An improved MPPT scheme employing adaptive integral derivative sliding mode control for photovoltaic systems under fast irradiation changes. ISA Transactions, 87, (2019), 297–306, DOI: 10.1016/j.isatra.2018.11.020.
[9] A.M. Jadhav, N.R. Patne, and J.M. Guerrero: A novel approach to neighborhood fair energy trading in a distribution network of multiple microgrid clusters. IEEE Transactions on Industrial Electronics, 66(2), (2019), 1520– 1531, DOI: 10.1109/TIE.2018.2815945.
[10] A. Fragaki, T. Markvart, and G. Laskos: All UK electricity supplied by wind and photovoltaics – The 30–30 rule. Energy, 169, (2019), 228–237, DOI: 10.1016/j.energy.2018.11.151.
[11] S.Z. Ahmed, et al.: Power quality enhancement by using D-FACTS systems applied to distributed generation. International Journal of Power Electronics and Drive Systems, 10(1), (2019), 330, DOI: 10.11591/ijpeds.v10.i1.pp330-341.
[12] H.H. Alhelou, et al.: A Survey on Power System Blackout and Cascading Events: Research Motivations and Challenges. Energies. 12(4), (2019), 1– 28, DOI: 10.3390/en12040682.
[13] M. Badoni, A. Singh, and B. Singh: Implementation of Immune Feedback Control Algorithm for Distribution Static Compensator. IEEE Transactions on Industry Applications, 55(1), (2019), 918–927, DOI: 10.1109/TIA.2018.2867328.
[14] S.R. Das, et al.: Performance evaluation of multilevel inverter based hybrid active filter using soft computing techniques. Evolutionary Intelligence (2019), 1–11, DOI: 10.1007/s12065-019-00217-6.
[15] F. Chishti, S. Murshid, and B. Singh: LMMN Based Adaptive Control for Power Quality Improvement of Grid Intertie Wind-PV System. IEEE Transactions on Industrial Informatics, 15(9), (2019), 4900–4912, DOI: 10.1109/TII.2019.2897165.
[16] S. Pradhan, et al.: Performance Improvement of Grid-Integrated Solar PV System Using DNLMS Control Algorithm. IEEE Transactions on Industry Applications, 55(1), (2019), 78–91, DOI: 10.1109/IICPE.2016.8079455.
[17] V. Jain, I. Hussain, and B. Singh: A HTF-Based Higher-Order Adaptive Control of Single-Stage Grid-Interfaced PV System. IEEE Transactions on Industry Applications, 55(2), (2019), 1873–1881, DOI: 10.1109/TIA.2018.2878186.
[18] N. Kumar, B. Singh, B. Ketan Panigrahi and L. Xu: Leaky Least Logarithmic Absolute Difference Based Control Algorithm and Learning Based InC MPPT Technique for Grid Integrated PV System. IEEE Transactions on Industrial Electronics. 66(11), (2019), 9003–9012, DOI: 10.1109/TIE.2018.2890497.
[19] P. Shah, I. Hussain, and B. Singh: Single-Stage SECS Interfaced with Grid Using ISOGI-FLL- Based Control Algorithm. IEEE Transactions on Industry Applications, 55(1), (2019), 701–711, DOI: 10.1109/TIA.2018.2869880.
[20] V. Jain and B. Singh: A Multiple Improved Notch Filter-Based Control for a Single-StagePVSystem Tied to aWeak Grid. IEEE Transactions on Sustainable Energy, 10(1), (2019), 238–247, DOI: 10.1109/TSTE.2018.2831704.
[21] N. Mohan and T. M. Undeland: Power electronics: converters, applications, and design. John Wiley & Sons, 2007.
[22] M. Badoni, et al.: Grid interfaced solar photovoltaic system using ZA-LMS based control algorithm. Electric Power Systems Research, 160, (2018), 261–272, DOI: 10.1016/j.epsr.2018.03.001.
[23] M. Rezkallah, et al.: Lyapunov function and sliding mode control approach for the solar-PV grid interface system. IEEE Transactions on Industrial Electronics, 64(1), (2016), 785–795, DOI: 10.1109/tie.2016.2607162.
[24] N. Kumar, B. Singh, and B.K. Panigrahi: Integration of Solar PV with Low- Voltage Weak Grid System: using Maximize-M Kalman Filter and Self-Tuned P&O Algorithm. IEEE Transactions on Industrial Electronics, 66(11), (2019), 9013–9022, DOI: 10.1109/tie.2018.2889617.
[25] H. Sharma, G. Hazrati, and J.Ch.Bansal: Spider monkey optimization algorithm. Evolutionary and swarm intelligence algorithms. Springer, Cham, 2019, 43–59.
[26] K. Neelu, P. Devan, Ch.L. Chowdhary, S. Bhattacharya, G. Singh, S. Singh, and B. Yoon: Smo-dnn: Spider monkey optimization and deep neural network hybrid classifier model for intrusion detection. Electronics, 9(4), (2020), 692, DOI: 10.3390/electronics9040692.
[27] M.A.H. Akhand, S.I. Ayon, A.A. Shahriyar, and N. Siddique: Discrete spider monkey optimization for travelling salesman problem. Applied Soft Computing, 86 (2020), DOI: 10.1016/j.asoc.2019.105887.
[28] Avinash Sharma, Akshay Sharma, B.K. Panigrahi, D. Kiran, and R. Kumar: Ageist spider monkey optimization algorithm. Swarm and Evolutionary Computation, 28 (2016), 58–77, DOI: 10.1016/j.swevo.2016.01.002.
[29] Sriram Mounika and K. Ravindra: Backtracking Search Optimization Algorithm Based MPPT Technique for Solar PV System. In Advances in Decision Sciences, Image Processing, Security and Computer Vision. Springer, Cham, 2020, 498–506.
[30] Pilakkat, Deepthi and S. Kanthalakshmi: Single phase PV system operating under Partially Shaded Conditions with ABC-PO as MPPT algorithm for grid connected applications. Energy Reports, 6 (2020), 1910–1921, DOI: 10.1016/j.egyr.2020.07.019.
[31] R. Gessing: Controllers of the boost DC-DC converter accounting its minimum- and non-minimum-phase nature. Archives of Control Sciences, 19(3), (2009), 245–259.
[32] A. Talha and H. Boumaaraf: Evaluation of maximum power point tracking methods for photovoltaic systems. Archives of Control Sciences, 21(2), (2011), 151–165.
[33] S.N. Singh and S. Mishra: FPGA implementation of DPWM utility/DG interfaced solar (PV) power converter for green home power supply. Archives of Control Sciences, 21(4), (2011), 461–469.