Dr. Vijay Babu Pamshetti
@bvrit.ac.in
Assistant Professor
B V Raju Institute of Technology, Narsapur
EDUCATION
EDUCATION
• Ph. D. in Electrical Engineering Department with specialization in Power Systems from Indian Institute of Technology (Banaras Hindu University), Varanasi India
Duration: July 2014 –September 2020.
• M. Tech. in Electrical Engineering Department with specialization in Power Systems from National Institute of Technology (NIT) Kurukshetra with CGPA of 9.018/10.
Duration: 2012-2014.
• B. Tech. in Electrical and Electronics Engineering from VNR Vignana Jyothi Institute of Engineering and Technology Telangana with percentage of 71.75.
Duration: 2006-2010.
• Intermediate (Class-XII) from Narayana Junior college, Hyderabad, Telangana, India under Board of Intermediate Education with 93.5% marks
Duration: 2004-2006
• High-School (Class-X) from Siddhartha High School under Board of Secondary Education with 81.33% marks (2004).
RESEARCH INTERESTS
Volt/VAR Optimization, Smart Distribution System planning, operation and control
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
R. Jyothi, P. Babu, Y. Wang, and Z. Tian
Elsevier BV
Surya Prakash Sankuru and Prabhu Babu
Elsevier BV
Surya Prakash Sankuru and Prabhu Babu
Elsevier BV
Constant modulus sequence having lower side-lobe levels in its auto-correlation function plays an important role in the applications like SONAR, RADAR and digital communication systems. In this paper, we consider the problem of minimizing the Integrated Sidelobe Level (ISL) metric, to design a complex unimodular sequence of any length. The underlying optimization problem is solved iteratively using the Block Majorization-Minimization(MM) technique, which ensures that the resultant algorithm to be monotonic. We also show a computationally efficient way to implement the algorithm using Fast Fourier Transform (FFT) and Inverse Fast Fourier Transform (IFFT) operations. Numerical experiments were conducted to compare the proposed algorithm with the state-of-the art algorithms and was found that the proposed algorithm performs better in terms of computational complexity and speed of convergence.
Vijay Babu Pamshetti and S P Singh
IEEE
The increasing penetration of renewable energy sources (RES) exacerbates the problems such as voltage rise, higher energy losses and energy consumption. The VAR support provided by inverter based distributed generators (IDG) and soft open points (SOP) devices is emerge as a potential solution for aforementioned problems. Therefore, a multi-stage coordination Volt/VAR control (VVC) with conservation voltage reduction (CVR) methodology incorporating IDG and SOP devices has been proposed in this paper. The proposed methodology includes three different stages namely; day-ahead scheduling stage, inner- day control stage, and real-time dispatch stage. In the day-ahead scheduling stage, a coordination optimisation model considering traditional VVC devices, IDG and SOP has been established; in the inner day control stage, a rolling optimisation control model based on model predictive control (MPC) is built, to reduce the influence of the predicted RES forecasted deviations; in the real-time dispatch stage, voltage violations occurred due to sudden change in generation/load are mitigated by regulating the reactive powers of IDG and SOP. To validate the developed scheme, a real time co-simulation framework using real time digital simulator (RTDS) and MATLAB-GAMS interface has been built. The proposed scheme has been tested and validated on a well-known 33 bus distribution system. The test results demonstrate the significance of the proposed scheme on volt/VAR control problems.
Vijay Babu Pamshetti, Shailendra Singh, and Shiv P. Singh
Institute of Electrical and Electronics Engineers (IEEE)
Reduction of energy consumption and energy losses is a major concern of the distribution network operator in the present scenario. Traditionally, on-load tap changers, a shunt capacitor bank, and a voltage regulator have been employed as volt-var control (VVC) devices for savings in energy consumption and losses. In this paper, an efficient and optimally coordinated operation of traditional VVC devices, a distribution network reconfiguration (DNR), and a photovoltaic smart inverter (PVSI) for energy savings has been proposed. In order to achieve the optimal solution, a modified binary gray wolf optimization (MBGWO) algorithm has been proposed. Besides, the proposed method in association with PVSI droop control has been employed to control the voltage violations during cloudy day condition. Furthermore, the proposed method has been employed for service restoration considering voltage regulation and peak demand reduction under faulty condition. For validation, the performance of the proposed algorithm has been tested on balanced as well as unbalanced distribution systems. The test results demonstrate the significance of the DNR associated with VVC devices and PVSI for energy savings under different load models. Outcome of the proposed algorithm has been compared with other existing metaheuristic algorithms and test results demonstrate the benefit of the proposed method.
