EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 472 (2024) E3S Web Conf., 472 (2024) 02008 References
Open Access
Issue
E3S Web Conf.
Volume 472, 2024
International Conference on Renewable Energy, Green Computing and Sustainable Development (ICREGCSD 2023)
Article Number 02008
Number of page(s) 8
Section Green Computing
DOI https://doi.org/10.1051/e3sconf/202447202008
Published online 05 January 2024
  1. K. Pandiarajan, C.K. Abulal, Fuzzy harmony search algorithm based optimal power flow for power system security enhancement, Electr. Power Energy Syst. 78, 72–79, (2016). [CrossRef] [Google Scholar]
  2. P.S. Rudra, M. Mukherjee, S.P. Ghoshal, Particle swarm optimization with an aging leader and challengers algorithm for optimal power flow problem with FACTS devices, Electr. Power Energy Syst 64, 1185–1196 (2015) [CrossRef] [Google Scholar]
  3. J. Mahadevan, R. Rengaraj, A novel fuzzy hybrid red fox chimp for optimal power flow in FACTS devices. Electr. Eng. 105, 4481–4498, (2023) [CrossRef] [Google Scholar]
  4. K.Y. Lee, Y.M. Park, J.L. Ortiz, A united approach to optimal real and reactive power dispatch, IEEE Trans. Power Appa. Syst. PAS-104 (5), 1147–1153, (1985) [CrossRef] [Google Scholar]
  5. D.W. Wells, Method for economic secure loading of a power system, Proceedings of IEE 115 (8), 1190–1194 (1968) [Google Scholar]
  6. G.F. Reid, L. Hasdorff, Economic dispatch using quadratic programming. IEEE Trans. Power Appa. Syst. PAS-92, 2015–2023, (1973) [CrossRef] [Google Scholar]
  7. L.S. Vargas, V.H. Quintana, A. Vanneli, A tutorial description of an interior point method and its applications to security-constrained economic dispatch, IEEE Trans. Power Appa. Syst. 8 (3), 1315–1324, (1993) [CrossRef] [Google Scholar]
  8. T.T. Nguyen, V. Nguyen, A. Karimishad, Transient stability-constrained optimal power flow for online dispatch and nodal price evaluation in power systems with flexible AC transmission system devices. IET Gene. Transm. Distr. 5 (3), 332–346, (2011) [CrossRef] [Google Scholar]
  9. J. Aghaei, M. Gitizadeh, M. Kaji, Placement and operation strategy of FACTS devices using optimal continuous power flow, Sci. Iran. Trans. D: Comp. Sci. Eng. Electr. 19(6) 1683–1690, (2012) [Google Scholar]
  10. D. Thanh Long, G. Yao., T. Vietanh, A new method for secured optimal power flow under normal and network contingencies via optimal location of TCSC, Electr. Power Energy Syst 52 68–80, (2013) [CrossRef] [Google Scholar]
  11. B. Srinivasa Rao, K. Vaisakh, Multi-objective adaptive clonal selection algorithm for solving optimal power flow considering multi-type FACTS devices and load uncertainty, Appl. Soft Comput. 23 286–297, (2014) [CrossRef] [Google Scholar]
  12. K. Pandiarajan, C.K. Babulal, Fuzzy harmony search algorithm based optimal power flow for power system security enhancement, Electr. Power Energy Syst 78 72–79, (2016). [CrossRef] [Google Scholar]
  13. A. Arsalan, A.G. Ali, R. Mohammad, Optimal power flow incorporating facts devices and stochastic wind power generation using krill herd algorithm. Electr. 9 1–18, (2020) [Google Scholar]
  14. H. Pulluri, M. Vyshnavi, P. Shraddha, B.S. Priya, T.S. Hari, Genetic Algorithm with Multi-Parent Crossover Solution for Economic Dispatch with Valve Point Loading Effects. Innovations in Electr. Electro. Eng. Lecture Notes in Electrical Engineering. 6, 429–438 (2020). [CrossRef] [Google Scholar]
  15. A. Sloiman, H. Abdel-Aal, Modern Optimization Techniques with Applications in Electric Systems (Springer Publications, 2011). https://doi.org/10.1007/978-4614-1752-1. [Google Scholar]
  16. T.N. Malik, A.U. Asar, M.F. Wyne, S. Akhtar, A new hybrid approach for the solution ofnonconvex economic dispatch problem with valve-point effects. Int. J. Elctr, Power Syst. Research, 80, 1128–1136 (2010) [CrossRef] [Google Scholar]
  17. S. Penta, S. Venkateshwarlu K.N. Sujatha, A novel adaptive controller with lyapunov analysis for strategy grid intelligent integrated wind turbine maximum power point tracking system, Int. J. Intell. Syst. Appl. Eng. 11 (9), 94–107 (2023) [Google Scholar]
  18. Y. Celal, O. Serdar, A new hybrid approach for non-convex economic dispatch problem with valvepoint effect, Energy, 36, 5838–5845, (2011) [CrossRef] [Google Scholar]
  19. M. Saber, A.R. Elsayed, A comparative study of different variants of genetic algorithms for constrained optimization, Simul. Evol. Lear. 6457 177–186 (2017) [Google Scholar]
  20. H. Pulluri, Preeti, B. Vedik, T.A. Kumar, A New Genetic Algorithm Variant Designed for Dynamic Economic Dispatch. In: Tomar, A., Malik, H., Kumar, P., Iqbal, A. (eds) Proceedings of 3rd International Conference on Machine Learning, Advances in Computing, Renewable Energy and Communication. Lecture Notes in Electrical Engineering, vol 915. Springer, Singapore. https://doi.org/10.1007/978-981-19-2828-4_37 (2022) [Google Scholar]
  21. T. Srihari, M. Boppa, S. Anil, H. Pulluri, The Application of Genetic Algorithm with Multi-parent Crossover to Optimal Power Flow Problem. In: Saini, H., Srinivas, T., Vinod Kumar, D., Chandragupta Mauryan, K. (eds) Innovations in Electrical and Electronics Engineering. Lecture Notes in Electrical Engineering, Vol. 626. Springer, Singapore. https://doi.org/10.1007/978-981-15-2256-740 (2020). [Google Scholar]
  22. T.M. Mohan, T. Neerikshana, A Genetic Algorithm for Solving Optimal Power Flow Problem. In: Proceedings of 3rd International Conference on Electronics, Communication and Aerospace Technology (ICECA) DOI: 10.1109/ICECA.2019.8822090 (2019) [Google Scholar]
  23. P. Samyuktha, S. Venkateshwarlu, K.N. Sujatha, Lyapunov based control strategy for DFIG based wind turbines to enhance stability and power, Int. J. Electr. Electro. Eng. Res. 11(4), 898–903, (2023) [Google Scholar]
  24. N. Saber, A. Ruhul, L. Dary, GA with a new multi-parent crossover for constrained optimization, IEEE Cong. Evol. Comput., 10, 857–864 (2011). [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.