Dr Pratap Chandra Nayak
@cet.edu.in
Assistant Professor
Odisha University of Technology and Research
EDUCATION
PhD in Electrical Engineering
RESEARCH INTERESTS
Power System Operation Control
Microgrid
Renewable Energy Sources
Artificial Intelligence
Scopus Publications
Scopus Publications
F. Varsi, S. Ahmad, M. Chakraborty, A. Chandra, S.R. Dugad, U.D. Goswami, S.K. Gupta, B. Hariharan, Y. Hayashi, P. Jagadeesan,et al.
IOP Publishing
Abstract The GRAPES-3 experiment located in Ooty, India, samples the electron and muon components in extensive air showers using an array of plastic scintillator detectors and a muon telescope (G3MT) consisting of proportional counters to study the composition of primary cosmic rays (PCRs) as well as γ-ray sources in the TeV–PeV energy range. The G3MT is designed with an appropriate mass absorber to shield the electromagnetic and hadronic components in the shower and to detect muons above 1 GeV×sec(θ) energy, incident from a zenith angle θ. We developed a simulation framework based on the GEANT4 toolkit to evaluate the response of shower particles such as muons, γ-rays, electrons and hadrons in the G3MT. We discuss the geometric modeling of the G3MT using GEANT4 starting with the proportional counter. We estimated the punch-through contribution of hadrons in the G3MT. We compare the simulated muon multiplicity distributions with the observed ones assuming PCR composition from a four population supernova remnant acceleration model namely H4a.
Satyajeet Das, Pratap Chandra Nayak, Ramesh Chandra Prusty, and Sidhartha Panda
Springer Science and Business Media LLC
Debashish Mishra, Pratap Chandra Nayak, Ramesh Chandra Prusty, and Sidhartha Panda
Springer Science and Business Media LLC
Ashirbad Behera, Sonalika Mishra, Pratap Chandra Nayak, Ramesh Chandra Prusty, and Binod Kumar Sahu
IEEE
This study introduces Teaching Learning Based Optimization (TLBO) technique based fractional order PID controller (FOPID) for frequency regulation of multi microgrid system (MMG). Under this study, the MMG system comprises renewable energy sources (RES) such as photo-voltaic generators, wind generators and diesel power generators coordinated with different energy storage systems such as battery energy storage (BESS), flywheel energy storage (FESS), Redox flow battery (RFB)and Ultracapacitor (UC). For optimal design of the FOPID controller parameter, the TLBO technique is used. The efficacy of the proposed techniques is justified over the Dragonfly algorithm (DA) and Particle Swarm Optimization (PSO) algorithm. The projected FOPID controller is studied over PID & I controller. The response of different coordinated structures such as FOPID with BESS, FOPID with FESS, FOPID with US & FOPID with RFB is also analysed.
Debashish Mishra, Pratap Chandra Nayak, Ramesh Chandra Prusty, and Binod Kumar Sahu
IEEE
This article introduces the “Bald Eagle Search Optimisation” (BESO) technique for the improvement of the load frequency control (LFC) of an isolated Microgrid (i-MG) system using a cascaded PI - fractional order FOPID controller. The BESO algorithm is based on a bald eagle's intelligent hunting strategy for food. The i-MG consists of distributed energy sources (DEs) such as wind/ photovoltaic systems with diesel and various energy storage systems (ESSs). Real wind dynamics and photovoltaic uncertainties are considered for this study. The proposed BESO optimised PI-FOPID controller responses are compared with BESO set PID and FOPID controller and also with other typical optimizing tools like differential evolution (DE) and Particle Swarm Optimization (PSO). The performance of the proposed approach is studied under stochastic power variations of load, wind and photovoltaic systems under the influence of several ESSs to manage the deficiency of power in critical situations.
