Sushama Wagh

Wireless Power Transfer Using Metamaterial Bonded Microstrip Antenna for Smart Grid WSN

Wireless Power Transfer (WPT) system is a suitable alternative for power transmission where conventional wired power transfer faces geographical challenges. In a long range wireless power transmission system, power is transmitted through microwaves. A highly directive antenna is required for an effective transmission through this system. This paper talk about a circularly polarized microstrip rectangular patch antenna incorporated with a metamaterial slab. Use of microstrip antennas will considerably reduce the size of WPT system in comparison to other microwave antenna. In this paper the modeling and analysis of the wireless power transmission system is done on 2.45 GHz frequency and using GaAs Schottky barrier diode for the rectification of microwave power to DC power at the receiver end. Antenna assigned with metamaterial proposed in paper will enhance the amount of transferred power to wireless sensors network with less radiation loss.

Support-Vector-Machine-Based Proactive Cascade Prediction in Smart Grid Using Probabilistic Framework

The worldwide major blackout events of power network are highlighting the need for technology upgradation in traditional grid. One of the major upgradations required is in the area of early warning generation in case of any grid disturbances such as line contingency leading to cascade failure. This paper proposes a proactive blackout prediction model for a smart grid early warning system. The proposed model evaluates system performance probabilistically, in steady state and under dynamical (line contingency) state, and prepares a historical database for normal and cascade failure states. A support vector machine (SVM) has been trained with this historical database and is used to predict blackout events in advance. The key contribution of this paper is to capture the essence of the cascading failure using probabilistic framework and integration of SVM machine learning tool to build a prediction rule, which would be able to predict the scenarios of the blackout as early as possible. The proposed model is validated using the IEEE 30-bus test-bed system. Proactive prediction of cascade failure using the proposed model may help in realizing the grid resilience feature of smart grid.

Impact of Topology on the Propagation of Cascading Failure in Power Grid

In the past two decades the frequent occurrences of large scale blackouts and catastrophic events has reduced the reliability of power grid to a great extent. A thorough analysis of the propagation of failures, in terms of line outages, combined with the topological characteristics of the grid aids, has been done to take corrective actions to save the system from complete collapse. It also helps to investigate the progress and understand the nature and intensity of blackouts. This motivates to establish the relationship between the network topological characteristics and cascading failure in the power grid. In this paper, the basic topological characteristics of the power network are studied in detail and the average propagation of failure under varying topological conditions is calculated as a branching process parameter. The variation in the mean propagation is studied in detail using a number of test bed networks with the alternate realistic networks derived from the standard IEEE networks imitating the real network conditions. The results confirm a qualitative agreement between the variations in topological parameter and the failure propagation rate in the cascading regime. Based on the analysis mentioned above, data clearly shows that the average failure propagation factor varies linearly with the variations in the statistical metrics.

Neural Network Based Early Warning System for an Emerging Blackout in Smart Grid Power Networks

Worldwide power blackouts have attracted great attention of researchers towards early warning techniques for cascading failure in power grid. The key issue is how to analyse, predict and control cascading failures in advance and prevent system against emerging blackouts. This paper proposes a model which analyse power flow of the grid and predict cascade failure in advance with the integration of Artificial Neural Network (ANN) machine learning tool. The Key contribution of this paper is to introduce machine learning concept in early warning system for cascade failure analysis and prediction. Integration of power flow analysis with ANN machine learning tool has a potential to make present system more reliable which can prevent the grid against blackouts. An IEEE 30 bus test bed system has been modeled in powerworld and used in this paper for preparation of historical blackout data and validation of proposed model. The proposed model is a step towards realizing smart grid via intelligent ANN prediction technique.

Wireless Power Transfer using microstrip antenna assigned with graded index lenses for WSN

Wireless Power Transfer (WPT) systems are considered as sophisticated alternative for modern day wired power transmission. In long range WPT systems, power is transmitted through microwaves. Highly directive antenna systems assure effective power transmission. This paper presents a Micro-strip rectangular patch antenna incorporated with meta-material based graded refractive index lens. Using micro-strip antenna considerably reduces the size of WPT systems as compared to other microwave antenna. In this paper, the WPT system is modeled for 2.45 GHz frequency. In addition, the antenna incorporated with meta-material lens will enhance the amount of transferred power to Wireless Sensor Network (WSN) with mitigated radiation losses.

