http://localhost:8080/xmlui/handle/123456789/34 2026-04-26T08:06:15Z http://localhost:8080/xmlui/handle/123456789/3904 Title: Thermal evaluation of space vector PWM based four- level dual inverter fed open -end winding induction motor drive Authors: Reddy, B. Venugopal; Somasekhar, V.T. Abstract: Multilevel inverters are increasingly being used due to their superior performance compared to two-level inverters. Different circuit topologies on multilevel inverters have been extensively researched. Conduction and switching losses of IGBT in multilevel inverter is the key factor which could influence the converter reliability and efficiency. In this paper, thermal evaluation is described for four level Neutral Point Clamped inverter and four-level dual inverter fed open-end winding induction motor drive using Space Vector Modulation. Description: NITW 2011-01-01T00:00:00Z http://localhost:8080/xmlui/handle/123456789/3903 Title: Optimal placement and sizing of multi distributed generators using teaching and learning based optimization Authors: Kumar Ganivada, Phanindra; Venkaiah, Chintham Abstract: In this paper a new optimization algorithm TLBO (Teaching and Learning Based Optimization) has been implemented to solve optimal multi Distributed Generator (DG) placement problem. This problem has been formulated for minimization of loss, capacity release of transmission lines and voltage profile improvement. To reduce search space and computational burden optimization has been done in two stages first to find the optimal locations for DG placement and latter to find the optimal size of each DG. The proposed TLBO technique has been tested on IEEE 33 bus and IEEE 69 bus radial distribution system. The results have been compared with well known algorithms in literature like GA (Genetic Algorithm) and PSO (Particle Swarm Optimization). A study on effect of DG size and power factor on system performance is done. Results showed significant reduction in power loss and line flows and significant improvement in voltage profile. Description: NITW 2014-01-01T00:00:00Z http://localhost:8080/xmlui/handle/123456789/3896 Title: Optimal PMU placement by teaching-learning based optimization algorithm Authors: Raj, Akhil; Venkaiah, Chintham Abstract: In this paper Teaching-Learning-Based Optimization Algorithm (TLBO) is presented for solving the problem of placement of phasor measurement units (PMU) optimally in a power system network for complete observability. The TLBO algorithm enables optimal PMU placement by zero injection measurements and also by not including zero injection measurements. The algorithm has been tested on standard test systems such as IEEE 14-bus, IEEE 30-bus, IEEE 57-bus and the results are contrasted with other optimization algorithms like Genetic Algorithm and Binary PSO. Description: NITW 2016-01-01T00:00:00Z http://localhost:8080/xmlui/handle/123456789/3895 Title: Electricity price forecasting of deregulated market using Elman Neural Network Authors: Vardhan, N. Harsha; Chintham, Venkaiah Abstract: Price forecasting is one of the main issues faced in deregulated market because of the dynamic behaviour of the electricity prices. In a day-ahead pool market, market participants need forecasted prices to submit their bids to the market operator. Accurate forecast can provide a risk free environment for the producers and consumers to invest into the market. Participants themselves feel that they can have assured return if the forecasted prices are accurate. This paper presents Elman Neural Network to forecast the dynamics in the electricity prices accurately. The proposed method has been tested on Mainland Spain market to forecast the market clearing prices and found to be an efficient method in comparison with many existing methods. Description: NITW 2016-01-01T00:00:00Z