Pratap Chandra Nayak, Sonalika Mishra, Ramesh Chandra Prusty, and Sidhartha Panda
Springer Science and Business Media LLC
Sonalika Mishra, Pratap Chandra Nayak, Ramesh Chandra Prusty, and Sidhartha Panda
Wiley
This paper proposes frequency regulation of multi microgrid systems. The system under study consists of wind energy, solar energy and energy storage system operating in dissimilar combinations to establish equilibrium among the production and consumer demand. In this proposed work, stability analysis of the concerned model is studied using the Henkel matrix approach of the reduced‐order model. Again, an attempt is made to apply the adaptive fuzzy proportional integral and derivative (AFPID) controller for frequency control of the system. The optimal gains of the controllers are tuned by reducing the integral time absolute error using a hybrid dragonfly algorithm supported by the pattern search (hDAPS) algorithm. The efficacy of the proposed adaptive fuzzy controller is examined with fuzzy PID and PID for different cases of the concern system. The efficacy of the hDAPS algorithm is justified over the genetic algorithm, dragonfly algorithm and particle swarm optimization. The robustness study also reveals that the systems are offering reduced overshoot and undershoot under different scenarios of load and source environment. To demonstrate expediency of the proposed controller sensitivity analysis was carried out under different loading conditions. In addition, to show the efficiency of the hDAPS tuned AFPID controller, the outcomes were associated with other artificial intelligence methods reported in the literature.
Sonalika Mishra, Pratap Chandra Nayak, Ramesh Chandra Prusty, and Sidhartha Panda
Springer Science and Business Media LLC
Pratap Chandra Nayak, Ramesh Chandra Prusty, and Sidhartha Panda
Springer Science and Business Media LLC
Sonalika Mishra, Pratap Chandra Nayak, Ramesh Chandra Prusty, and Sidhartha Panda
Informa UK Limited
Umesh Chandra Prusty, Pratap Chandra Nayak, Ramesh Chandra Prusty, and Sidhartha Panda
Informa UK Limited
Pratap Chandra Nayak, Sonalika Mishra, Ramesh Chandra Prusty, and Sidhartha Panda
Informa UK Limited
This article investigates the effect of hydrogen aqua equaliser (HAE) with hydrogen repository tank and fuel cell (FC) as an energy storage element for frequency control in an interconnected power ...
Pratap Chandra Nayak, Ramesh Chandra Prusty, and Sidhartha Panda
Informa UK Limited
This article introduces Grasshopper Optimisation Algorithm (GOA)-based multistage Proportional Derivative filter type (PDF) with One plus Proportional Integral (1 + PI) controller for Automatic Gen...
Pratap Chandra Nayak, Ramesh Chandra Prusty, and Sidhartha Panda
Springer Science and Business Media LLC
Pratap Chandra Nayak, Ramesh Chandra Prusty, and Sidhartha Panda
Springer Science and Business Media LLC
AbstractThis paper uses a Grasshopper Optimization Algorithm (GOA) optimized PDF plus (1 + PI) controller for Automatic generation control (AGC) of a power system with Flexible AC Transmission system (FACTS) devices. Three differently rated reheat turbine operated thermal units with appropriate generation rate constraint (GRC) are considered along with different FACTS devices. A new multistage controller design structure of a PDF plus (1 + PI) is introduced in the FACTS empowered power system for AGC while the controller gains are tuned by the GOA. The superiority of the proposed algorithm over the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithms is demonstrated. The dynamic responses of GOA optimized PDF plus (1 + PI) are compared with PIDF, PID and PI controllers on the same system. It is demonstrated that GOA optimized PDF plus (1 + PI) controller provides optimum responses in terms of settling time and peak deviations compared to other controllers. In addition, a GOA-tuned PDF plus (1 + PI) controller with Interline Power Flow Controller (IPFC) exhibits optimal results compared to other FACTS devices. The sturdiness of the projected controller is validated using sensitivity analysis with numerous load patterns and a wide variation of parameterization. To further validate the real-time feasibility of the proposed method, experiments using OPAL-RT OP5700 RCP/HIL and FPGA based real-time simulations are carried out.
Sonalika Mishra, Pratap Chandra Nayak, Umesh Chandra Prusty, and Ramesh Chandra Prusty
IEEE
This paper introduces a model predictive controller for load frequency control of an isolated ac microgrid system, clustered with the wind system, solar system, and plugged in an electric vehicle. The model predictive controller is an active model-based control which predicts a signal for future control action based on past, present, and future variable of the system. The present study involves a model predictive controller for microgrid load frequency control in the presence of an electric vehicle as a maiden work. The controlled structure formed on the basics of minimization of controller error. The robustness of the controller is tested under a different type of source power fluctuation, load power fluctuation, and simultaneous source and load fluctuation. The predominance of the projected approach is related to conventional GA tuned PID and PI controller. The pragmatic picture of the efficiency of this work is shown by testing it against sinusoidal load perturbation.
