EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 472 (2024) E3S Web Conf., 472 (2024) 02005 References
Open Access
Issue
E3S Web Conf.
Volume 472, 2024
International Conference on Renewable Energy, Green Computing and Sustainable Development (ICREGCSD 2023)
Article Number 02005
Number of page(s) 15
Section Green Computing
DOI https://doi.org/10.1051/e3sconf/202447202005
Published online 05 January 2024
  1. N. Nireekshana, “Reactive Power Compensation in High Power Applications by Bidirectionalcasceded H-Bridge Based Statcom”. [Google Scholar]
  2. N. Nireekshana, R. Ramachandran, and G. V. Narayana, “A Novel Swarm Approach for Regulating Load Frequency in Two-Area Energy Systems”. [Google Scholar]
  3. Electrical Engineering department, Annamalai University, Annamalai Nagar, India. and N. Nireekshana, “A Peer Survey on Load Frequency Contol in Isolated Power System with Novel Topologies,” Int. J. Eng. Adv. Technol., vol. 11, no. 1, pp. 82–88, Oct. 2021, DOI: 10.35940/ijeat.A3124.1011121. [CrossRef] [Google Scholar]
  4. N. Nireekshana, R. R. Chandran, and G. V. Narayana, “Frequency Regulation in Two Area System with PSO Driven PID Technique,” J. Power Electron. Power Syst., vol. 12, no. 2, pp. 8–20, Nov. 2022. [Google Scholar]
  5. Y. Güler and I. Kaya, “Load Frequency Control of Single-Area Power System with PI- PD Controller Design for Performance Improvement,” J. Electr. Eng. Technol., pp. 1–16, 2023. [Google Scholar]
  6. P. R. Sahu et al., “Effective Load Frequency Control of Power System with Two- Degree Freedom Tilt-Integral-Derivative Based on Whale Optimization Algorithm,” Sustainability, vol. 15, no. 2, p. 1515, 2023. [CrossRef] [Google Scholar]
  7. R. Kumar and A. Sikander, “A novel load frequency control of multi area non-reheated thermal power plant using fuzzy PID cascade controller,” Sādhanā, vol. 48, no. 1, p. 25, 2023. [Google Scholar]
  8. D. Jutury, N. Kumar, A. Sachan, Y. Daultani, and N. Dhakad, “Adaptive neuro-fuzzy enabled multi-mode traffic light control system for urban transport network,” Appl. Intell., vol. 53, no. 6, pp. 7132–7153, 2023. [CrossRef] [Google Scholar]
  9. N. Ram Babu, S. K. Bhagat, L. C. Saikia, T. Chiranjeevi, R. Devarapalli, and F. P. García Márquez, “A comprehensive review of recent strategies on automatic generation control/load frequency control in power systems,” Arch. Comput. Methods Eng., vol. 30, no. 1, pp. 543–572, 2023. [CrossRef] [Google Scholar]
  10. N. Mohanty, U. K. Mishra, and S. K. Sahu, “An adaptive neuro fuzzy inference system model for studying free in plane and out of plane vibration behavior of curved beams,” in Structures, Elsevier, 2023, pp. 1836–1845. [CrossRef] [Google Scholar]
  11. I. A. Khan, H. Mokhlis, N. N. Mansor, H. A. Illias, L. J. Awalin, and L. Wang, “New trends and future directions in load frequency control and flexible power system: A comprehensive review,” Alex. Eng. J., vol. 71, pp. 263–308, 2023. [CrossRef] [Google Scholar]
  12. S. Tripathi, V. P. Singh, N. Kishor, and A. S. Pandey, “Load frequency control of power system considering electric Vehicles’aggregator with communication delay,” Int. J. Electr. Power Energy Syst., vol. 145, p. 108697, 2023. [CrossRef] [Google Scholar]
  13. V. Navale and S. Mhaske, “Artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) model for Forecasting groundwater level in the Pravara River Basin, India,” Model. Earth Syst. Environ., vol. 9, no. 2, pp. 2663–2676, 2023. [CrossRef] [Google Scholar]
  14. R. R. Mutra, D. Mallikarjuna Reddy, J. Srinivas, D. Sachin, and K. Babu Rao, “Signalbased parameter and fault identification in roller bearings using adaptive neuro-fuzzy inference systems,” J. Braz. Soc. Mech. Sci. Eng., vol. 45, no. 1, p. 45, 2023. [CrossRef] [Google Scholar]
  15. L. Yang, V. Varadarajan, and Y. Qu, “Special issue on neuro, fuzzy and their hybridization,” Neural Computing and Applications. Springer, pp. 1–2, 2023. [Google Scholar]
  16. Namburi Nireekshana, M. Anil Goud, R. Bhavani Shankar, and G. Nitin Sai Chandra, “Solar Powered Multipurpose Agriculture Robot,” May 2023, DOI: 10.5281/ZENODO.7940166. [Google Scholar]
  17. Namburi Nireekshana, Tanvi H. Nerlekar, P. N. Kumar, and M. M. Bajaber, “An Innovative Solar Based Robotic Floor Cleaner,” May 2023, DOI: 10.5281/ZENODO.7918621. [Google Scholar]
  18. L. Gong, G. Hou, and C. Huang, “A two-stage MPPT controller for PV system based on the improved artificial bee colony and simultaneous heat transfer search algorithm,” ISA Trans., vol. 132, pp. 428–443, 2023. [CrossRef] [Google Scholar]
  19. B. R. S. Reddy, V. V. Reddy, and M. V. Kumar, “Modelling and analysis of DC-DC converters with AI based MPP tracking approaches for grid-tied PV-fuel cell system,” Electr. Power Syst. Res., vol. 216, p. 109053, 2023. [CrossRef] [Google Scholar]
  20. I. Griche, S. Messalti, K. Saoudi, and M. Y. Touafek, “A New Adaptive Neuro-Fuzzy Inference System (ANFIS) Controller to Control the Power System equipped by Wind Turbine,” in ITM Web of Conferences, EDP Sciences, 2022. [Google Scholar]
  21. P. Kuate Nkounhawa, D. Ndapeu, and B. Kenmeugne, “Artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS): application for a photovoltaic system under unstable environmental conditions,” Int. J. Energy Environ. Eng., vol. 13, no. 2, pp. 821–829, 2022. [CrossRef] [Google Scholar]
  22. D. Ghimire, D. Kil, and S. Kim, “A survey on efficient convolutional neural networks and hardware acceleration,” Electronics, vol. 11, no. 6, p. 945, 2022. [CrossRef] [Google Scholar]
  23. S. Kamthan and H. Singh, “Hierarchical fuzzy logic systems,” J. Inst. Eng. India Ser. B, vol. 103, no. 4, pp. 1167–1175, 2022. [CrossRef] [Google Scholar]
  24. N. K. Kumar et al., “Fuzzy logic-based load frequency control in an island hybrid power system model using artificial bee colony optimization,” Energies, vol. 15, no. 6, p. 2199, 2022. [CrossRef] [Google Scholar]
  25. S. Kaushik, Artificial intelligence. Cengage Learning, 2011. [Google Scholar]
  26. S. Ishaq, I. Khan, S. Rahman, T. Hussain, A. Iqbal, and R. M. Elavarasan, “A review on recent developments in control and optimization of micro grids,” Energy Rep., vol. 8, pp. 4085–4103, 2022. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.