Energy-sorted Prony analysis for identification of dominant low frequency oscillations

In modern power system, the large size areas are interconnected for better power pooling that results in increased system inertia. However, this makes power to flow over long distances and pushing tie lines to operate closer to their maximum capacity. Operating tie lines closer to maximum capacity increases the possibility of inter-area oscillations (0.1-1 Hz) between two areas and is dominating near high load density area. The modern power system with growing interconnection creates more challenges in inter-area stability analysis. This paper proposes energy-sorted Prony method for online identification of dominant modes corresponding to Low Frequency Electromechanical Oscillations (LFEOs) in highly interconnected power system using Phasor Measurement Unit (PMU) data. The proposed method overcomes the disadvantage of higher false alarm rate of basic Prony method. This disadvantage is due to trivial modes that get introduced because of higher order system used in basic Prony method. The proposed method introduces a new methodology that uses the energy-sorted Prony that calculates the energy of all modes and sorts them according to energy content, this reduces the higher false alarm rate. To verify the effectiveness of the proposed method, a test signal and a two-area, four-machine system are used and the simulated results are presented.

Modes preserving wavelet based multi-scale PCA algorithm for compression of smart grid data

In this paper, wavelet based multiscale PCA algorithm is proposed for effective compression of smart grid data under normal as well as fault conditions. The signal decomposition is done using wavelet transform, followed by the de-correlation using PCA, to achieve maximum compression, while simultaneously preserving the dominant modes of the signal and bad data rejection. The optimum decomposition scale of wavelet transform is selected based on the energy of wavelet coefficients in each scale. The proposed algorithm employing multiscale PCA computes the principal components of the wavelet coefficients at each scale, followed by combining the results at relevant scales. The wavelet coefficients of a particular scale corresponding to the dominant eigen values are retained for signal compression. The dominant modes in the signal are sorted based on their energy content. This overcomes the drawback of false detection of modes and lower accuracy of estimation which arises when systems of higher order are used. Prony analysis is performed to check ability of the compression strategy to preserve the modal information. The phasor data are simulated under fault conditions in the IEEE 30-bus system. The results from Prony analysis indicate that multiscale PCA effectively compresses the disturbance signals while preserving the model information of the signal.

Implementation of ZigBee/802.15.4 in Smart Grid communication and analysis of power consumption: A case study

Communication standards in Smart Grid intend to facilitate reliable exchange of critical data securely. But selection of suitable technology as per the application area is crucial. Communication standards being considered for establishing a network between various substations within the smart grid are WiMAX, Wi-Fi, ZigBee, Bluetooth, GSM, PLCC, UMTS, etc. Smart grid profile requires monitoring of the power and controlling it as per the user demand. As ZigBee is primarily designed for low power, control & monitoring application; it is considered to be the most challenging competitor. This paper presents ZigBee (over IEEE 802.15.4) for smart grid application in Home Area Network (HAN), Neighboring Area Network (NAN) andWide Area Network (WAN). The comparative analysis for power consumption with other standard technologies viz. Wi-Fi & Bluetooth is illustrated. Topologies in ZigBee that support the case study applications are proposed and performance for each is evaluated. Also, the transceiver chip selection criteria on the basis of power utilization is studied and results are illustrated with the help of graphs.

Dynamic phasor-based small-signal stability analysis and control of solid state transformer

The inability of the conventional grid to meet peak demand, maintain quality, continuity, and reliability in power supply is driving the growth of microgrids. However, creating a microgrid is more expensive because one of the key components, transformer, plays important role in the distribution network. The solid state transformer (SST) proposed by FREEDM centre is one of the most suitable alternatives for the conventional transformers which can help the business industries to justify the trade-off between investment and resilience. Acknowledging the importance of SST in future microgrids, this paper proposes a dynamic phasor (DP) based model for stability analysis of SST, allowing a tremendous simplification of analysis resulting in faster simulation, revealing dynamical coupling between various quantities, which is essential to modern power grids for real-time control in grid operation, especially during disturbances. Using the DP based model of SST which is further linearized, the main contribution of the paper is in proposing a modular and a cascade model of SST, the consequences of which are discussed from the point of view of ease of control and complexity. Also the challenges in integrating many SSTs with the grid are discussed.

Resonance-based Wireless Power Transfer for smart grid systems

Wireless Power Transmission (WPT) can provide solutions for power transfer in complex environment and topologically challenging locations. This technology is mainly affected by the range and efficiency of transmission. Specially, bulk power transfer using WPT is also a challenging task. WPT using resonant coupling can provide an effective solution for power transfer to sensors and monitoring meters in temperature variant environments and battery powered static and mobile devices. However, its effects related to simultaneously charging multiple units and its directional field pattern when introduced on both the transmitting as well as receiving side of the system is to be studied. This system can be expanded to transmit power from single transmitter to multiple receivers.