Shailendra Singh, S. P. Singh, and Vijay Babu Pamshetti
Wiley
Vijay Babu Pamshetti and S. P. Singh
Institute of Electrical and Electronics Engineers (IEEE)
Surya Prakash Sankuru and Prabhu Babu
Institute of Electrical and Electronics Engineers (IEEE)
R. Jyothi and Prabhu Babu
Institute of Electrical and Electronics Engineers (IEEE)
We consider the problem of localizing the source using range, and range-difference measurements. Both the problems are non-convex, and non-smooth, and are challenging to solve. In this article, we develop an iterative algorithm - Source Localization Via an Iterative technique (SOLVIT) to localize the source using all the distinct range-difference measurements, i.e., without choosing a reference sensor. SOLVIT is based on the Majorization Minimization approach - in which a novel upper bound is formulated, and minimized to get a closed-form solution at every iteration. We also solve the source localization problem based on range measurements, and rederive the Standard Fixed Point algorithm using the Majorization Minimization approach. By doing so, we show a less intricate way to prove the convergence of the Standard Fixed Point algorithm. Numerical simulations, and experiments in an anechoic chamber confirm that SOLVIT performs better than existing reference-based, and reference-free methods in terms of source positioning accuracy.
Vijay Babu Pamshetti, Shailendra Singh, and Shiv Pujan Singh
Wiley
Nitesh Sahu, Prabhu Babu, Arun Kumar, and Rajendar Bahl
Institute of Electrical and Electronics Engineers (IEEE)
This paper proposes a novel algorithm to determine the optimal orientation of sensing axes of redundant inertial sensors such as accelerometers and gyroscopes (gyros) for increasing the sensing accuracy. In this paper, we have proposed a novel iterative algorithm to find the optimal sensor configuration. The proposed algorithm utilizes the majorization-minimization (MM) algorithm and the duality principle to find the optimal configuration. Unlike the state-of-the-art approaches which are mainly geometrical in nature and restricted to sensors’ noise being uncorrelated, the proposed algorithm gives the exact orientations of the sensors and can easily deal with the cases of correlated noise. The proposed algorithm has been implemented and tested via numerical simulation in the MATLAB. The simulation results show that the algorithm converges to the optimal configurations and shows the effectiveness of the proposed algorithm.
Sai Subramanyam Thoota, Prabhu Babu, and Chandra R. Murthy
Institute of Electrical and Electronics Engineers (IEEE)
In this paper, we study the problem of downlink (DL) sum rate maximization in codebook based multiuser (MU) multiple input multiple output (MIMO) systems. The user equipments (UEs) estimate the DL channels using pilot symbols sent by the access point (AP) and feedback the estimates to the AP over a control channel. We present a closed form expression for the achievable sum rate of the MU-MIMO broadcast system with codebook constrained precoding based on the estimated channels, where multiple data streams are simultaneously transmitted to all users. Next, we present novel, computationally efficient, minorization-maximization (MM) based algorithms to determine the selection of beamforming vectors and power allocation to each beam that maximizes the achievable sum rate. Our solution involves multiple uses of MM in a nested fashion. Based on this approach, we propose and contrast two algorithms, which we call the square-root-MM (SMM) and inverse-MM (IMM) algorithms. The algorithms are iterative and converge to a locally optimal beamforming vector selection and power allocation solution from any initialization. We evaluate the performance and complexity of the algorithms for various values of the system parameters, compare them with existing solutions, and provide further insights into how they can be used in system design.
