Browsing by Author "Vittal, K."

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A heuristic approach for distributed generation sources location and capacity evaluation in distribution systems
(2008) Sharma, K.M.; Vittal, K.; Seshagiri, P.
Distributed Generation (DG) sources are becoming more prominent in distribution systems due to increased demand for the electrical energy. The locations and capacities of DG sources will have an impact on system losses, voltage profile characteristics of distribution network. This paper presents a heuristic approach for selection of optimal location and determination of optimal capacity of DG sources. The technique adopts Genetic Algorithms and Optimal Power Flow to facilitate the decision making process. The developed technique is incorporated with the flexibility so that the network planner can choose the total number of DGs to be included, their constraints on maximum power outputs, non-feasible locations for DG insertion which are to be excluded from search. The proposed approach is tested for IEEE 69 bus system and the results have indicated the versatility of the technique.
MSSEAG-UNet: A Novel Deep Learning Architecture for Cloud Segmentation in Fisheye Sky Images and Solar Energy Forecast
(Institute of Electrical and Electronics Engineers Inc., 2025) Kumar, A.; Kashyap, Y.; Sharma, K.; Vittal, K.; Shubhanga, K.N.
This study analyzes sky images captured using a ground-based fisheye camera, aiming to address the challenge of accurately segmenting clouds, which is difficult due to their fuzzy and indistinct boundaries and uneven lighting conditions. Accurate segmentation of clouds in ground-based sky images is crucial for accurate solar energy forecasting. Motivated by these challenges, this article has proposed a novel deep learning architecture called multispatial squeeze-and-excite attention gated U-Net (MSSEAG-UNet) for cloud segmentation in ground-based fisheye sky images. The proposed architecture integrates a multispatial convolutional (MS-CNN) block and squeeze-and-excitation (SE) blocks in the encoder path to improve multiscale feature extraction (MFF) and recalibrate feature maps, while an attention block is incorporated in the decoder path to emphasize key cloud features. The segmentation performance of the MSSEAG-UNet is compared with five benchmark models, and results show that the proposed model outperforms than all benchmarks models. Furthermore, the segmented cloud images produced by the MSSEAG-UNet are used to calculate the cloud percentage, which is then integrated with the original sky images using a multicolumn convolutional model for global horizontal irradiance (GHI) forecast. GHI forecast is conducted for 15-, 30-, and 60-min ahead timesteps, with the best results achieved for the 60-min forecast, yielding mean absolute error (MAE), mean square error (mse), and RMSE values of 6.245%, 0.683%, and 8.265%, respectively. These results highlight the effectiveness of the proposed approach in improving both cloud segmentation accuracy and short-term solar irradiance forecasting. © 1980-2012 IEEE.
On line fault detection and an adaptive algorithm to fast distance relaying
(2008) Srivani Iyengar, S.G.; Vittal, K.
This paper presents the design of an hybrid scheme of wavelet transforms and an adaptive Fourier filtering technique for on line fault detection and phasor estimation to fast distance protection of transmission lines. The wavelet transform is used as a signal processing tool. The sampled voltage and current signals at the relay location are decomposed using wavelet transform- Multi Resolution Analysis (MRA). The decomposed signals are used for the fault detection and as input to the phasor estimation algorithm. The phasor estimation algorithm possesses the advantage of recursive computing and a decaying dc offset component is removed from fault signals by using an adaptive compensation method. Fault detection index and a variable data window scheme are embedded in the algorithm. The proposed scheme provides capability for fast tripping decision, taking accuracy into account. Extensive simulation tests and comparative evaluation presented prove the efficacy of the proposed scheme in distance protection. Â© 2008 IEEE.
Performance analysis of a smart meter node for congestion avoidance and LoS coverage
(AIMS Press, 2019) Pawar, P.; Vittal, K.
Smart meters are intelligent next-generation energy meters which are used for measuring energy consumption and transmitting information over a network. In a real-time environment, a smart meter network faces congestion and coverage issues. To connect to the network, a network interface card (NIC) is installed for each smart meter. NICs are hardware components that link a host to a network and acts as both the physical and data link layer. Generally, a single node is connected to a NIC. We found that the use of multiple NICs in a node shows significant improvement over the use of a single NIC to overcome network congestion in a real-time environment. The line of sight (LoS) between the transmitter and the receiver is a coverage issue in a smart meter network, which leads to an increase in the packet loss ratio (PLR). In this work, we address network congestion and the coverage issue through multi-channel capability and maximum LoS with singleand multi-hop nodes respectively. The proposed multi-channel network shows two times improvement in the throughput over the regular system; with additional hardware and approximately 1.5 times lower PLR for Node. The experimental results suggest that for a single-hop node, approximately 30 m is the average distance over which LoS communication is possible, and for multi-hop nodes, the distance is 24 m. © 2019 the Author(s).
Simulation of four quadrant operation & speed control of BLDC MOTOR on MATLAB / SIMULINK
(2008) Vinatha Urundady, U.; Pola, S.; Vittal, K.
BLDC motors have been gaining attention from various Industrial and household appliance manufacturers, because of its high efficiency, high power density and low maintenance cost. After many research and developments in the fields of magnetic materials and power electronics, their applications to electric drives have increased to a significant extent. In this paper, the modeling of Brushless DC motor drive system along with control system for speed and current has been presented using MATLAB / SIMULINK. In order to evaluate the model, various cases of simulation studies are carried out. Test results thus obtained show that, the model performance is satisfactory.
Situation awareness of deep mining environment using raspberry pi
(American Scientific Publishers order@aspbs.com, 2019) Ramesh, B.; Vittal, K.
The signal from sensor network helps to check the environmental parameters. Sensors have been employed in many fields such as coal mine safety monitoring, industrial monitoring, and also in healthcare monitoring. In this paper, sensor data collection using raspberry pi is studied. Use of analog to digital converter MCP3008 for connecting analog signal to raspberry pi is also studied. The study is mainly to emphasize the use of different sensors and electronic devices to monitor the parameters in deep mining environment. © © 2019 American Scientific Publishers All rights reserved.