K. Sathiyasekar

Bio: K. Sathiyasekar is an academic researcher from S.A. Engineering College. The author has contributed to research in topics: Partial discharge & Solar power. The author has an hindex of 4, co-authored 14 publications receiving 95 citations.

An enhanced bacterial foraging algorithm approach for optimal power flow problem including FACTS devices considering system loadability.

Abstract: Obtaining optimal power flow solution is a strenuous task for any power system engineer. The inclusion of FACTS devices in the power system network adds to its complexity. The dual objective of OPF with fuel cost minimization along with FACTS device location for IEEE 30 bus is considered and solved using proposed Enhanced Bacterial Foraging algorithm (EBFA). The conventional Bacterial Foraging Algorithm (BFA) has the difficulty of optimal parameter selection. Hence, in this paper, BFA is enhanced by including Nelder-Mead (NM) algorithm for better performance. A MATLAB code for EBFA is developed and the problem of optimal power flow with inclusion of FACTS devices is solved. After several run with different initial values, it is found that the inclusion of FACTS devices such as SVC and TCSC in the network reduces the generation cost along with increased voltage stability limits. It is also observed that, the proposed algorithm requires lesser computational time compared to earlier proposed algorithms.

Transmission line faults detection, classification, and location using Discrete Wavelet Transform

Abstract: Transmission line is a vital component that acts as a bridge between the generating stations and end users In the power system, reliability and stability must be ensured to provide continuity of service Transmission lines run over several kilometers will have the chance for occurrence of fault In order to maintain stability, faults should be cleared at short span of time with recent advancements in signal processing In this paper, a novel technique for the protection of transmission lines is proposed The proposed system uses Discrete Wavelet Transform (DWT) which is widely used in recent times for power system protection DWT is used here to extract the hidden factors from the fault signals by performing decomposition at different levels Daubechies wavelet “dB6” is used with single level decomposition and adaptive threshold is calculated to discriminate and detect the faulty phase The location of faults is carried out by obtaining the local fault information and remote location fault information along with the transmission line length The system is independent of any statistical system data and has negligible fault resistance Test system is modeled and fault signals are generated to test the reliability of the algorithm The proposed system promises the result by detecting, classifying and locating all the ten faults possible in the transmission line of the power system

A Review of BLDC Motor: State of Art, Advanced Control Techniques, and Applications

Abstract: Brushless direct current (BLDC) motors are mostly preferred for dynamic applications such as automotive industries, pumping industries, and rolling industries. It is predicted that by 2030, BLDC motors will become mainstream of power transmission in industries replacing traditional induction motors. Though the BLDC motors are gaining interest in industrial and commercial applications, the future of BLDC motors faces indispensable concerns and open research challenges. Considering the case of reliability and durability, the BLDC motor fails to yield improved fault tolerance capability, reduced electromagnetic interference, reduced acoustic noise, reduced flux ripple, and reduced torque ripple. To address these issues, closed-loop vector control is a promising methodology for BLDC motors. In the literature survey of the past five years, limited surveys were conducted on BLDC motor controllers and designing. Moreover, vital problems such as comparison between existing vector control schemes, fault tolerance control improvement, reduction in electromagnetic interference in BLDC motor controller, and other issues are not addressed. This encourages the author in conducting this survey of addressing the critical challenges of BLDC motors. Furthermore, comprehensive study on various advanced controls of BLDC motors such as fault tolerance control, Electromagnetic interference reduction, field orientation control (FOC), direct torque control (DTC), current shaping, input voltage control, intelligent control, drive-inverter topology, and its principle of operation in reducing torque ripples are discussed in detail. This paper also discusses BLDC motor history, types of BLDC motor, BLDC motor structure, Mathematical modeling of BLDC and BLDC motor standards for various applications.

Insulation condition assessment of high-voltage rotating machines using hybrid techniques

Abstract: The enduring life span of the machine insulation will be decided based on degradation level in motor and generator stator windings The non-destructive diagnostic tools like dielectric loss and capacitance test and partial discharge (PD) analysis, recognized to access the deterioration in the insulation system of rotating machines The experiments reveal various characteristic parameters such as leakage current, dielectric dissipation factor, the capacitance value, and PD magnitude The integrity of the rotating machine can be find out by analyzing these parameters This research study shows the hybrid method for prediction of insulation condition in the stator winding by utilizing the artificial neural network (ANN) with gravitational search algorithm in comparison with ANN and ANN-genetic algorithm The advent of expert systems ensures the quality assurance and service life assessment of the high-voltage assets It offers a predictive maintenance solution to personnel dealt with power utilities thereby increasing the uptime, reliability, and productivity, which in turn reducing the operating costs, downtime and unplanned outages For testing and predicting the insulation status, several 11 kV machines are considered The predicted results using hybrid techniques extend a close agreement with reference to the data obtained from the experiments performed The proposed method indicate the competent and trustworthy, by the presented test results

A Novel Salp Swarm Optimization MPP Tracking Algorithm for the Solar Photovoltaic Systems under Partial Shading Conditions

Abstract: To extract the maximum solar power from the photovoltaic (PV) panel/array with the high conversion efficiency under partial shading condition (PSC), this paper discusses a new and an efficient maxi...

