M. Jaya Bharata Reddy

Smart Fault Location for Smart Grid Operation Using RTUs and Computational Intelligence Techniques

The smart grid aims to improve the quality and reliability of power at the generation, transmission, and distribution levels. The transmission lines can be considered the arteries of the power system, as they carry power over long distances and are exposed to difficult terrain. Transmission line protection philosophy is undergoing a change of paradigm with the advent of digital relays and high-speed broadband communication with the global positioning system (GPS). This paper explores the possibility of transmission line protection for a multigenerator system using wavelet multiresolution analysis (MRA) and computational intelligence techniques in conjunction with GPS. The inputs for the wavelet transform are the synchronized currents measured from remote telemetry units (RTUs) using GPS technology on different buses. The smart location technique uses a wavelet MRA technique to extract the features of the transient current signals based on the harmonics generated at the instant of occurrence of faults due to the abrupt changes of currents in a three-phase transmission line. These extracted features, with such computational intelligence techniques as an adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN), lead the grid toward smarter strategies for locating the fault distance. A comparative study establishes the superiority of ANFIS over ANNs for more accurate and reliable smart fault location. Furthermore, the efficacy of the proposed method is validated through a Monte Carlo simulation to incorporate the stochastic (random) nature of fault occurrence in a real-time transmission line. The most significant contribution of this paper is that the proposed smart location technique is immune to the effects of the fault inception angle (FIA), fault impedance, fault distance, and power angle. The results contained in this paper validate the use of the proposed algorithm for the real-time smart grid operation of transmission lines.

Power quality analysis using Discrete Orthogonal S-transform (DOST)

Power quality is one of the major issues in the modern electrical power world. The widespread usage of power electronic devices and non-linear loads make the power system more vulnerable to the power quality disturbances. As the power grids are expanding more and more because of the renewable sources, it necessitates responsive detection and accurate classification of power quality disturbances for corrective measures. This paper presents a new approach for power quality analysis using an orthogonal time-frequency representation of S-transform called Discrete Orthogonal S-transform (DOST). These power quality disturbances are generated on EHV transmission line under different fault and load condition. Different power quality disturbances have been analyzed using the short time Fourier transform (STFT), discrete wavelet transform (DWT), S-transform (ST) and DOST. Different case studies validate the superiority of DOST over other transforms in a more efficient way to monitor the power quality disturbances.

Robust transmission line fault classification using wavelet multi-resolution analysis☆

Abstract With the advent of high speed communication technology, global positioning system (GPS) and artificial intelligence (AI) techniques, there has been a paradigm shift in the parlance of power grid operation and control. The power system is in a phase of transition towards smart grid with the aid of these techniques to combat against contingencies, leading to reduction of failures and blackouts. The transmission lines are considered to be the back bone of the grid and traverse over difficult terrains. With the advancements in digital relaying and wide-area protection along with GPS technology, philosophy of protection has also undergone a paradigm change to take care of such challenges. This paper explores the possibility of transmission line protection for multi-generator system using wavelet Multi-Resolution Analysis (MRA) technique along with GPS. The inputs for the wavelet transform are the synchronized currents measured by remote telemetry units (RTUs) in conjunction with GPS technology at different buses. The classification algorithm uses wavelet MRA technique to extract features of the transient current signals based on harmonics generated due to abrupt change of currents in a three-phase transmission line caused by different faults. The major contribution of this paper is that the classification algorithm is immune to the effects of fault inception angle, fault impedance, fault distance and power angle. The results validate the efficacy of the proposed algorithm for real time smart grid operation.

A DOST based approach for the condition monitoring of 11 kV distribution line insulators

The diminishing trend of reliability owing to possible power system failures has become a serious concern for the power system as a whole. It has necessitated the development of advanced protection methodologies employing advanced information technology and substation monitoring system (SMS) constitutes an integral part of such methodologies. The proposed scheme for condition monitoring of insulators, which serves as an augmented feature of SMS, aims at alleviating overall system reliability as well as power quality because cracked insulators cause disruption of power, thereby incurring heavy loss to the power system utilities. The image processing based video surveillance (VS) is incorporated to dispense with the cumbersome and time consuming conventional manual on-site detection using discrete orthogonal S-transform (DOST) in conjunction with some intelligent classification algorithms to ascertain the condition of the insulators.