Deboshree Roy, Prabhu Babu, and Suneet Tuli
Institute of Electrical and Electronics Engineers (IEEE)
This paper proposes an idea of employing sparse reconstruction-based technique for thermal imaging defect detection. The implementation of the reconstruction technique is tested on a carbon fiber reinforced polymer test piece with artificially drilled defects and the test results are compared with the established cross correlation method. The two processes are compared in terms of defect detectability, their SNR variation with defect depth and their computation complexity. When compared with cross correlation algorithm, the technique is expected to solve memory space problems by compressing all information from large cross-correlated pulse video into a single reconstructed image as an output. Furthermore, in existing cross correlation methods, the pulse peak time shifts with defect depth. Hence, defect quantification algorithms, such as SNR calculation, require multiple frame analysis. Such algorithms are comparatively simplified in sparse reconstruction technique. This paper explores sparse reconstruction algorithm for resolving close-spaced defects. This paper further describes cross-validation method for optimization of a user parameter in sparse reconstruction method.
Shailendra Singh, Vijay Babu Pamshetti, and S. P. Singh
Institute of Electrical and Electronics Engineers (IEEE)
This paper investigates the need of coordinated operation of conservation voltage reduction (CVR) in the presence of electric vehicle (EV) penetration in the active distribution network. In order to analyze the impact of both the technologies (CVR and EV), a time horizon-based model predictive Volt/VAR optimization (VVO) methodology has been introduced in smart grid framework. The proposed VVO methodology operates in centralized as well as local controls under different time scale of operation, including cloud transient effects on solar photovoltaic (PV) power output. Moreover, the control algorithms also consider the uncertainties in load demand and PV power generation. The VVO methodology has been validated with and without presence of EV loads in the distribution network. The VVO includes the impact of different EV charging loads having the ability of participation in reactive power support at selected charging points. This is also referred to as vehicle-to-grid operation in terms of reactive power dispatch only. Besides, the voltage and VAR regulation through smart inverters of PVs and EV charging station has been fruitfully utilized in global as well as local domain. A real-time Volt/VAR droop based controller has been introduced to control the smart inverters reactive power dispatch. To validate the developed methodology, a real-time cosimulation framework, using real-time digital simulator and Python interface, has been built. The proposed model predictive VVO algorithm has been tested and validated on a modified IEEE 34 bus test system. The simulated results reveal that significant CVR energy savings and losses reduction has been achieved without violating the system constraints. The voltage control algorithm works well in both slow and fast time scales.
Vijay Babu Pamshetti, Shailendra Singh, Amit Kumar Thakur, S P Singh, and Vinod Kumar Bussa
IEEE
High penetration of photovoltaic (PV) generation in distribution system exacerbates the over voltage issue and violation of thermal limit of distribution lines. Further, this increased penetration leads to negative impact on system losses. In order to overcome above mentioned problems, this paper introduces the integrated operation of conservation voltage reduction (CVR) and distribution network reconfiguration (DNR) for advance distribution management system (ADMS) application. Besides, impact of advanced flexible power electronic devices such as PV smart inverter and soft open point (SOP) on energy consumption and losses have been studied. The proposed methodology has been implemented on modified 33 bus distribution system. The test results demonstrate the significant impact of the proposed integrated operation on voltage violation, energy losses and energy consumption.
Vijay Babu Pamshetti and Shiv Pujan Singh
Wiley
Sai Subramanyam Thoota, Prabhu Babu, and Chandra R. Murthy
IEEE
The goal of this paper is to propose a novel, principled approach to solve non-convex optimization problems that arise in multiuser (MU) multiple input multiple output (MIMO) cellular wireless communication systems. We explore a minorization-maximization (MM) optimization approach, which is guaranteed to converge to a stationary point starting from any initialization. One of the important problems in wireless communications is sum rate maximization in MU MIMO broadcast systems, in which multiple data streams are simultaneously transmitted to all users. In this paper, we adopt a codebook based precoding method, where each data stream is beamformed using a vector selected from a predetermined codebook. Our objective is to determine the selection of beamforming vectors and power allocation to each beam to maximize the achievable sum rate. We reformulate the problem to facilitate the application of MM procedure in a nested fashion. The outcome is a novel, iterative, and computationally efficient solution, which we call the inverse-MM (IMM) algorithm. We illustrate the superior performance of our algorithm compared to existing approaches through Monte Carlo simulations. The advantages of computational efficiency, simple implementation, and structured approach makes the MM framework a good candidate for solving non convex optimization problems in wireless communications.
