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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) IAES International Journal of Artificial Intelligence (IJ-AI) Perfecting a Video Game with Game Metrics Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Surender Reddy Salkuti
Woosong University
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Electrical load forecasting through long short term memory Debani Prasad Mishra; Sanhita Mishra; Rakesh Kumar Yadav; Rishabh Vishnoi; Surender Reddy Salkuti
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 1: January 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i1.pp42-50

Abstract

For a power supplier, meeting demand-supply equilibrium is of utmost importance. Electrical energy must be generated according to demand, as a large amount of electrical energy cannot be stored. For the proper functioning of a power supply system, an adequate model for predicting load is a necessity. In the present world, in almost every industry, whether it be healthcare, agriculture, and consulting, growing digitization and automation is a prominent feature. As a result, large sets of data related to these industries are being generated, which when subjected to rigorous analysis, yield out-of-the-box methods to optimize the business and services offered. This paper aims to ascertain the viability of long short term memory (LSTM) neural networks, a recurrent neural network capable of handling both long-term and short-term dependencies of data sets, for predicting load that is to be met by a Dispatch Center located in a major city. The result shows appreciable accuracy in forecasting future demand.
Optimal short-term hydro-thermal scheduling using multi-function global particle swarm optimization Surender Reddy Salkuti
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 1: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i1.pp537-544

Abstract

An optimal short-term hydro-thermal scheduling (ST-HTS) problem is solved in this paper using the multi-function global particle swarm optimization (MF-GPSO). A multi-reservoir cascaded hydro-electric system with a non-linear relationship between water discharge rate, power generation and net head is considered in this paper. The ST-HTS problem determines the optimal power generation of hydro and thermal generators which is aimed to minimize total fuel cost of thermal power plants during a determined time period. Effects of valve point loading and prohibited operating zones in the fuel cost function of the thermal power plants is examined. Power balance, reservoir volume, water balance and operation constraints of hydro and thermal plants are considered. The effectiveness and feasibility of MF-GPSO algorithm is examined on a standard test system, and the simulation results are compared with other algorithms presented in the literature. The results show that the MF-GPSO algorithm appears to be the best in terms of convergence speed and optimal cost compared with other techniques reported in the literature.
Solving optimal generation scheduling problem of microgrid using teaching learning based optimization algorithm Surender Reddy Salkuti
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 3: March 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i3.pp1632-1638

Abstract

This paper proposes a new optimal scheduling methodology for a Microgrid (MG) considering the energy resources such as diesel generators, solar photovoltaic (PV) plants, wind farms, battery energy storage systems (BESSs), electric vehicles (EVs) and demand response (DR). The penetration level of renewable and sustainable energy resources (i.e., wind, solar PV energy, geothermal and ocean energy) in power generation systems is increasing. In this work, the EVs and storage are used as flexible DR sources and they can be combined with DR to improve the flexibility of MG. Various uncertainties exist in the MGs due to the intermittent/uncertain nature of renewable energy resources (RERs) such as wind and solar PV power outputs. In this paper, these uncertainties are modeled by using the probability analysis. In this paper, the optimal scheduling problem of MG is solved by minimizing the total operating cost (TOC) of MG. The TOC minimization objective is formulated by considering the cost due to power exchange between main grid and MG, diesel generators, wind, solar PV units, EVs, BESSs, and DR. The successful implementation of optimal scheduling of MG requires the widespread use of demand response and EVs. In this paper, teaching-learning-based optimization (TLBO) algorithm is used to solve the proposed optimization problem. The simulation studies are performed on a test MG by considering all the components of MG.
Solving combined economic emission dispatch problem in wind integrated power systems Surender Reddy Salkuti
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp635-641