Letter to the Editor: Stability Concerns in Smart Grid with Emerging Renewable Energy Technologies

Abstract The environmental concerns due to conventional power plants have given impetus for widespread utilization of renewable energy based distributed generation technologies. As a consequence, the concepts pertaining to a smart grid with advanced functional architecture are evolving to incorporate these technologies. Many such smart grid strategies are focused on maximum utilization of renewable energy sources compared to conventional fossil or nuclear fuels for meeting real-time load demand. The diverse characteristics of renewable energy based distributed generation technologies compared to conventional power plants have led to many operational stability concerns for the smart grid. This article discusses these stability concerns in smart grid with distributed generation technologies.

Condition monitoring of 11 kV distribution system insulators incorporating complex imagery using combined DOST-SVM approach

The increasing demand for the uninterrupted supply of power is equally increasing the necessity to monitor the health of the distribution network. The failure of the network implicates loss of supply and hence incurs huge loss to power distribution utilities. This paper envisages an algorithm to monitor the condition of overhead distribution line insulators with complex background, keeping in view pragmatic considerations. Complex background necessitates an arduous effort to monitor the condition of insulators and requires a powerful technique to monitor and identify the condition of the insulator. Support vector machines (SVM) and Adaptive neuro-fuzzy inference system (ANFIS) are used to estimate the condition of the insulator with the aid of features extracted from Discrete Orthogonal STransform (DOST). The algorithm is developed in MATLAB environment using the image processing toolbox. Superiority of the SVM over ANFIS has been shown from the results for complex background to validate the efficacy of proposed technique.

Reliability evaluation of solar photovoltaic microgrid

This paper presents an algorithm for reliability analysis and energy management of Power Conditioning System for grid connected PV power generation using a high frequency AC (HFAC) microgrid system. The scheme is designed involving several electrical and electronics components. This analysis excludes redundancy of components. In the microgrid, connected loads are subjected to variable operating conditions of voltage and current. In this analysis component stress and temperature cycles are incorporated in an order to predict the life time and effective design methodologies.

Detection, classification and localization of power system impulsive transients using S-transform

Power quality issues have been of a great concern in recent years due to extensive use of power electronic devices and non-linear loads in electrical power system. In order to monitor electrical power quality disturbance, short time discrete Fourier transform (STFT) is most often used. But in case of non-stationary signals, STFT does not track the signal dynamics properly due to limitations of a fixed window width chosen a priori. By using wavelet transform, disturbances in electrical power system can only be detected and localized, but for sake of classification, standard multi-resolution analysis or other classification techniques must be used. This paper presents a new approach for power quality analysis along with classification using a modified wavelet transform, known as S-transform. Case studies for detection and classification several complex power quality disturbances for impulsive transients using S-transform have been corroborated in this paper and the results contained in this paper validate superiority of S-transform over wavelet transform.

Sliding Mode Control of Single-Phase Grid-Connected Quasi-Z-Source Inverter

Quasi-Z-source inverters (qZSIs) are nowadays increasingly used owing to advantages such as single-stage operation, lower component rating, and continuous input current and common dc rail. These benefits lead to investigate this converter for grid-connected applications. This paper presents a grid-connected qZSI with both ac and dc side control. Sliding mode control (SMC)-based controller for capacitor voltage regulation has been proposed to ensure a fast and dynamic response for wide variations in input voltage, output load, and reference controlled quantity. A detailed mathematical model of the system is presented. A stable and fast response of SMC has been demonstrated using simulation and is validated by experimental results.

Impact of adaptive relaying in Smart Grid

This paper presents the impact of adaptive relaying in smart Grid. Smart grid is an innovative system where integrity of all possible generating system are well connected with the load end or end user to reduce the impact of increased load demand compared to the generation. Obviously, it leads to the increased number of inter connectivity between generating and load end. Thus, on one side the power system becomes complex and on the other side it leads a complex protective system too. To avoid the unnecessary tripping or response for the small scale variation in the system parameters it becomes important that the system acquire adaptivity with the slight changes in system. In this situation the role of adaptive relaying also becomes important because it is responsible to actuate the corresponding circuit breaker to trip and make the system safe to threats. For this purpose, hence the adaptivity of relay is analyzed by using fuzzy inference (FIS) system where the action and response time of relay are considered by taking the short circuit current, fault impedance, location of fault from end as inputs with the result obtained.