An Optimal Model for Power Quality Improvement in Smart Grid using Gravitational Search-based Proportional Integral Controller and Node Microcontroller Unit

References

• N. Vanajakshi and G. Nageswara Rao, “A three phase shunt active power filter for harmonics reduction,” Int. Res. J. Eng. Technol., vol. 02, no. 09, pp. 110–114, 2015.
   Google Scholar
• B. Sahoo, S. K. Routray, and P. K. Rout, “A novel centralized energy management approach for power quality improvement,” Int. Trans. Electric. Energy Syst., vol. 31, no. 10, pp. e12582, 2021. DOI: 10.1002/2050-7038.12582.
   Web of Science ®Google Scholar
• R. Palanisamy, V. Govindaraj, S. Siddhan, and J. R. Albert, “Experimental investigation and comparative harmonic optimization of AMLI incorporate modified genetic algorithm using for power quality improvement,” IFS., vol. 43, no. 1, pp. 1163–1176, 2022. DOI: 10.3233/JIFS-212668.
   Google Scholar
• A. Khan et al., “Hardware-in-the-loop implementation and performance evaluation of three-phase hybrid shunt active power filter for power quality improvement,” Math. Probl. Eng., vol. 2021, pp. 1–23, 2021. DOI: 10.1155/2021/8032793.
   Web of Science ®Google Scholar
• S. S. Dheeban and N. B. Muthu Selvan, “ANFIS-based power quality improvement by photovoltaic integrated UPQC at distribution system,” IETE J. Res., pp. 1–19, 2021. DOI: 10.1080/03772063.2021.1888325.
   Web of Science ®Google Scholar
• S. K. Bilgundi, R. Sachin, H. Pradeepa, H. B. Nagesh, and L. Kumar, “Grid power quality enhancement using an ANFIS optimized PI controller for DG,” Prot. Control Mod. Power Syst., vol. 7, no. 1, pp. 1–14, 2022. DOI: 10.1186/s41601-022-00225-2.
   Google Scholar
• S. Hou, Y. Chu, and J. Fei, “Adaptive type-2 fuzzy neural network inherited terminal sliding mode control for power quality improvement,” IEEE Trans. Ind. Inf., vol. 17, no. 11, pp. 7564–7574, 2021. DOI: 10.1109/TII.2021.3049643.
   Web of Science ®Google Scholar
• X. Zhang, L. Chen, M. Gendreau, and A. Langevin, “A branch-and-cut algorithm for the vehicle routing problem with two-dimensional loading constraints,” Eur. J. Oper. Res., vol. 302, no. 1, pp. 259–269, 2022. DOI: 10.1016/j.ejor.2021.12.050.
   Web of Science ®Google Scholar
• H. Koch, A. Bortfeldt, and G. Wäscher, “A hybrid algorithm for the vehicle routing problem with backhauls, time windows and three-dimensional loading constraints,” Or Spectrum, vol. 40, no. 4, pp. 1029–1075, 2018. DOI: 10.1007/s00291-018-0506-6.
   Web of Science ®Google Scholar
• X. Hua et al., “Research on many-to-many target assignment for unmanned aerial vehicle swarm in three-dimensional scenarios,” Comput. Electr. Eng., vol. 91, pp. 107067, 2021. DOI: 10.1016/j.compeleceng.2021.107067.
   Web of Science ®Google Scholar
• B. Hoffmann, N. Urquhart, K. Chalmers, and M. Guckert, An empirical evaluation of a novel domain-specific language–modelling vehicle routing problems with Athos,” Empir. Softw. Eng., vol. 27, no. 7, pp. 1–52, 2022. DOI: 10.1007/s10664-022-10210-w.
   PubMed Web of Science ®Google Scholar
• M. Yan, H. Yuan, J. Xu, Y. Yu and L. Jin, “Task allocation and route planning of multiple UAVs in a marine environment based on an improved particle swarm optimization algorithm,” EURASIP J. Adv. Sig. Process., vol. 2021, no. 1, pp. 1–23, 2021. DOI: 10.1186/s13634-021-00804-9.