Debashish Mishra, Pratap Chandra Nayak, Sushil Kumar Bhoi, and Ramesh Chandra Prusty
IEEE
This research work presenting an innovative approach to design AC off-grid Multi Microgrid system and proposing an analytical aspect of load frequency control using the Modified sine cosine algorithm based Multi-stage tilt TDF/(1+TI) controller. A Multi Micro-Grid system unites distinctive advantages identical to RES (Renewable energy sources), photovoltaic system model, wind turbine model, etc. The asymmetrical property of RES causes a contradiction between the load ultimatum and the source of the Multi Microgrid system. This asymmetrical property of renewable energy sources affects the system frequency adversely. So, nowadays there is a major challenge to stabilize the frequency oscillations in a Multi Microgrid system. Despite all these complications, this paper proposes an approach to stabilize the system frequency by a Modified sine cosine algorithm (MSCA) tuned Multi-stage tilt TDF/(1+TI) controller. To enhance the modern power system capability to meet the recent nonlinear load demand, Microgrid plays an important component to fulfill the critical loading effectively. To establish the efficacy of the proposed Multi-stage tilt TDF/(1+TI) controller, it has been analyzed by the dynamic responses of the classical PI & PID controller. The effectiveness of the MCSA has been validated by the comparative analysis of responses over the most popular responses obtained by the GA & PSO method.
Satyajeet Das, Sushil Kumar Bhoi, Pratap Chandra Nayak, and Ramesh Chandra Prusty
IEEE
This study proposes a Slime Mould Algorithm (SMA) based Fractional Order (FO) cascaded controller (FOPI-FOPD) for frequency control of a two-area AC microgrid (MG) system. The multi-area MG system comprising of a diesel engine generator (DEG), wind turbine generator (WTG), photovoltaic cell (PV), microturbine (MT), along with electric vehicles (EV) and energy storage system like ultra-capacitor (UC). SMA is a novel bio-based optimization tool, which can be used to solve an eclectic real-world problem. This paper aims to incorporate the SMA optimization strategy to solve the Load Frequency Control (LFC) in a microgrid arising due to the ambiguous nature of solar, wind and random load variation. The supremacy of SMA has been vindicated by its comparison over two other intelligent tuning approaches like Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Moreover, the effectiveness of SMA optimized FOPI-FOPD is validated through a comparative study with some classical controllers. Lastly, it is inferred from numerous simulated outcomes that recommended SMA based FOPI-FOPD controller is better concerning LFC of the MG system.
Umesh Chandra Prusty, Bishwaranjan Pasayat, Pratap Chandra Nayak, Ramesh Chandra Prusty, and Sidhartha Panda
IEEE
The frequency regulation problem due to unpredictable load changes and integration of solar/ wind power into the existing thermal unit is studied with the proposed teaching learning-based optimization (TLBO) based tilt integral derivative with a low-frequency filter (TIDF) controller. To establish the competency of the TIDF controller the dynamic performances are correlated with PID and multistage PID controller through integral of time multiplied absolute error (ITAE), integral of absolute error (IAE) and integral of squared error (ISE) fitness function. The hydrogen aqua electrolyser-based fuel cell has been introduced to study the impression on the frequency oscillations due to concern load/ wind/ solar interference. The formulation of the proposed model simulated in Matlab software and interfacing of TLBO based TIDF is carried out for an optimal solution. By doing multiple iterations, the optimum gains for the tilt controller gains of both areas are realized. Simulation results are presented to show the comparison of the suggested TLBO based controllers TIDF over multistage PID and PID control approach which were implemented individually. These resulting performances were judged in terms of settling times and different indices extenuating the effectiveness of the proposed approach.
