Author
Rabindra Kumar Sahu
Other affiliations: KIIT University, Indian Institute of Technology Madras
Bio: Rabindra Kumar Sahu is an academic researcher from Veer Surendra Sai University of Technology. The author has contributed to research in topics: PID controller & Control theory. The author has an hindex of 21, co-authored 61 publications receiving 2552 citations. Previous affiliations of Rabindra Kumar Sahu include KIIT University & Indian Institute of Technology Madras.
Papers
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TL;DR: In this article, a two area thermal system with governor dead-band nonlinearity is considered for the design and analysis purpose and differential evolution (DE) algorithm based on parallel 2-Degree Freedom of Proportional-Integral-Derivative (2-DOF PID) controller for Load Frequency Control (LFC) of interconnected power system is presented.
272 citations
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TL;DR: The superiority of the proposed fuzzy PI controller has been shown by comparing the results with Bacteria Foraging Optimization Algorithm (BFOA), Genetic Al algorithm (GA), conventional Ziegler Nichols (ZN), Differential Evolution (DE) and hybrid BFOA and PSO based PI controllers for the same interconnected power system.
259 citations
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TL;DR: In this paper, a hybrid Firefly Algorithm and Pattern Search (hFA-PS) technique is proposed for automatic generation control of multi-area power systems with the consideration of Generation Rate Constraint (GRC).
258 citations
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TL;DR: In this paper, the design and performance analysis of differential evolution algorithm based Proportional Integral Time multiply Absolute Error (ITAE), damping ratio of dominant eigenvalues and settling time with appropriate weight coefficients are derived in order to increase the performance of the controller.
255 citations
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TL;DR: The supremacy of the proposed 2-DOF PID controller has been shown by comparing the results with recently published technique such as conventional ZN, GA, BFOA, DE and hBFOA-PSO based PI controllers for the same system.
225 citations
Cited by
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TL;DR: In this paper, the existing research works on PV cell model parameter estimation problem are classified into three categories and the research works of those categories are reviewed based on the conducted review, some recommendations for future research are provided.
Abstract: The contribution of solar photovoltaics (PV׳s) in generation of electric power is continually increasing. PV cells are commonly modelled as circuits. Finding appropriate circuit model parameters of PV cells is crucial for performance evaluation, control, efficiency computations and maximum power point tracking of solar PV systems. The problem of finding circuit model parameters of solar PV cells is referred to as “PV cell model parameter estimation problem,” and is highly attracted by researchers. In this paper, the existing research works on PV cell model parameter estimation problem are classified into three categories and the research works of those categories are reviewed. Based on the conducted review, some recommendations for future research are provided.
419 citations
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TL;DR: In this article, the authors presented controller parameters tuning of differential evolution (DE) algorithm and its application to Load Frequency Control (LFC) of a multi-source power system having different sources of power generation like thermal, hydro and gas power plants.
320 citations
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TL;DR: The journey of Differential Evolution is shown through its basic aspects like population generation, mutation schemes, crossover schemes, variation in parameters and hybridized variants along with various successful applications of DE.
316 citations
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TL;DR: The use of polymer micro/nanocomposites in electrical engineering is very promising and further research work must be accomplished in order to diversify the polymer composites matrices and to improve their properties.
Abstract: The present review article represents a comprehensive study on polymer micro/nanocomposites that are used in high-voltage applications. Particular focus is on the structure-property relationship of composite materials used in power engineering, by exploiting fundamental theory as well as numerical/analytical models and the influence of material design on electrical, mechanical and thermal properties. In addition to describing the scientific development of micro/nanocomposites electrical features desired in power engineering, the study is mainly focused on the electrical properties of insulating materials, particularly cross-linked polyethylene (XLPE) and epoxy resins, unfilled and filled with different types of filler. Polymer micro/nanocomposites based on XLPE and epoxy resins are usually used as insulating systems for high-voltage applications, such as: cables, generators, motors, cast resin dry-type transformers, etc. Furthermore, this paper includes ample discussions regarding the advantages and disadvantages resulting in the electrical, mechanical and thermal properties by the addition of micro- and nanofillers into the base polymer. The study goals are to determine the impact of filler size, type and distribution of the particles into the polymer matrix on the electrical, mechanical and thermal properties of the polymer micro/nanocomposites compared to the neat polymer and traditionally materials used as insulation systems in high-voltage engineering. Properties such as electrical conductivity, relative permittivity, dielectric losses, partial discharges, erosion resistance, space charge behavior, electric breakdown, tracking and electrical tree resistance, thermal conductivity, tensile strength and modulus, elongation at break of micro- and nanocomposites based on epoxy resin and XLPE are analyzed. Finally, it was concluded that the use of polymer micro/nanocomposites in electrical engineering is very promising and further research work must be accomplished in order to diversify the polymer composites matrices and to improve their properties.
263 citations
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TL;DR: Simulation results show that GWO has better tuning capability than CLPSO, EPSDE and other similar population-based optimization techniques.
Abstract: In this article an attempt has been made to solve load frequency control (LFC) problem in an interconnected power system network equipped with classical PI/PID controller using grey wolf optimization (GWO) technique. Initially, proposed algorithm is used for two-area interconnected non-reheat thermal-thermal power system and then the study is extended to three other realistic power systems, viz. (i) two-area multi-units hydro-thermal, (ii) two-area multi-sources power system having thermal, hydro and gas power plants and (iii) three-unequal-area all thermal power system for better validation of the effectiveness of proposed algorithm. The generation rate constraint (GRC) of the steam turbine is included in the system modeling and dynamic stability of aforesaid systems is investigated in the presence of GRC. The controller gains are optimized by using GWO algorithm employing integral time multiplied absolute error (ITAE) based fitness function. Performance of the proposed GWO algorithm has been compared with comprehensive learning particle swarm optimization (CLPSO), ensemble of mutation and crossover strategies and parameters in differential evolution (EPSDE) and other similar meta-heuristic optimization techniques available in literature for similar test system. Moreover, to demonstrate the robustness of proposed GWO algorithm, sensitivity analysis is performed by varying the operating loading conditions and system parameters in the range of ± 50 % . Simulation results show that GWO has better tuning capability than CLPSO, EPSDE and other similar population-based optimization techniques.
260 citations