Other affiliations: Narula Institute of Technology, University of Calcutta, Academy of Technology ...read more
Bio: Abhijit Chakrabarti is an academic researcher from Indian Institute of Engineering Science and Technology, Shibpur. The author has contributed to research in topics: Electric power system & Transformer. The author has an hindex of 12, co-authored 66 publications receiving 530 citations. Previous affiliations of Abhijit Chakrabarti include Narula Institute of Technology & University of Calcutta.
TL;DR: In this article, the optimal location and setting parameters of SVC and TCSC controllers using PSO (Particle Swarm Optimization) to mitigate small signal oscillations in a multimachine power system is discussed.
TL;DR: A new approach for solving economic load dispatch problems with valve-point effect where the cost function of the generating units exhibits non-convex characteristics, as the valve- point effects are modeled and imposed as rectified sinusoid components.
TL;DR: In this paper, a generalized algorithm has been developed on the basis of Newton-Raphson load flow method for system simulation, which demonstrates that the magnitude of global stability can be ascertained on off-line basis for any variation of load in an interconnected network.
20 Jan 2009-World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering
TL;DR: Features that characterize power quality disturbances from recorded voltage waveforms using wavelet transform are presented, which includes sag, swell, outage and transient.
Abstract: This paper presents features that characterize power quality disturbances from recorded voltage waveforms using wavelet transform. The discrete wavelet transform has been used to detect and analyze power quality disturbances. The disturbances of interest include sag, swell, outage and transient. A power system network has been simulated by Electromagnetic Transients Program. Voltage waveforms at strategic points have been obtained for analysis, which includes different power quality disturbances. Then wavelet has been chosen to perform feature extraction. The outputs of the feature extraction are the wavelet coefficients representing the power quality disturbance signal. Wavelet coefficients at different levels reveal the time localizing information about the variation of the signal. Keywords—Power quality, detection of disturbance, wavelet transform, multiresolution signal decomposition.
••01 Jan 2014
TL;DR: In this article, two powerful stochastic optimization methods the PSO and the GA are employed to find the optimal locations and setting parameters of the FACTS controllers: SVC and TCSC.
Abstract: This chapter emphasizes on tuning and design of optimal power system controllers Two powerful stochastic optimization methods the PSO and the GA are employed to find the optimal locations and setting parameters of the FACTS controllers: SVC and TCSC This chapter also compares the performance of the PSO-based SVC and the PSO-based TCSC controllers with their GA-based design The theory and method of the design of a robust TCSC controller has been explained An H ∞ TCSC controller has been designed in an LMI framework with pole placement constraint in order to mitigate interarea oscillations in a multiarea power system network Finally, a remote feedback control scheme has been proposed to realize a closed-loop control system in a multiarea power system
TL;DR: The proposed novel approach, which combines expert knowledge, neuro-fuzzy inference systems and evolutionary algorithms, can be applied for land use planning and spatial modeling of landslide susceptibility.
Abstract: The main objective of the present study was to produce a novel ensemble data mining technique that involves an adaptive neuro-fuzzy inference system (ANFIS) optimized by Shuffled Frog Leaping Algorithm (SFLA) and Particle Swarm Optimization (PSO) for spatial modeling of landslide susceptibility Step-wise Assessment Ratio Analysis (SWARA) was utilized for the evaluation of the relation between landslides and landslide-related factors providing ANFIS with the necessary weighting values The developed methods were applied in Langao County, Shaanxi Province, China Eighteen factors were selected based on the experience gained from studying landslide phenomena, the local geo-environmental conditions as well as the availability of data, namely; elevation, slope aspect, slope angle, profile curvature, plan curvature, sediment transport index, stream power index, topographic wetness index, land use, normalized difference vegetation index, rainfall, lithology, distance to faults, fault density, distance to roads, road density, distance to rivers and river density A total of 288 landslides were identified after analyzing previous technical surveys, airborne imagery and conducting field surveys Also, 288 non-landslide areas were identified with the usage of Google Earth imagery and the analysis of a digital elevation model The two datasets were merged and later divided into two subsets, training and testing, based on a random selection scheme The produced landslide susceptibility maps were evaluated by the receiving operating characteristic and the area under the success and predictive rate curves (AUC) The results showed that AUC based on the training and testing dataset was similar and equal to 089 However, the processing time during the training and implementation phase was considerable different SWARA-ANFIS-PSO appeared six times faster in respect to the processing time achieved by SWARA-ANFIS-SFLA The proposed novel approach, which combines expert knowledge, neuro-fuzzy inference systems and evolutionary algorithms, can be applied for land use planning and spatial modeling of landslide susceptibility
TL;DR: In this article, a new and efficient krill herd algorithm (KHA) was proposed to solve both convex and non-convex ELD problems of thermal power units considering valve point loading, multiple fuel operation, transmission losses and constraints such as ramp rate limits and prohibited operating zones.
TL;DR: A modified cuckoo search algorithm is proposed to solve economic dispatch problems that have non-convex, non-continuous or non-linear solution spaces considering valve-point effects, prohibited operating zones, transmission losses and ramp rate limits.
Abstract: A modified cuckoo search ( CS ) algorithm is proposed to solve economic dispatch ( ED ) problems that have non-convex, non-continuous or non-linear solution spaces considering valve-point effects, prohibited operating zones, transmission losses and ramp rate limits. Comparing with the traditional cuckoo search algorithm, we propose a self-adaptive step size and some neighbor-study strategies to enhance search performance. Moreover, an improved lambda iteration strategy is used to generate new solutions. To show the superiority of the proposed algorithm over several classic algorithms, four systems with different benchmarks are tested. The results show its efficiency to solve economic dispatch problems, especially for large-scale systems.
TL;DR: Simulation results of IEEE 30-bus and IEEE 57-bus test cases show that the key nodes can be effectively identified with high electrical centrality and resultant cascading failures that eventually lead to a severe decrease in net-ability, verifying the correctness and effectiveness of the analysis.
Abstract: The analysis of blackouts, which can inevitably lead to catastrophic damage to power grids, helps to explore the nature of complex power grids but becomes difficult using conventional methods This brief studies the vulnerability analysis and recognition of key nodes in power grids from a complex network perspective Based on the ac power flow model and the network topology weighted with admittance, the cascading failure model is established first The node electrical centrality is further pointed out, using complex network centrality theory, to identify the key nodes in power grids To effectively analyze the behavior and verify the correctness of node electrical centrality, the net-ability and vulnerability index are introduced to describe the transfer ability and performance under normal operation and assess the vulnerability of the power system under cascading failures, respectively Simulation results of IEEE 30-bus and IEEE 57-bus test cases show that the key nodes can be effectively identified with high electrical centrality, the resultant cascading failures that eventually lead to a severe decrease in net-ability, verifying the correctness and effectiveness of the analysis
TL;DR: This paper aims to guide the reader toward choosing the most effective method according to the issue investigated, namely the N-k problem, trade-off between robustness and optimality, and emerging drivers in power grids.