Intelligent Renewable Energy Systems. Группа авторов

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Intelligent Renewable Energy Systems - Группа авторов


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F., Umayal, C., Ramachandaramurthy, V.K. A Hybrid Moth-Flame Fuzzy Logic Controller Based Integrated Cuk Converter Fed Brushless DC Motor for Power Factor Correction. MDPI Electronics, 2018, 7: 288.

      26. Priyadarshi, N., Padmanaban, S., Lonel, D., Mihet-Popa, L., Azam, F. Hybrid PV-Wind, Micro-Grid Development Using Quasi-Z-Source Inverter Modeling and Control—Experimental Investigation. MDPI Energies, 2018, 11:2277

      27. Priyadarshi, N.; Ramachandaramurthy, V, K.; Padmanaban, S.; Azam, A.; An Ant Colony Optimized MPPT for Standalone Hybrid PV-Wind Power System with Single Cuk Converter. MDPI Energies, 2019, 12: 167

      28. Azam, F.; Yadav, S.K.; Priyadarshi, N.; Padmanaban, S.; and Bansal, R.C.; A Comprehensive Review of Authentication Schemes in Vehicular Ad-Hoc Network, IEEE Access, 2021, 9:31309-31321, 2021, doi: 10.1109/ACCESS.2021.3060046.

      29. Priyadarshi, N.; Sharma, A.K.; Bhoi, A. K.; Ahmad, S. N.; Azam, F.; Priyam, S.; A Practical performance verification of AFLC based MPPT for standalone PV power system under varying weather condition, International Journal of Engineering & Technology, 2018, 7:338-343

      30. Azam F.; Priyadarshi N.; Nagar H.; Kumar S.; Bhoi A.K.; An Overview of Solar-Powered Electric Vehicle Charging in Vehicular Adhoc Network. in: Electric Vehicles. Green Energy and Technology. Springer, Singapore. https://doi.org/10.1007/978-981-15-9251-5_5

      31. Azam, F.; Kumar, S.; Yadav, K.P.; Priyadarshi N.; Padmanaban, S.; An Outline of the Security Challenges in VANET, in Proc. of IEEE UPCON 2020, Nov, 2020.

      32. Priyadarshi, N.; Azam, F.; Bhoi, A.K.; Sharma, A.K.; A Multilevel Inverter-Controlled Photovoltaic Generation. in Advances in Greener Energy Technologies. Springer, Singapore. 2020 https://doi.org/10.1007/978-981-15-4246-6_8

      33. Priyadarshi, N.; Azam, F.; Bhoi, A.K.; Sharma, A.K.; Dynamic Operation of Grid-Connected Photovoltaic Power System. in Advances in Greener Energy Technologies. Springer, Singapore. 2020 https://doi.org/10.1007/978-981-15-4246-6_13

      34. Priyadarshi, N.; Azam, F.; Bhoi, A.K.; Sharma, A.K.; A Proton Exchange Membrane-Based Fuel Cell Integrated Power System. in Advances in Greener Energy Technologies. Springer, Singapore. 2020 https://doi.org/10.1007/978-981-15-4246-6_18

      35. Priyadarshi, N.; Azam, F.; Bhoi, A.K.; Sharma, A.K.; A Closed-Loop Control of Fixed Pattern Rectifier for Renewable Energy Applications. in Advances in Greener Energy Technologies. Springer, Singapore. 2020 https://doi.org/10.1007/978-981-15-4246-6_25

      37. Vardia, M.; Priyadarshi, N.; Ali, I.; Azam, F.; Bhoi, A.K.; Maximum Power Point Tracking for Wind Energy Conversion System. in Advances in Greener Energy Technologies. Springer, Singapore. 2020 https://doi.org/10.1007/978-981-15-4246-6_36

      38. Vardia, M.; Priyadarshi, N.; Ali, I.; Azam, F.; Bhoi, A.K.; Design of Wind Energy Conversion System Under Different Fault Conditions. in Advances in Greener Energy Technologies. Springer, Singapore. 2020 https://doi.org/10.1007/978-981-15-4246-6_41

      39 Choudhary, T.; Priyadarshi, N.; Kuma,r P.; Azam, F.; Bhoi A.K. (2020) A Fuzzy Logic Control Based Vibration Control System for Renewable Application. in Advances in Greener Energy Technologies. Springer, Singapore. 2020 https://doi.org/10.1007/978-981-15-4246-6_38

