Power System Monitoring Research Articles

Transformer Monitoring and Protection in Dynamic Power Systems – A Review

Increasing distributed energy resources, especially the renewable energy resources (RESs) are being installed across power systems these years. These RESs, including solar photovoltaic, wind turbines, etc., provide opportunities for operators to improve power quality, enhance power system resilience, and help meet green energy goals. However, RESs also bring challenges to the operators. As the operating conditions of RESs vary drastically, power systems may experience larger dynamics compared with the traditional power systems with limited RESs. Such dynamics may impose some impacts on devices in power systems. Transformer, as one of the critical and expensive components in power systems, is in need to be protected and monitored constantly. With this said, monitoring and protection of transformers is significant and critical in power system industry as well as in academic research. This paper presents a comprehensive review of the existing transformer monitoring and protection methods. The paper first introduces monitoring and protection approaches for the legacy low frequency transformers, as those transformers are still playing a major role between low frequency interfaces. Then, the literature of the protection of solid-state transformers, i.e., power electronics-based transformers, is investigated. A summary of the present technology of transformer monitoring and protection follows.

Design Bluetooth Low Energy for Battery and Photovoltaic Monitoring at Solar Powered Street Lamp System

In this paper, we designed an electrical power monitoring system for PV, batteries, and lamps at solar powered street lamps based on wireless sensor network (WSN) system using Bluetooth Low Energy. The power monitoring system is low-cost and open platform technology. The WSN used tree and linear topologies for data transmission and both in terms of the type of sensors and the number of sensor nodes. The distance between sensor nodes about 40 m as standard of street lamp. The network design used 2 chains in tree topology and each chain have 5 hop or nodes. The WSN at solar powered street lamps is well suited for a wide variety of applications related to environmental monitoring, because solar powered street lamps spread into remote areas and use solar energy as a main power source.

Analyzing Six Indices for Online Short-Term Voltage Stability Monitoring in Power Systems

In recent years, the importance of online monitoring short-term voltage stability has been considerably increased. Unstable cases due to response of fast dynamic loads such as induction motors to the serious disturbances can be avoided by online monitoring of voltage transients and activating fast and appropriate controls to encounter deep and prolonged voltage drop. In this paper, a set of indices based on the phasor measurement unit (PMU) measurements are introduced and compared for short-term voltage stability. To increase efficiency of the indices, a special algorithm for each index is proposed by using the investigation of the results of applying them to six disturbances’ scenarios simulated on the IEEE 39 bus system. The disturbance scenarios are representative of different cases of stable, unstable, and deep and prolonged voltage drop associated with short-term voltage transients. The performance of these indices are studied in terms of the time and accuracy required for determining the short-term voltage stability/instability cases. It is shown that the proposed method has better performance in comparison with other techniques that can be applied to power systems in reality.

ATC assessment and enhancement of integrated transmission and distribution system considering the impact of active distribution network

Assessment and enhancement of transmission network capability have been one of the prime interests of power system monitoring, operation and control. Conventionally, the issue of available transfer capability (ATC) assessment has been tackled considering the transmission and distribution networks as segregated entities because they had little or no influence on each other's performance owing to the unidirectional flow of power from the transmission to distribution networks. Now, with increasing interest in smart transmission and distribution in amalgamation with a paradigm shift in sources of generation from centralised to decentralised even at distribution levels mandating the analysis of power grid while inculcating both the hierarchies simultaneously. In this study, a platform for quasi-static operation of power transmission and distribution networks, employing a multi-agent based system has been developed. The developed multi-agent systembased system has been utilised for assessment of ATC considering active distribution network (ADN) whereby Modified IEEE 24 bus system at transmission and Modified IEEE 123 node system at distribution level has been considered as a test system. It has been observed that the presence of ADN considerably affects the ATC of the system.

Optimized placement of parasitic vibration energy harvesters for autonomous structural health monitoring

Energy harvesting, based on sources including vibration and thermal gradients, has been exploited in recent years to power telemetry, small devices, or to charge batteries or capacitors. Generating the higher levels of power which have thus far been required to run sensor systems such as those needed for structural health monitoring has been more challenging. In addition, harvesters such as those required to capture vibration often require additional elements (e.g. cantilevers) to be added to the structure and harvest over a relatively narrow band of frequencies. In aerospace applications, where weight is at a premium and vibrations occur over a broader range of frequencies, this is non-ideal. With the advent of new, lower power monitoring systems, the potential for energy harvesting to be utilized is significantly increased. This article optimizes the placement of a set of parasitic piezoelectric patches to harvest over the broad band of frequencies found in an aircraft wing and validates the results experimentally. Results are compared with the requirements of a low-power structural health monitoring system, with a closing of the gap between the energy generated and that required being demonstrated.