   Web of Science ®Google Scholar
• A. Adam et al., “Improving EEG signal peak detection using feature weight learning of a neural network with random weights for eye event-related applications,” Sādhanā, vol. 42, no. 5, pp. 641–653, 2017. DOI: 10.1007/s12046-017-0633-9.
   Web of Science ®Google Scholar
• P. S. Puhan, P. K. Ray, and G. Panda, “A comparative analysis of artificial neural network and synchronous detection controller to improve power quality in single phase system,” IJPELEC., vol. 9, no. 4, pp. 385–401, 2018. DOI: 10.1504/IJPELEC.2018.10014248.
   Google Scholar
• B. Rout, B. B. Pati, and S. Panda, “Modified SCA algorithm for SSSC damping controller design in power system,” ECTI-EEC., vol. 16, no. 1, pp. 46–63, 2017. DOI: 10.37936/ecti-eec.2018161.171326.
   Google Scholar
• S. Sah and T. Rizvi, “Power quality improvement using shunt active filters with multilevel inverter,” Int. J. Res. Trends Innov., vol. 6, no. 4, 2021.
   Google Scholar
• G. Goswami and P. K. Goswami, “Power quality improvement at nonlinear loads using transformer‐less shunt active power filter with adaptive neural fuzzy interface system supervised PID controllers,” Int. Trans. Electr. Energ. Syst., vol. 30, no. 7, pp. e12415, 2020. DOI: 10.1002/2050-7038.12415.
   Web of Science ®Google Scholar
• S. M. Kuchibhatla, D. Padmavathi, and R. S. Rao, “An elephant herding optimization algorithm-based static switched filter compensation scheme for power quality improvement in smart grid,” J. Circuits Syst. Comput., vol. 29, no. 04, pp. 2050066, 2020. DOI: 10.1142/S0218126620500668.
   Google Scholar
• A. K. Mishra, P. K. Ray, R. K. Mallick, A. Mohanty, and S. R. Das, “Adaptive fuzzy controlled hybrid shunt active power filter for power quality enhancement,” Neural Comput. Appl., vol. 33, no. 5, pp. 1435–1452, 2021. DOI: 10.1007/s00521-020-05027-x.
   Web of Science ®Google Scholar
• S. R. Das et al., “Artificial intelligence based grid connected inverters for power quality improvement in smart grid applications,” Comput. Electric. Eng. vol. 93, pp. 107208, 2021. DOI: 10.1016/j.compeleceng.2021.107208.
   Web of Science ®Google Scholar
• P. R. Kumar, and D. M. S. Kalavathi, “Power quality improvement using interleaved boost converter fed shunt active filter in photo voltaic system,” IOSR J. Electr. Electron. Eng. (IOSR-JEEE) e-ISSN, 2018, pp. 2278–1676.
   Google Scholar
• Y. Sychev, B. Abramovich, and V. Prokhorova, “The assesement of the shunt active filter efficiency under varied power supply source and load parameters,” Int. J. Electr. Comput. Eng. (2088-8708), vol. 10, no. 6, pp. 5621–5630, 2020.
   Google Scholar
• S. Echalih et al., “Hybrid automaton-fuzzy control of single phase dual buck half bridge shunt active power filter for shoot through elimination and power quality improvement,” Int. J. Electr. Power Energy Syst., vol. 131, pp. 106986, 2021. DOI: 10.1016/j.ijepes.2021.106986.
   Web of Science ®Google Scholar
• H. Mittal, A. Tripathi, A. C. Pandey, and R. Pal, “Gravitational search algorithm: A comprehensive analysis of recent variants,” Multimed. Tools Appl., vol. 80, no. 5, pp. 7581–7608, 2021. DOI: 10.1007/s11042-020-09831-4.
   Web of Science ®Google Scholar
• R. K. Beniwal, M. K. Saini, A. Nayyar, B. Qureshi, and A. Aggarwal, “A critical analysis of methodologies for detection and classification of power quality events in smart grid,” IEEE Access, vol. 9, pp. 83507–83534, 2021. DOI: 10.1109/ACCESS.2021.3087016.
   Web of Science ®Google Scholar