Pratap Chandra Nayak, Barada Prasanna Nayak, Ramesh Chandra Prusty, and Sidhartha Panda
Informa UK Limited
Pratap Chandra Nayak, Umesh Chandra Prusty, Ramesh Chandra Prusty, and Sidhartha Panda
Informa UK Limited
Control of multi-energy source-based microgrid is a complex task due to the presence of unpredictable renewable energy sources (RES). This paper proposes a cascade structure of proportional derivat...
Umesh Chandra Prusty, Pratap Chandra Nayak, Ramesh Chandra Prusty, and Sidhartha Panda
IEEE
Recently, the innovation of distributed hybrid generation process to meet local power demand and having the flexibility to provide power to the existing power grid makes it revolutionary in the electric power sector. Predictably, integration of nonconventional source will enhance the electric energy efficiency economically. This article introduces a standalone Microgrid comprising of the thermal plant with Photovoltaic power, wind power, diesel power, microturbine, hydrogen aqua equalizer-based fuel-cell and energy storage like battery storage, fly-wheel and Electric Vehicle. This article introduces the study of fuzzy-based optimal controller performance for the balance between load and power generation in Standalone Microgrid (S-MG) with Electric Vehicles (EVs). The optimal controller parameters are provided by the nature enthused metaheuristic Moth flame optimization (MFO) technique. To establish the feasibility of MFO tuned fuzzy-based optimal controller under uncertainty due to deviating loading conditions and penetration of renewable energy sources (RES) the dynamic responses of power frequency are compared with classical controller and algorithms responses.
Debashish Mishra, Pratap Chandra Nayak, Sushil Kumar Bhoi, and Ramesh Chandra Prusty
IEEE
The article aims to propose an innovative robust secondary load frequency control (LFC) technique for Microgrid (MG) in OFF-Grid mode. Generally, MG power generators are unable to maintain frequency stability due to sudden change in loading condition. Another crucial non-linearity encountered due to the most important power source of the MG, the Solar and Wind generating system due to irregularity in solar irradiance and wind deviation in magnitude and direction. The participation of Energy storage system (ESS) is an effective solution to this problem up to great extent. Among various ESS devices, Electric vehicle (EV) has created a unique identity due to its low cost and overwhelming performance in frequency stabilization. The involvement of EVs has been considered to introduce a robust control strategy with other ESS devices for the study of MG. In this paper, the innovative cascaded PID (CPID) controller along with the Grey Wolf optimization (GWO) technique has projected to find the optimal solution for LFC problem of the MG due to various disturbance occurred during operation. The viability of the CPID controller has been measured by most popular PI and PID tuned by the GWO approach. The efficacy of the GWO tuned CPID has been validated by assessing the performance with GA/PSO based CPID controller.
Sonalika Mishra, Pratap Chandra Nayak, Umesh Chandra Prusty, and Ramesh Chandra Prusty
IEEE
Recently the Microgrid system with low inertia, frequency regulation becomes challenging issue due to high dispersion of non-conventional sources. The inertia constant of the microgrid system can be virtually increased with the support of energy storage devices. This paper aims to regulate the system frequency of a islanded Microgrid with the coordination of Virtual inertia control technique. The utilization of an intelligent Salp swarm algorithm (SSA) for ultimate selection of inertia gain and the parameters of the secondary controller, which is a proportional integral and derivative controller used for this case study. The system robustness is analyzed by doing a variety of scenarios including different perturbations. A comparison between the salp swarm technique over most popular algorithms is carried out for justification of the superiority of the utilized SSA method.
Sonalika Mishra, Pratap Chandra Nayak, Umesh Chandra Prusty, and Ramesh Chandra Prusty
IEEE
This study proposes a salp swarm algorithm (SSA) tuned hybrid PID-LQG controller for load frequency control of an isolated microgrid. In the beginning, micro-grid considered here is a cluster of renewable energy sources such as photovoltaic (PV), wind turbine generator (WTG) and battery storage system which diverges from their optimal operating point due to change in its environment. The optimal value of the suggested PID-LQG controller is determined by the SSA method. The supremacy of the proposed controller is tested over the PI and PID controller. The results of SSA tuned hybrid PID-LQG are compared to the genetic algorithm (GA) and particle swarm optimization algorithm (PSO). It is noticed that of SSA tuned hybrid PID-LQG controller is more effective compared to some recently proposed approaches.