Self- Regulation Routing Algorithm for Power Monitoring System based on IoT Platform

Self- Regulation Routing Algorithm for Power Monitoring System based on IoT Platform

Wireless Networks for Voltage Stability Analysis and Anti-islanding Protection of Smart Grid System

With the evolution of smart grid system (SGS), many issues associated with traditional grid network, i.e., power system security, monitoring and control, energy efficiency and aging of system’s equipment are resolved. The smart system is flexible enough to integrate many DGs without violating its hosting capacity. However, during and after the integration of DGs into SGS, still many other technical problems exist in the system especially islanding and stability of system. This research proposes a modified Thevenien Equivalent model for voltage stability analysis of smart grid system. With the help of phasor measurement units (PMUs), the data is collected globally and thus voltage stability margin is determined. The dS/dV algorithm is then used to determine voltage stability at all the system nodes. The proposed scheme also provides online monitoring and control of voltage stability of Smart Grid System and results in a new efficient and economical anti-islanding technique based on WSNs. Since, WSNs are already being distributed along the entire structure of Smart Grid Systems for effective communication but can also be used as sensor nodes to record the changes in system voltage and its angle, called sag calculations. The data from sensor nodes, with the help of routing nodes will be then transferred to SCADA center for operating respective circuit breaker of affected DG wirelessly. Power-Hardware-In-Loop setup is used to validate the efficacy of propositions. The analysis is carried for normal as well as for faulty conditions.

Remote Sensing of Sewing Work Levels Using a Power Monitoring System

The measurement of sewing work in the labor-intensive garment industry depends considerably on the person performing the measurements, making it difficult to quantitatively define the level of skill (LS) of the sewing machine operator and the level of difficulty (LD) of the unit process. In this study, a power monitoring system attached to the sewing machine was used to remotely collect power consumption data, which were then analyzed to extract the working times for a series of sewing tasks. LS of each operator was then classified and LD of each process was analyzed in terms of working time and quality. Finally, the resulting LS and LD weight factors considered to optimize the subject garment production line were compared against those proposed by experts. The LS weight factor proposed by the experts was ~15% less than that indicated by the experimental results, whereas the LD weight factor proposed by the experts was ~15%–40% greater than that indicated by the experimental results. The results of this study suggest that the proposed method could be applied in real time to inform the arrangement of line workers to increase the productivity of a garment production line.

Intelligent power monitoring of building equipment based on Internet of Things technology

With the development of intelligent buildings, problems such as difficulties in system integration, poor scalability, and difficulties in coordinated operation across systems have emerged. The development of the Internet of Things technology has provided new ideas for solving these problems. This paper proposes an intelligent building architecture based on the Internet of Things technology. The data aggregation of the indoor electrical Internet of Things and public facilities integration system forms building big data, and provides decision support for building operation and maintenance management through a variety of data analysis algorithms. This paper analyzes and discusses the determination of monitoring objects, the selection and placement of monitoring points in the smart power monitoring system. By building an experimental platform, system function debugging is performed. After several experiments, the power supply device based on intelligent monitoring designed in this paper achieved the expected goal. The system was verified through experiments to realize the collection of power supply parameters, and compared with the actual data, the accuracy can meet the requirements of the monitoring system. When the power supply is abnormal, the power can be cut off in time, which effectively protects the safety of the system and confirms the feasibility of the scheme.

Synchronized Measurements Processing Methodology as a Tool for Monitoring Power System Oscillations

Synchronized Measurements Processing Methodology as a Tool for Monitoring Power System Oscillations

Phasor measuring unit calibration considering topology expansion of electric power utilities

Phasor Measuring Units (PMU) is considered as a feasible alternative for power system data communication and for the preparation of smart grid. To operate multiple PMUs in stable mode, synchronization is a much essential procedure. After examining the concise literature survey on topical PMU applications, this paper step ahead by considering prevailing objectives such as: extension of network topology and PMU calibration considering bias errors. The appropriate deployment of PMUs and intimidating situation influence the reliance on physical configuration. Hence, it is obligatory to extend the topology of the networks. Also, calibrating the PMUs in a definite trail is crucial as the phasor measurements will be corrupted by bias error. This paper proposes a novel framework for bias error detection and calibration of PMU while expanding the topology network. With a whale optimization algorithm based method to improve the accuracy of PMU measurements for enhancing power system state estimation, monitoring and control operations. Case studies on the standard test systems have been conducted to test the efficacy of the intended tool.