Abstract

A meta-heuristic based optimization method for solving combined economic emission dispatch (CEED) problem for the power system with thermal and wind energy generating units is proposed in this paper. Wind energy is environmentally friendly and abundantly available, but the intermittency and variability of wind power affects the system operation. Therefore, the system operator (SO) must aware of wind forecast uncertainty and dispatch the wind power accordingly. Here, the CEED problem is solved by including the nonlinear characteristics of thermal generators, and the stochastic behavior of wind generators. The stochastic nature of wind generators is handled by using probability distribution analysis. The purpose of this CEED problem is to optimize fuel cost and emission levels simultaneously. The proposed problem is changed into a single objective optimization problem by using weighted sum approach. The proposed problem is solved by using particle swarm optimization (PSO) algorithm. The feasibility of proposed methodology is demonstrated on six generator power system, and the obtained results using the PSO approach are compared with results obtained from genetic algorithm (GA) and enhanced genetic algorithms (EGA).
Compact MIMO antenna using dual-band for fifth-generation mobile communication system Debani Prasad Mishra; Kshirod Kumar Rout; Surender Reddy Salkuti
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp921-929

Abstract

This paper presents the design of a multiple-input and multiple-output (MIMO) antenna for a fifth-generation (5G) smartphone that will work in dual-band. The antenna proposed in this work operates at 2 frequency ranges, i.e., (3300-3600) MHz and (4800-5000) MHz. The antenna design consists of four antennas that are placed perpendicular to the edge of the system and this makes it different from the traditional 5G antennas. The area of each antenna on the side frames is (3.9×17 mm), and hence can be used in ultra-thin smartphones for 5G applications. The reflection coefficient obtained in the simulations is less than -6 dB for the required band, which suggests that the required impedance matching is obtained. The antenna proposed is designed by using central time zone (CST) microwave studio.
Optimal location and sizing of DG and D-STATCOM in distribution networks Surender Reddy Salkuti
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i3.pp1107-1114

Abstract

The main aim of this paper is to determine optimal locations and sizing of Distributed Generations (DGs) and Distribution STATic COMpensator (D-STATCOM) in the distribution network for reducing the system losses and to improve the voltage profile. In this paper, the loss sensitivity factor approach is used to determine optimal location for DG and voltage stability index is used to determine optimal location for D-STATCOM. The objective of proposed optimization problem is to minimize the total real power losses in the system while satisfying several equality and inequality constraints. Artificial fish swarm optimization algorithm (AFSOA) is used to determine the optimal size of DG and D-STATCOM. The simulations are performed on standard 33 bus and 69 bus radial distribution systems and the obtained  results show the feasibility and effectiveness of proposed approach.
A comprehensive study on smart cities: recent developments, challenges and opportunities V. Sandeep; Pallavi V. Honagond; Pooja S. Pujari; Seong-Cheol Kim; Surender Reddy Salkuti
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 2: November 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i2.pp575-582

Abstract

This paper presents the importance and applications of smart cities in view of taxonomy in urbanization particularly in Asia and Africa economies. It describes the characteristics and architecture of smart cites and reviews on the recent technological developments. The paper analyses the social impacts due to up-gradation of existing cities. The implementation goals like policies and standards are still in progressive state. The international organizations like IEEE, ISO, IEC etc are focused in this emerging area and prepared road map for successful deployment of technologies in cities. In this way of development, there are some interesting challenges like visualization, integration, privacy etc, need to be addressed with specific and innovative solutions. The paper highlights the opportunities in developing and governance of smart cities.
Modern tools and current trends in web-development Debani Prasad Mishra; Kshirod Kumar Rout; Surender Reddy Salkuti
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp978-985

Abstract

In this paper, a social media platform like LinkedIn and Facebook is made using MongoDB as a database. This paper aims to touch all the modern tools required to make an efficient web app, keeping in mind both the customer satisfaction and the ease for the developers to make their web designs, front-end and back-end. In this application, a user could make an account, add or delete details of their profile, education, and experience fields. The users could post, also comment and even like a post of other users. A monolithic architectural approach is used for simplicity in maintaining the database. Postman application programming interface (API) was used to check the working of the back-end. Git, Github, and Heroku were used to deploy the website. Node package manager (NPM) packages like bcrypt and validator are used to encrypt passwords and to validate a user during login. Media queries are used in cascading style sheets (CSS) to achieve a responsive design. Therefore, the users could view the website through a mobile phone, i-pad and also a personal computer (PC), maintaining the readability and design across all these devices.
Comprehensive analysis of current research trends in energy storage technologies Surender Reddy Salkuti; Sravanthi Pagidipala; Seong-Cheol Kim
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 3: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i3.pp1288-1296

