Browsing by Author "Das, Milton Kumar"

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AloA Optimized RLNN controller for LFC of deregulated two-area power system /
(Informatics Publishing Limited, 2021-07-20) Das, Milton Kumar
The performance of the ant lion optimization algorithm (AloA) optimized RLNN controllers are analysed in this work for LFC of two-area deregulation power system. The comparisons are performed for time domain performances of AloA optimized RLNN controllers with traditional PID controllers. The input of PID and RLNN controllers are used area control error (ACE) and controllers’ gains are adjusted through online for RLNN controllers. The performance analyses are also studied to check the controllers’ robustness with variation in parameters of the system and loads. The analysis exposes that AloA optimized RLNN controllers significantly improve the time domain performances of the considered power system compared to PID controllers.
Analysis of transient performance for DFIG wind turbines under the open switch faults /
(IEEE, 2010-12-01) Das, Milton Kumar
The fast development of grid-integrated wind power introduces new requirements for the operation and control of power networks. In order to maintain the reliability of a host power grid, it is preferred that the grid-connected wind turbine should restore its normal operation with minimized power losses in events of grid fault. This paper presents the results for the transient performance of a 2MW doubly-fed induction generator (DFIG), a type of variable-speed wind turbine. The paper concentrates on transient performance of the said generator technology under open-switch grid faults. The simulation was performed using MATLAB - Simulink software. The results obtained have shown that the control schemes employed for the DFIG wind turbines played an effective role in the restoration of the normal operation for the wind turbine in response to grid faults. The results for both during and after the grid fault will be discussed in this paper.
Discrete mode AGC of restructured power system using P-I controller with governor dead-band nonlinearity /
(IEEE, 2016-10-01) Das, Milton Kumar
The paper presents the application of proportional-integral (P-I) Controller for the discrete mode Automatic Generation Control (AGC) problems in the deregulated environment. Governor dead-band non-linearity has been considered in a two area deregulated power system while designing the P-I controller. Imperialist Competitive Algorithm (ICA) has been used for optimizing the gains of P-I controller and the dynamics responses are compared with and without considering optimized values of the controller gains. Simulation results show that P-I controller optimized using ICA gives better dynamic performances compared to P-I controller without optimized using ICA.
Expert-based FMEA of wind turbine system /
(IEEE, 2011-12-01) Das, Milton Kumar
This paper presents the results of a Failure mode and effects analysis (FMEA) conducted for wind turbine (WT) systems. The FMEA was performed on the functional modes of WT sub-systems in order to understand its performance of each sub-system, and to identify weaknesses in the respective sub-systems of WT considered. Sensitivity analysis had been done to investigate the cross-spreading of unreliability between sub-systems in the WT and a ranking of critical subassemblies was prepared on the basis of data supplied by experts that took part in the study. Overall, it was observed that crowbar protection and gearbox were found to be the two most critical components of WT given a reference to the Risk Priority Number (RPN) value of 200. Also, some design and improvement of these components could be envisaged to help improve the performance of the entire WT system by means of reducing the number of failures.
MOGOA Based RLNN controller for LFC of three area deregulated HDG power system /
(IEEE, 2021-09-24) Das, Milton Kumar
This paper presents the multi-objective grasshopper optimization algorithm (MOGOA) based reinforced learning neural network controller (RLNN) controllers in the load frequency control (LFC) problems for three area deregulated hybrid distributed generation (HDG) power system. The controller parameters and gains are optimized by MOGOA and its performance is compared with PID controllers. Sensitivity analyses are performed to investigate robustness of the considered MOGOA-RLNN controllers expose to change of inertia constant and loading conditions and also analysis exposes that MOGOA-RLNN controllers is superior performances than PID controllers.
Oppositional Krill Herd Algorithm-Based RLNN Controller for Discrete-Mode AGC in Deregulated Hydrothermal Power System Using SMES /
(Springer Nature, 2018-06-27) Das, Milton Kumar
This paper presents the application of oppositional krill herd algorithm (OKHA)-based reinforced learning neural network (RLNN) controller to study the discrete-mode automatic generation control (AGC) problems in the deregulated environment considering superconducting magnetic energy storage (SMES) system for three-area hydrothermal power system. The dynamic responses using OKHA-based RLNN controller for various loading conditions are compared with the proportional–integral–derivative (P–I–D) controllers whose gains are also optimized using OKHA. Area control error (ACE) is used as input to both P–I–D and RLNN controllers, and the weights of neural networks have been adjusted online for RLNN controllers. Sensitivity analyses have been performed to investigate the robustness of the controllers that are subject to change in SMES parameters and loading conditions. Investigation reveals that OKHA-based RLNN controllers give better dynamic performances compared to gains of P–I–D controllers obtained using OKHA considering SMES units for different loading conditions.
PI-RLNN Controller for LFC of hybrid deregulated power system based on SPOA /
(IEEE, 2021-12-19) Das, Milton Kumar
This paper presents the student psychology optimization algorithm (SPOA) based Proportional Integral structure incorporated reinforced learning neural network (PI-RLNN) controllers in the load frequency control (LFC) issues for three area hybrid deregulated power system (HDPS) with different generation units like hydro, thermal, diesel engine generation (DEG) and wind turbine generation (WTG). The controller parameters and gains are optimized by SPOA and its performance is compared with both RLNN and PID controllers. Sensitivity analyses are performed to investigate the robustness of the considered SPOA based PI-RLNN controllers representation to different of inertia constant and various loading situations. In addition, the time domain analysis represents that the SPOA based PI-RLNN controllers show superior results than other controllers.
PID-RLNN controllers for discrete mode LFC of a three-area hydrothermal hybrid distributed generation deregulated power system /
(Wiley, 2021-03-16) Das, Milton Kumar
The inequality between active power generation and load demand due to volatile power generation and random changes of load poses a challenge to maintain the system frequency. To address this, in the present work, reinforced learning neural network based–proportional-integral-derivative (PID-RLNN) controllers are proposed in the discrete mode load frequency control (LFC) problems for a three-area hydrothermal hybrid distributed generation (HDG) deregulated power system. The proposed power system is incorporated with super conducting magnetic energy storage system (SMES), and each control area is interconnected via AC/DC parallel links. The dynamic responses using PID-RLNN controllers are compared with PID controllers and RLNN controllers for different loading conditions. The gains and parameters of all the controllers are optimized using grasshopper optimization algorithm (GhOA). Investigation reveals that the PID-RLNN controllers give better dynamic performances compared to PID and RLNN controllers for different loading conditions. Sensitivity analyses are performed to investigate the robustness of the proposed controllers, and investigation reveals that their performances are quite robust for variation of inertia constant and loading conditions. The fluctuation of loads in each area is also considered to analyze the performances of proposed controllers and it is seen that the proposed PID-RLNN controllers damp the oscillations of dynamic responses.
Protection and voltage control of DFIG wind turbines during grid faults /
(IEEE, 2010-01-01) Das, Milton Kumar
The fault ride-through and grid support capabilities of the doubly fed induction generator (DFIG) wind turbines mainly address the design of DFIG wind turbine control with emphasis on power converters protection and voltage control issues. This paper presents the development of a protection and voltage control strategy for DFIG wind turbines, which enhances the fault ride-through capability of DFIG wind turbines and their ability to provide voltage control during grid faults. The performance of the proposed protection and voltage control strategy is assessed through the simulations of a 2MW DFIG wind farm. To protect the rotor side converter, a crowbar at the rotor is switched on. The performance of an active crowbar during voltage dips is investigated for several parameter sets of machine, resistor and control.