Synchrophasor Estimation for Three-Phase Systems Based on Taylor Extended Kalman Filtering

Synchronized phasor and frequency measurements are key tools for the monitoring and management of modern power systems. Under dynamic conditions, it is vital to define algorithms that allow accurately measuring time-varying signals with short latencies and high reporting rates. A dynamic phasor model can help the design of these algorithms and, in particular, of those based on the Kalman filter approach. This article proposes a three-phase synchrophasor estimator based on the extended Kalman filter; state variables are obtained from Taylor expansions of amplitudes and phase angles. The underlying dynamic model considers the inherent relationship among the phases and includes harmonics in an effective way. The process noise covariance matrix that allows representing the uncertainty introduced by the dynamic model has been written by considering that practical ac power systems are nearly three-phase symmetric during typical operation. This a priori information allows improving noise rejection and increasing accuracy in the presence of amplitude modulation, as highlighted by the reported simulation results.

An innovative fractional order LMS algorithm for power signal parameter estimation

Parameter estimation is an important issue for the quality monitoring and reliability assessment of power systems. In this study, an innovative fractional order least mean square (I-FOLMS) adaptive algorithm is presented for an effective parameter estimation. The I-FOLMS algorithm exploits the fractional gradient in its recursive parameter update mechanism, because its performance can be tuned by means of the fractional order. High values of the fractional order are good for fast convergence, but lead to steady state mis-adjustments. While, low values provide a smooth steady state behavior, but require a compromise in the convergence rate. The effective performance of I-FOLMS is verified and validated through two numerical examples of power signals estimation for different levels of noise variance and values of the fractional orders.

Cyber‐physical system testbed for power system monitoring and wide‐area control verification

The electric power system is intrinsically a cyber-physical system (CPS) with power flowing in the physical system and information flowing in the cyber-network. Testbeds are crucial for understanding the cyber-physical interactions and provide environments for prototyping novel applications. This study proposes a four-layer architecture for CPS testbeds with emphases on communication network emulation and networked physical components. A configurable software-defined network is employed to bridge physical components with wide-area applications for closed-loop control. In order to distribute physically coupled devices into multiple software simulations, this study proposes a data broker setup based on a distributed messaging environment to achieve low-latency data streaming. The decoupled design with data streaming allows for building testbed components as modules and running them in a distributed manner. Case studies verify the data broker setup for low-latency sensing and actuation, as well as the communication emulation setup for the desired network latency. Also illustrated is a replay attack scenario using synchrophasors in the Western Electricity Coordinating Council (WECC) 181-bus system for demonstrating the closed-loop cyber-physical simulation capability of the testbed.

Situational Awareness Enhancement in Transmission Lines using NI Based PMU

Phasor Measurement Units (PMUs) are becoming prominent in enhancing the situational awareness in wide area power system monitoring, thereby playing a vital role in its protection and control. This paper focuses on enhancing the situational awareness of transmission line using National Instruments (NI) based PMU. The data measured by the virtual PMU is used for fault detection and fault classification. The detection and the classification in the LabVIEW platform are performed using the Fourier Transform and support vector machines (SVMs) respectively. The proposed methodology has been applied on a laboratory set up consisting of transmission line, three phase load and an NI based PMU. The enhanced situational awareness in the detection and classification of transmission line faults helps in restoration of the transmission line as quickly as possible and trigger wide area control actions to maintain power system stability against the disturbances created by a fault.

Review on Oscillatory Stability in Power Grids With Renewable Energy Sources: Monitoring, Analysis, and Control Using Synchrophasor Technology

Oscillatory stability has received immense attention in recent years due to the significant increase in power electronic converter (PEC)-interfaced renewable energy sources. Synchrophasor technology offers superior capability to measure and monitor power systems in real time, and power system operators require better understanding of how it can be used to effectively analyze and control oscillations. This article reviews state-of-the-art oscillatory stability monitoring, analysis, and control techniques reported in the published literature based on synchrophasor technology. An updated classification is presented for power system oscillations with a special emphasis on oscillations induced from PEC-interfaced renewable energy generation. Oscillatory stability analysis techniques based on synchrophasor technology are well established in power system engineering, but further research is required to effectively utilize synchrophasor-based oscillatory stability monitoring, analysis, and control techniques to characterize and mitigate PEC-induced oscillations. In particular, emerging big data analytics techniques could be used on synchrophasor data streams to develop oscillatory stability monitoring, analysis, and damping techniques.

