P. Balakrishnan

Bio: P. Balakrishnan is an academic researcher from Malla Reddy College Of Engineering & Technology, Hyderabad. The author has contributed to research in topics: Electric power system & Inverter. The author has an hindex of 3, co-authored 5 publications receiving 49 citations. Previous affiliations of P. Balakrishnan include Anna University.

Current status and future prospects of renewable energy: A case study

Abstract: The aim of this study was to analyze renewable energy installed capacity of developing countries by focusing on China as the leading country in renewable energy development to determine the reasons...

Transmission line faults detection, classification, and location using Discrete Wavelet Transform

Abstract: Transmission line is a vital component that acts as a bridge between the generating stations and end users In the power system, reliability and stability must be ensured to provide continuity of service Transmission lines run over several kilometers will have the chance for occurrence of fault In order to maintain stability, faults should be cleared at short span of time with recent advancements in signal processing In this paper, a novel technique for the protection of transmission lines is proposed The proposed system uses Discrete Wavelet Transform (DWT) which is widely used in recent times for power system protection DWT is used here to extract the hidden factors from the fault signals by performing decomposition at different levels Daubechies wavelet “dB6” is used with single level decomposition and adaptive threshold is calculated to discriminate and detect the faulty phase The location of faults is carried out by obtaining the local fault information and remote location fault information along with the transmission line length The system is independent of any statistical system data and has negligible fault resistance Test system is modeled and fault signals are generated to test the reliability of the algorithm The proposed system promises the result by detecting, classifying and locating all the ten faults possible in the transmission line of the power system

A PCA-NPOGBDT strategy-based protection scheme to differentiate between inverter and distribution line faults plus detection and identification of faulty section in microgrid

Abstract: An effective hybrid strategy‐based protection scheme to differentiate between inverter faults and symmetric/unsymmetric faults on distribution line, in addition to detect and identify that faulty section in a microgrid. The proposed hybrid strategy is combined execution of principal component analysis (PCA) and nomadic people optimizer (NPO) learning process‐based gradient boosting decision tree (GBDT). Hence it is commonly named as PCA‐NPOGBDT strategy. Here, three stages are occupied using fault analysis on microgrid to differentiate among inverter faults on microgrid and symmetric/unsymmetric faults on distribution line, in addition to detect/classify that faults and recognize that faulty section. They are: data set generation, feature removal and training process. In this paper, the first procedure of the proposed strategy is the microgrid parameters such as voltage and current signals at usual and unusual condition data set preparation with PCA technique. The data set based on PCA preparation process has feature removal of the power flow parameters and describes that characteristics nature of the various signals happened with microgrid system. The removed data set is evaluated with the NPO‐based GBDT system to classify that sort of fault happened at microgrid system. The proposed model is performed at MATLAB/Simulink working stage and compared with various existing techniques. Computation time of fault detection using proposed and existing system is analyzed and likened to other existing systems like RF, DT, SVM and DBN under 100, 150, 200, 250, and 500 trails. The computation time under 100, 150, 200, 250 and 500 trails of proposed technique is 48.1740, 51.2133, 71.0483, 60.00126, and 57.80132.

Detection and Control of Water Leakage in Pipelines and Taps Using Arduino Nano Microcontroller

Abstract: All living organisms on earth mainly depend on water for their survival. The water is stored in dams and made to reach people through pipelines. The leakage in pipelines leads to a major loss of water, and this leakage is noticed only when it is visible on the earth’s surface. The use of automated water leakage detection and management systems will reduce the huge quantity of water that is getting wasted every day. This paper proposes an embedded system technology for water leakage management in an effective way. The water leakage in pipelines is detected using the water flow sensor, and in taps, it is detected using the water drop sensor. The leakage in pipelines is intimated wirelessly to the corresponding authorities through cloud-based data logging. The solenoid valves are installed at different locations of the pipelines to block the flow of water until the faulty part of the pipeline or tap is repaired during leakage. The main aim of any country is to save water as its demand is increasing rapidly. Involving the proposed automation system will reduce such supply demands.

Critical aspects on wavelet transforms based fault identification procedures in HV transmission line

Abstract: The fault identification process in transmission systems involves three functions: discrimination, classification and phase selection. The current study classifies the methods that applied for each function. Moreover, this study introduces criticism and assessment study that helps the power system protection engineer to choose the best fault identification scheme at responsible indices. Investigated solutions for the drawbacks appeared with the previous methods are suggested. This study also proposes sensitive and automated fault identification scheme to solve the existing challenges such as high-impedance faults (HIFs), non-linear modelling of arcing etc. Several simulation studies are employed using alternative transients program/electromagnetic transient program (ATP/EMTP) package on a sample 500 kV test system to ensure the performances of the proposed scheme compared with the previous methods. Simulation results concluded that: the proposed identification scheme has the ability to discriminate correctly between HIF and low-impedance faults using current signal captured from one end only. Moreover, the proposed scheme alleviates perfectly the problems associated with load variations by adaptive threshold settings and reduces the impacts on the environmental and external phenomena.

Optimal location identification for aggregated charging of electric vehicles in solar photovoltaic powered microgrids with reduced distribution losses

Abstract: The battery-powered electric vehicle finds an alternative for fossil fuel-based vehicles in the transportation sector. The charge-discharge power profiles of the battery storage systems (BSS) contr...