R. Jyothi, Prabhu Babu, and Rajendar Bahl
Institute of Electrical and Electronics Engineers (IEEE)
Matrix decomposition is ubiquitous and has applications in various fields like speech processing, data mining and image processing to name a few. Under matrix decomposition, nonnegative matrix factorization is used to decompose a nonnegative matrix into a product of two nonnegative matrices which gives some meaningful interpretation of the data. Thus, nonnegative matrix factorization has an edge over the other decomposition techniques. In this paper, we propose two novel iterative algorithms based on Majorization Minimization (MM) - in which we formulate a novel upper bound and minimize it to get a closed form solution at every iteration. Since the algorithms are based on MM, it is ensured that the proposed methods will be monotonic. The proposed algorithms differ in the updating approach of the two nonnegative matrices. The first algorithm - Iterative Nonnegative Matrix Factorization (INOM) sequentially updates the two nonnegative matrices while the second algorithm - Parallel Iterative Nonnegative Matrix Factorization (PARINOM) parallely updates them. We also prove that the proposed algorithms converge to the stationary point of the problem. Simulations were conducted to compare the proposed methods with the existing ones and was found that the proposed algorithms performs better than the existing ones in terms of computational speed and convergence.
Shailendra Singh, P.Vijay Babu, and S. P. Singh
IEEE
An investigation on the impact of the combined operation of Conservation of Voltage Reduction (CVR) and Energy Storage System (ESS) in distribution grid has been reported in this paper. A smart grid-enabled Volt/VAr Control (SG-VVC) based approach has been utilized to perform the CVR operation in presence of ESS. The main part of SG-VVC is the Volt/VAr optimization (VVO) engine that can perform numerous tasks for the advance distribution management system (ADMS) with the coordination of control centre operator. In this study, the main task of the VVO is to capitalize the CVR benefits (in terms of energy savings and voltage reduction range) by minimizing the total substation power demand through optimal settings of VVC parameters. To achieve the optimal VVC solution, a gravitational search algorithm driven VVO method has been utilized. The test system has been simulated for two cases as with and without ESS system. In each case, operation of test system is carried out with and without VVO mode considering different loadings such as light, normal and high loading conditions. The outcomes of simulated results demonstrated that significant improvement in peak load demand reduction has been achieved by proposed VVO including the ESS with reduced system losses and acceptable feeder voltage profile.
Linlong Wu, Prabhu Babu, and Daniel P. Palomar
Institute of Electrical and Electronics Engineers (IEEE)
In this paper, we consider the joint design of both transmit waveforms and receive filters for a colocated multiple-input-multiple-output (MIMO) radar with the existence of signal-dependent interference and white noise. The design problem is formulated into a maximization of the signal-to-interference-plus-noise ratio (SINR), including various constraints on the transmit waveforms. Compared with the traditional alternating semidefinite relaxation approach, a general and flexible algorithm is proposed based on the majorization-minimization method with guaranteed monotonicity, lower computational complexity per iteration and/or convergence to a B-stationary point. Many waveform constraints can be flexibly incorporated into the algorithm with only a few modifications. Furthermore, the connection between the proposed algorithm and the alternating optimization approach is revealed. Finally, the proposed algorithm is evaluated via numerical experiments in terms of SINR performance, ambiguity function, computational time, and properties of the designed waveforms. The experiment results show that the proposed algorithms are faster in terms of running time and meanwhile achieve as good SINR performance as the the existing methods.
P. Vijay Babu, Shailendra Singh, and S. P. Singh
IEEE
In this paper, analytical method is proposed to determine the optimal allocation of Distributed Generator (DG) in a radial distribution system to reduce the real power loss and improve the voltage profile. Proposed method is based on real power loss expression to calculate the optimal location and size of different DG types. The results are obtained on 69-bus radial distribution system and also compared with an existing method. The test results demonstrate the significance of the proposed method to allocate beneficial amount of DGs capacities at optimal locations. Besides, most favorable mix of different types of DG has been determined for efficient improvement in percentage loss reduction as well as voltage profile.
