Binod Kumar Sahu

Dr. Binod Kumar Sahu

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Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 February 2015 in Applied Soft Computing
Verified
Journal Article
Closed access
BSBinod Kumar Sahu
Binod Kumar Sahu
SPSwagat Pati
Swagat Pati
PMPradeep Kumar Mohanty
Pradeep Kumar Mohanty
SPSidhartha Panda
Sidhartha Panda

1 October 2012 in Journal of the Franklin Institute
Verified
Journal Article
Closed access
SPS. Panda
S. Panda
BSBinod Kumar Sahu
Binod Kumar Sahu
PMP.K. Mohanty
P.K. Mohanty

16 March 2022 in Energy Reports
Verified
Journal Article
Open access
Subhasis PandaSubhasis Panda
Subhasis Panda
Sarthak MohantySarthak Mohanty
Sarthak Mohanty
PRPravat Kumar Rout
Pravat Kumar Rout
BSBinod Kumar Sahu
Binod Kumar Sahu
Mohit BajajMohit Bajaj
Mohit Bajaj
SKSalah Kamel
Salah Kamel

1 January 2016 in International Journal of Electrical Power & Energy Systems
Verified
Journal Article
Closed access
BSBinod Kumar Sahu
Binod Kumar Sahu
TPTridipta Kumar Pati
Tridipta Kumar Pati
JNJyoti Ranjan Nayak
Jyoti Ranjan Nayak
SPSidhatrha Panda
Sidhatrha Panda
SKSanjeeb Kumar Kar
Sanjeeb Kumar Kar

29 September 2022 in Energy Reports
Verified
Journal Article
Open access
Sarthak MohantySarthak Mohanty
Sarthak Mohanty
Subhasis PandaSubhasis Panda
Subhasis Panda
SPShubhranshu Mohan Parida
Shubhranshu Mohan Parida
PRPravat Kumar Rout
Pravat Kumar Rout
BSBinod Kumar Sahu
Binod Kumar Sahu
SKSalah Kamel
Salah Kamel

1 November 2014 in IET Generation, Transmission & Distribution
Verified
Journal Article
Open access
PDF file
BSBinod Kumar Sahu
Binod Kumar Sahu
SPSwagat Pati
Swagat Pati
SPSidhartha Panda
Sidhartha Panda
A novel fuzzy proportional–integral derivative (PID) controller is proposed in this study for automatic generation control (AGC) of interconnected power systems. The optimum gains of the proposed fuzzy PID controller are optimised employing a hybrid differential evolution particle swarm optimisation (DEPSO) technique using an integral of time multiplied by absolute value of error criterion. The superiority of hybrid DEPSO algorithm over differential evolution and particle swarm optimisation (PSO) algorithm has also been demonstrated. The results are also compared with some recently published approaches such as artificial bee colony and PSO based proportional–integral/PID controllers for the same interconnected power systems. Furthermore, performance of the proposed system is analysed by varying the different parameters such as loading condition, system parameters and objective functions. It is observed that the optimum gains of the proposed fuzzy PID controller need not be reset even if the system is subjected to variation in loading condition and system parameters. Finally, the study is extended to a three area system considering generation rate constraint to demonstrate the ability of the proposed approach to cope with multiple interconnected systems. Comparison with previous AGC methods reported in the literature validates the significance of the proposed approach.