Abstract

This paper addresses the comprehensive analysis of various energy storage technologies, i.e., electrochemical and non-electrochemical storage systems by considering their storage methods, environmental impact, operations, costs, and their importance and applications. These storage technologies will help to reduce the energy shortage. There has been a significant deployment of storage systems in power grids throughout the world. The characteristics of storage systems such as the ability to act both as generation and load, fast response time, and high ramp rate. Make them promising options for the system operators to reduce the peak demand, and facilitate renewable energy integration. Various new trends in energy depict the ways this generated energy could be stored and harnessed. With the recent integration of renewable energy, it is important to store the energy and it is combined to help the green energy demand. The integration of renewable energy into the power grid has increased reliability, efficiency, and stability. Adding the energy component will further enhance the capabilities of the grid. This paper also recommends an optimal storage technique from various available storage technologies.
Fraudulent credit card transaction detection using soft computing techniques Aishwarya Priyadarshini; Sanhita Mishra; Debani Prasad Mishra; Surender Reddy Salkuti; Ramakanta Mohanty
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1634-1642

Abstract

Nowadays, fraudulent or deceitful activities associated with financial transactions, predominantly using credit cards have been increasing at an alarming rate and are one of the most prevalent activities in finance industries, corporate companies, and other government organizations. It is therefore essential to incorporate a fraud detection system that mainly consists of intelligent fraud detection techniques to keep in view the consumer and clients’ welfare alike. Numerous fraud detection procedures, techniques, and systems in literature have been implemented by employing a myriad of intelligent techniques including algorithms and frameworks to detect fraudulent and deceitful transactions. This paper initially analyses the data through exploratory data analysis and then proposes various classification models that are implemented using intelligent soft computing techniques to predictively classify fraudulent credit card transactions. Classification algorithms such as K-Nearest neighbor (K-NN), decision tree, random forest (RF), and logistic regression (LR) have been implemented to critically evaluate their performances. The proposed model is computationally efficient, light-weight and can be used for credit card fraudulent transaction detection with better accuracy.
Co-Authors Abhisek Sahoo Aditya Prasad Mahapatra Aishwarya Priyadarshini Amba Subhadarshini Nayak Ambika Prasad Hota Ankit Gupta Arghya Sardar Arun Kumar Sahoo Arun Kumar Sahoo Ashutosh Singh Chauhan Asutosh Samal Atman Panigrahi Bhabani Shankar Panda Bishweashwar Sukla Dashmat Hembram Debani Prasad Mishra Debani Prasad Mishra Debani Prasad Mishra Debani Prasad Mishra Debani Prasad Mishra Debani Prasad Mishra Debani Prasad Mishra Debani Prashad Mishra Drishana Jhunjhunwalla Gangavaram Teja Rishitha Harikrishnan K. M. Jayanta Kumar Sahu Jayanta Kumar Sahu Kalpa Ranjan Behera Kaushiki Agrawal Kishrod Kumar Rout Kshirod Kumar Rout Kshirod Kumar Rout Kshirod Kumar Rout Kshirod Kumar Rout Kunal Badapanda Mandakurit Nivas Mandakuriti Nivas Monalisa Panda Neelakanteshwar Rao Battu Nimay Chandra Giri Nitish Saswat Mallik P. Sravanthi Padarabinda Palai Pallavi V. Honagond Pankaj Sharma Papia Ray Pooja S. Pujari Prakash Kumar Ray Pranay Kumar Panda Pratyush Gupta Priyansh Kasyap Rakesh Kumar Yadav Ramakanta Mohanty Rambilli Krishna Prasad Rao Naidu Rambilli Krishna Prasad Rao Naidu Rishabh Vishnoi Rudra Narayan Senapati Rudranarayan Senapati S. Narasimha S. Narasimha S. S. Saswat Sandeep Vuddanti Sanhita Mishra Sanhita Mishra Saroj Kumar Panda Seong-Cheol Kim Sivkumar Mishra Sivkumar Mishra Sivkumar Mishra Sivkumar Mishra Smrutisikha Jena Somnath Banerjee Sopa Mousumi Patro Soumya Ranjan Das Sravanthi Pagidipala Subhrajit Jena Suchitra Shastri Suman Patra Suman Patra Swarnodeep Kar Truptasha Tripathy V. Sandeep Varun N. John Vinod Karknalli