Zhongju Wang, Prabhu Babu, and Daniel P. Palomar
IEEE
Phase noise compensation plays an indispensable role in realizing the potential of orthogonal frequency division multiplexing (OFDM) for high-data-rate communications. Due to various heuristics employed to deal with the particular properties of phase noise, the existing approaches are still performance-limited in terms of accuracy and computational cost. In this paper, we focus on channel estimation stage and formulate the problem of phase noise compensation in the time domain. An efficient algorithm is devised using the majorization-minimization technique with guaranteed convergence. Numerical results with phase noise generated as a Wiener process demonstrate that our proposed algorithm is able to provide substantially improved phase noise and channel estimates with lower mean squared error especially for moderate signal-to-noise ratio (SNR). The computational complexity is also much lower than that of the benchmark.
Linlong Wu, Prabhu Babu, and Daniel P. Palomar
IEEE
Joint design of transmit waveforms and receive filters has been an active research field since the emergence of MIMO radar. The design problem is usually formulated into a maximization of the signal-to-interference-plus-noise ratio (SINR), subject to waveform constraints. A widely used approach is the alternating optimization scheme combined with the rank-one constrained SDP programming. In this paper, a new algorithm based on the majorization-minimization (MM) method is proposed. This algorithm is not only capable of dealing with various waveform constraints, but also computationally efficient. Furthermore, its connection to the alternating optimization approach is also revealed. Numerical experiments show that the proposed algorithm outperforms the existing benchmarks in terms of running time and/or achieved SINR.
Zhongju Wang, Prabhu Babu, and Daniel P. Palomar
Institute of Electrical and Electronics Engineers (IEEE)
Phase noise correction is crucial to exploit full advantage of orthogonal frequency-division multiplexing (OFDM) in modern high-data-rate communications. OFDM channel estimation with simultaneous phase noise compensation has therefore drawn much attention and stimulated continuing efforts. Existing methods, however, either have not taken into account the fundamental properties of phase noise or are only able to provide estimates of limited applicability owing to considerable computational complexity. In this paper, we have reformulated the joint phase noise and channel estimation problem in the time domain as opposed to existing frequency-domain approaches, which enables us to develop much more efficient algorithms using the majorization–minimization technique. In addition, we propose two methods based on dimensionality reduction and regularization, respectively, that can adapt to various phase noise levels and signal-to-noise ratio and achieve much lower estimation errors than the benchmarks without incurring much additional computational cost. Several numerical examples with phase noise generated by free-running oscillators or phase-locked loops demonstrate that our proposed algorithms outperform existing methods with respect to both computational efficiency and mean squared error within a large range of SNRs.
Ashwani Kumar, P. Vijay Babu, and V. V. S. N. Murty
Springer Science and Business Media LLC
Rapidly increasing electricity demands and capacity shortage of transmission and distribution facilities are the main driving forces for the growth of distributed generation (DG) integration in power grids. One of the reasons for choosing a DG is its ability to support voltage in a distribution system. Selection of effective DG characteristics and DG parameters is a significant concern of distribution system planners to obtain maximum potential benefits from the DG unit. The objective of the paper is to reduce the power losses and improve the voltage profile of the radial distribution system with optimal allocation of the multiple DG in the system. The main contribution in this paper is (i) combined power loss sensitivity (CPLS) based method for multiple DG locations, (ii) determination of optimal sizes for multiple DG units at unity and lagging power factor, (iii) impact of DG installed at optimal, that is, combined load power factor on the system performance, (iv) impact of load growth on optimal DG planning, (v) Impact of DG integration in distribution systems on voltage stability index, (vi) Economic and technical Impact of DG integration in the distribution systems. The load growth factor has been considered in the study which is essential for planning and expansion of the existing systems. The technical and economic aspects are investigated in terms of improvement in voltage profile, reduction in total power losses, cost of energy loss, cost of power obtained from DG, cost of power intake from the substation, and savings in cost of energy loss. The results are obtained on IEEE 69-bus radial distribution systems and also compared with other existing methods.