A fiber optic temperature sensor based on interference fringe contrast demodulation

We propose and verify a fiber optic temperature sensor whose demodulation method is measuring the spectra contrast, which is quantified by the amplitude of the fast Fourier transform (FFT) of interference fringes within a certain small wavelength range. A section of polarization-maintaining fiber (PMF) is spliced in the sensing arm of the Mach-Zehnder interferometer (MZI). Due to the birefringence of the PMF, a visible envelope is formed in the interference fringes. Within a certain range of optical frequency (i.e. wavelength), the change of birefringence caused by external temperature will drive the envelope drift, and the amplitude of interference fringe after fast Fourier transform will also change correspondingly. By measuring the change of amplitude, the purpose of demodulating external temperature can be realized. Experimental results show high sensitivity better than 2.1 dB/°Cwith a high accuracy of 0.00048 °C, comparing with the envelope drift measuring results 1.62 nm/°C with resolution of 0.012 °C. The resolution of this scheme is increased by two orders of magnitude compared with measuring the envelope drift. Moreover, merits of our sensor in terms of immune to phase shift of reference arm and the power fluctuation of light source benefit our practical application for such as electric power system monitoring.

Enhanced data communication models for real‐time power system monitoring in a distributed platform

ABSTRACTThe novelty behind this research is to develop enhanced models for real‐time power system monitoring in a platform‐independent and distributed platform. Distributed models for power system applications have been implemented using Remote Method Invocation (RMI), Common object Request Broker Architecture and. NET remoting technologies. The interoperability among the heterogeneous power system clients in a distributed platform has been achieved through XMLization of power system data which provides meaningful solution to the legacy issues associated with power systems. A RMI‐based model for real‐time power system monitoring in a distributed platform had been implemented and discussed in detail. A component model for real‐time power system monitoring has also been proposed and implemented to increase the reusability and scalability of the system. A location transparent model has been developed using Common object Request Broker Architecture with RMI‐Internet Inter‐Orb Protocol for load flow monitoring and the idea is extended to solve real‐time economic load dispatch and dynamic security monitoring. The detailed monitoring on performance of the proposed models has been done with load flow monitoring, dynamic security monitoring and economic load dispatch problems. A. NET remoting architectural model has been developed for real‐time economic load dispatch in a distributed platform. This research paper explores various issues in deploying power system applications in a distributed platform. It will serve the purpose of stimulating interest among power engineers and also will be extremely useful for electric power utilities.

Remote interactive platform for matching design of ship screw propeller and diesel engine based on Internet Plus

In order to meet the requirements of the remote ship propeller matching design, and can feed the measurement data to the offshore calculation model to guide the design of the ship propulsion system, this paper designed a screw propeller matching computing platform based on the internet. The platform was built on the B/S architecture, combined with MATLAB and C# for mixed programming, and used EasyUI plug-in set to design user interface. The open water characteristics of the ship were selected as the fundamental data of the whole process of matching calculation. The platform was tested by three parts: the preliminary matching, ultimate matching and cavitation checking. By comparison, the difference between calculated value and actual value is very small, which can meet the accuracy requirements. This platform can provide an engineering basis for the online working condition monitoring of the ship power system and the dynamic matching of the ship propeller in the 'Internet Plus' environment in future.

Power Quality and Energy-Efficient Operation of Marine Induction Motors

Ship power systems are characterised by a comparatively high level of various power quality disturbances, such as voltage deviations, frequency deviations, voltage waveform distortions and sometimes voltage unbalance, which exert a detrimental effect on energy receivers. Among other things, power quality disturbances may cause an extraordinary increase in power losses occurring in on-board induction motors as well as ineffective utilisation of their mechanical output power. In this study, the results of empirical research which demonstrates how power quality disturbances in real ship microgrids affect induction motors are shown. The results of power quality monitoring in ship power systems from the point of view of the energy-efficient operation of induction motors are presented for various vessels and operating conditions. Recommendations concerning the revision of power quality standards and rules are elaborated to provide more energy-efficient ship operation.