Cat Swarm Optimization algorithm for optimal linear phase FIR filter design.

Abstract: In this paper a new meta-heuristic search method, called Cat Swarm Optimization (CSO) algorithm is applied to determine the best optimal impulse response coefficients of FIR low pass, high pass, band pass and band stop filters, trying to meet the respective ideal frequency response characteristics CSO is generated by observing the behaviour of cats and composed of two sub-models In CSO, one can decide how many cats are used in the iteration Every cat has its' own position composed of M dimensions, velocities for each dimension, a fitness value which represents the accommodation of the cat to the fitness function, and a flag to identify whether the cat is in seeking mode or tracing mode The final solution would be the best position of one of the cats CSO keeps the best solution until it reaches the end of the iteration The results of the proposed CSO based approach have been compared to those of other well-known optimization methods such as Real Coded Genetic Algorithm (RGA), standard Particle Swarm Optimization (PSO) and Differential Evolution (DE) The CSO based results confirm the superiority of the proposed CSO for solving FIR filter design problems The performances of the CSO based designed FIR filters have proven to be superior as compared to those obtained by RGA, conventional PSO and DE The simulation results also demonstrate that the CSO is the best optimizer among other relevant techniques, not only in the convergence speed but also in the optimal performances of the designed filters

An efficient particle swarm optimization algorithm to solve optimal power flow problem integrated with FACTS devices

Abstract: Optimal power flow (OPF) is one of the most important tools in power system operation and control, which determines the minimum operating cost and retains the control variables in their secure boundaries. This paper takes into account several unbridled practical constraints in the OPF problem, three of which – that is – valve-point effect, multi-fuel option, and, above all, prohibited operating zone are the most conspicuous ones. Further, the flexible alternating current transmission systems (FACTS) devices are considered, as well, which have several merits such as decreasing the active power transmission loss, controlling the power flow, and improving the voltage stability/profile, to name but a few. Accordingly, thyristor controlled series capacitor (TCSC) – the most popular and common component of the FACTS equipment’s category – is utilized in this study. As a result, the OPF problem integrated with such practical constraints referred to above as well as FACTS devices becomes a highly nonlinear-nonconvex optimization problem and to solve it, a reliable and efficient evolutionary algorithm such as fuzzy-based improved comprehensive-learning particle swarm optimization (FBICLPSO) algorithm is introduced. The proposed approach is scrutinized on IEEE 30-bus test system, which is a commonly used test system for solving the non-smooth and non-convex versions of the OPF problem. Comparing the obtained results by the proposed algorithm with the available alternatives in the literature corroborate the potential and effectiveness of the proposed approach.

Symbiotic organisms search algorithm for optimal power flow problem based on valve-point effect and prohibited zones

Abstract: In this study, symbiotic organisms search (SOS) stochastic method is proposed to solve the optimal power flow (OPF) problem with valve-point effect and prohibited zones, which is one of the most important problems of the modern power system. The SOS approach is defined as the symbiotic relationships observed between two organisms in the ecosystem, which do not need the control parameters unlike other meta-heuristic algorithms in the literature. The effectiveness of the proposed SOS method is tested on modified IEEE 30-bus test system. The OPF problem is considered with four different test cases, such as (1) without valve-point effect and prohibited zones, (2) with valve-point effect, (3) with prohibited zones and (4) with valve-point effect and prohibited zones. The obtained results from the SOS algorithm are compared with the other optimization techniques in the literature. The obtained comparison results indicate that proposed approach is effective to reach optimal solution for the OPF problem.

Critical aspects on wavelet transforms based fault identification procedures in HV transmission line

Abstract: The fault identification process in transmission systems involves three functions: discrimination, classification and phase selection. The current study classifies the methods that applied for each function. Moreover, this study introduces criticism and assessment study that helps the power system protection engineer to choose the best fault identification scheme at responsible indices. Investigated solutions for the drawbacks appeared with the previous methods are suggested. This study also proposes sensitive and automated fault identification scheme to solve the existing challenges such as high-impedance faults (HIFs), non-linear modelling of arcing etc. Several simulation studies are employed using alternative transients program/electromagnetic transient program (ATP/EMTP) package on a sample 500 kV test system to ensure the performances of the proposed scheme compared with the previous methods. Simulation results concluded that: the proposed identification scheme has the ability to discriminate correctly between HIF and low-impedance faults using current signal captured from one end only. Moreover, the proposed scheme alleviates perfectly the problems associated with load variations by adaptive threshold settings and reduces the impacts on the environmental and external phenomena.