      40. Priyadarshi, N.; Azam F.; Solanki, S. S.; Sharma, A.K.; Bhoi, A.K.; Almakhles, D.; A Bio-Inspired Chicken Swarm Optimization-Based Fuel Cell System for Electric Vehicle Applications. in Bio-inspired Neurocomputing. Studies in Computational Intelligence, vol 903. Springer, Singapore. 2021 https://doi.org/10.1007/978-981-15-5495-7_1

      41. Gandomkar M.,Vikilian M., and Ehsan M.A. (2005) A genetic-based Tabu search algorithm for optimal DG allocation in distribution systems. Electr. Power Compon. Syst. 33:1351-1362.

      42. Jamian J.J., Mustafa M.W., and Mokhlis H. (2015) Optimal multiple distributed generation output through rank evolutionary particle swarm optimization, Neurocomput. 152:190-198.

      43. Gomez-Gonzalez M., Lopez A., and Jurado F. (2012) Optimization of distributed generation systems using a new discrete PSO and OPF. Electr. Power Syst. Res. 84 (1): 174-180.

      44. Moradi M.H., andAbedini M. (2012) A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems.Int. J. Electr. Power Energy Syst. 34(1): 66-74.

      45. Abu-Mouti F.S., and El-Hawary M.E. (2011) Optimal Distributed Generation Allocation and Sizing in Distribution Systems via Artificial Bee Colony Algorithm. IEEE Trans. Power Delivery. 26 (4): 2090-2101.

      46. Rao R.S., Ravindra K., Satish K., and Narasimham S. (2012) Power loss minimization in distribution system using network reconfiguration in the presence of distributed generation. IEEE Trans Power Syst. 28: 317–325.

      47. Kollu R.,Rayapudi S.R., and Sadhu V.L.N. (2014) A novel method for optimal placement of distributed generation in distribution systems using HSDO. Int.Trans. on Electr. Energy Syst. 24(4): 547-561.

      48. Nayak M.R., Dash S.K., and Rout P. (2012) Optimal Placement and Sizing of Distributed Generation in Radial Distribution System Using Different Evolution Algorithm. In. Proc. third international conference on Swarm, Evolutionary, and Memetic Computing.: 133-142.

      49. Sultana S., and Roy P.K. (2014) Optimal capacitor placement in radial distribution systems using teaching learning based optimization. Int. J. Electr. Power Energy Syst. 54: 387-398.

      50. Sadighizadeh M., Esmaili M., and Esmaili M. (2014) Application of the hybrid Big Bang-Big Crunch algorithm to optimal reconfiguration and distributed generation power allocation in distributed systems. Energy 76: 920-930.

      51. Doagou-Mojarrad H., Gharehpetian G., Rastegar H., and Olamaei J. (2013) Optimal placement and sizing of DG (distributed generation) units in distribution networks by novel hybrid evolutionary algorithm. Energy 54: 129–138.

      52. Aman M.M.,Jasmon G.B., Bakar A.H.A., and Mokhlis H. (2014) A new approach for optimum simultaneous multi-DG distributed generation units placement and sizing based on maximization of system loadability using HPSO (hybrid particle swarm optimization) algorithm. Energy 66: 202-215.

      53. Singh A.K., and Parida S.K. (2015) Allocation of distributed generation using proposed DMSP approach based on utility and consumers aspects under deregulated environment. Int. J. Electr. Power Energy Syst. 68: 159-169.

      54. Shaaban M.F., Atwa Y.M., and El-Saadany E.F. (2013) DG allocation for benefit maximization in distribution networks. IEEE Trans. Power Syst. 28(2): 639–649.

      55. Ettchadi M.,Ghasemi H., and Vaez-Zedah S. (2013) Voltage stability-based DG placement in distribution network. IEEE Trans. Power Delivery 28(1):171-178.

      56. Karatepe E.,Ugrandi F., and Hiyama T. (2015) Comparison of single and multiple-distributed generation concepts in terms of power loss, voltage profile and line flows under uncertainty scenarios. Renew. Sustain. Energy Rev. 48: 317-327.

      57. Arefifar S.A., Mohamed Y.A.I., El-Fouly T.H.M. (2012) Supply-adequacybased optimal construction of micro grids in smart distribution systems. IEEE Trans. Smart Grids 3(3):1491–1502.

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