Article Per Year (5 Year)
p-Index From 2019 - 2024
0.659
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS)
Papia Ray
Veer Surendra Sai University of Technology
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Asset management and maintenance: a smart grid perspective Chan-Mook Jung; Papia Ray; Surender Reddy Salkuti
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (435.654 KB) | DOI: 10.11591/ijece.v9i5.pp3391-3398

Abstract

This paper presents the importance, issues and challenges related to Smart Grid. It also evaluates various approaches for Smart Grid planning and operation. It discusses tools for asset management and their applicability to the next generation grid. Aging assets, uncertainty in load demand profile and renewable energy resources, and demand management create a challenge for the optimal operation and maintenance of electrical grid. This paper addresses the challenges and opportunities to improve transmission and distribution systems asset maintenance. This paper also presents the asset replacement alternatives. This paper also presents the cost-benefit analysis of asset management using the information/real time data from the utility company. This paper will serve a guide for doing the asset management to the electrification  process, investment and  recovery to sustain reliable and efficient power delivery.
Islanding detection in a distribution network with distributed generators using signal processing techniques Seong-Cheol Kim; Papia Ray; Surender Reddy Salkuti
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 11, No 4: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v11.i4.pp2099-2106

Abstract

This paper proposes quick & accurate islanding detection technique for a distribution system with distributed generators (DGs). Here two schemes of islanding detection based on signal processing is proposed of which one is based on discrete wavelet transform (DWT) with artificial neural network (ANN), and another one is based on S-transform with ANN. The negative sequence current/voltage signals are retrieved at targeted DG location which are used for islanding detection in the distribution system. Here, the wavelet and S-transforms are used for fault location and classification applications. Further, the feature extraction is used for reducing the size of data matrix by transforming it into set of features. In this work, particle swarm optimization (PSO) based feature selection scheme is applied. Simulation results on test system indicate the efficacy of proposed islanding detection techniques.
Short-term load forecasting of the distribution system using cuckoo search algorithm Saroj Kumar Panda; Papia Ray; Debani Prasad Mishra; Surender Reddy Salkuti
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 13, No 1: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v13.i1.pp159-166

Abstract

For solving the different optimization problems, the cuckoo search is one of the best nature's inspired algorithms. It is an effective technique compare to other optimization methods. For this manuscript, we are using a back propagation neural network for the Xintai power plant consist of short-term electrical load forecasting. The limitation of back propagation is overcome by the cuckoo search algorithm. The function is used for cuckoo search is Gamma probability distribution and its result is compared with other possible cuckoo search methods. The mean average percentage error of Gamma cuckoo search is 0.123%, cuckoo search with Pareto based is 0.127% and Levy based cuckoo search is 0.407%. Other results of the cuckoo search are also found by a linear decreasing switching parameter with a mean average error is 0.344% and 0.389% of mean average error with the use of an exponentially increasing switching parameter. This improved cuckoo search algorithm brings good results in the predicted load which is very important for the Xintai power plant using short-term load forecasting.
Co-Authors Chan-Mook Jung Debani Prasad Mishra Saroj Kumar Panda Seong-Cheol Kim Surender Reddy Salkuti Surender Reddy Salkuti