This paper presents a field demonstration of two emerging power system monitoring technologies in a coupled 120 V and 480 V circuit: continuous synchronized waveform recording and sub-synchronous low-amplitude probing. Challenges are addressed, including cross-device measurement alignment, the impact of transformers on synchronized data, and the signal processing required to detect low-amplitude perturbations. Experiments confirmed that low-amplitude sub-synchronous perturbations injected at a standard 120 V outlet are detectable not only by nearby 120 V waveform measurement units (WMUs) but also by a utility-grade 480 V WMU on the far side of a wye-delta transformer. This detection was made possible by precise GPS-based time synchronization and advanced signal processing techniques, including amplitude demodulation, Fourier analysis, and vector time averaging, which effectively extracted subtle probe signatures from noisy real-world data. These findings establish low-amplitude modulated probing as a practical tool for feeder-wide assessments and pave the way for low-cost active monitoring, with potential applications in stability margin assessment, inverter model validation, and network diagnostics.

Peaks and troughs in the subsynchronous impedance spectrum of a distribution feeder may be a useful indication of oscillation risk, or more importantly lack of oscillation risk, if inverter-based resource (IBR) deployments are increased on that feeder. This paper demonstrates that the impedance spectrum can be measured by GridSweep, an instrument device. GridSweep combines an active probing device that modulates a 120-volt 1-kW load sinusoidally at a user-selected GPS-phase locked frequency from 1.0 Hz to 40.0 Hz, and with a recorder that takes ultra-high-precision continuous point-on-wave (CPOW) 120-volt synchrowaveforms at 4 kHz. Our paper reveals that the measured voltage spectra by GridSweep correspond to the subsynchronous impedance spectra of distribution feeders. For demonstration, we construct an electromagnetic transient (EMT) simulation of a single-phase distribution feeder equipped with multiple IBRs. We include a model of the GridSweep probing device, then demonstrate the model’s capability of measuring the subsynchronous apparent impedance spectrum of the feeder. In addition, we show that peaks in that spectrum align with the system’s dominant oscillation modes caused by IBRs.

This paper gives an overview of the smart grids developments, seen from a power-quality viewpoint; describes the main relations between smart grids and power qu ality, and goes into some detail for some of the aspects. Diff erent types of real and virtual energy storage are distinguished. Power-quality monitoring in the smart grid is discussed in detail . Further aspects discussed in the paper are: emission by new devices; interference between devices and power-line communi cation; allocation of emission limits; improving voltage qu ality; immunity of devices; and weakening of the transmiss ion grid. Although the smart grid brings many new power-quali ty challenges, these should not result in the introduc tion of unnecessary barriers against the introduction of ne w technology.

Peaks and troughs in the subsynchronous impedance spectrum of a distribution feeder may be a useful indication of oscillation risk, or more importantly lack of oscillation risk, if inverter-based resource (IBR) deployments are increased on that feeder. GridSweep is a new instrument for measuring the subsynchronous impedance spectra of distribution feeders. It combines an active probing device that modulates a 120-volt 1-kW load sinusoidally at a user-selected GPS-phase locked frequency from 1.0 to 40.0 Hz, and with a recorder that takes ultra-high-precision continuous point-on-wave (CPOW) 120-volt synchrowaveforms at 4 kHz. This paper presents a computer simulation of GridSweep's probing and measurement capability. We construct an electromagnetic transient (EMT) simulation of a single-phase distribution feeder equipped with multiple inverter-based resources (IBRs). We include a model of the GridSweep probing device, then demonstrate the model's capability to measure the subsynchronous apparent impedance spectrum of the feeder. Peaks in that spectrum align with the system's dominant oscillation modes caused by IBRs.

This paper introduces a new application for Power Quality and Energy Monitoring: embedding power quality monitors inside sensitive industrial, commercial, automation, manufacturing and medical equipment – and bringing SmartGrid to the factory and automation floor. Using power quality monitors to solve intermittent problems has also been limited by the cost of monitors. In this case, the monitors are generally installed at the equipment terminals. So the monitors can either directly interface with the load, or they can interface via e-mail or WebServer with a remotely connected user. In addition the new technology also combines a high accuracy energy monitor that can precisely control loads based on the load profile. It also introduces IEC 61000-4-30 which is an excellent standard that ensures that all compliant power quality instruments, regardless of manufacturer, will produce the same results when connected to the same signal. However, instruments that comply with the Class A requirements of this standard have, until now, been too expensive for common use. Now a new set of technologies developed by an American company, in cooperation with a Japanese company, demonstrate that it is possible to manufacture three-phase power quality instruments that are fully compliant with the Class A requirements of IEC 61000-4-30, and to do so at ultra-low-cost, allowing these monitoring devices to be used even at entry levels of individual loads.

Continuous streaming of synchro-waveforms, i.e., time-synchronized waveform measurements, can provide a comprehensive record of the status of the power system. The key to unmask the value of such massive data recording is to extract the most informative aspects of the data. In this paper, we develop and test new methods to detect and characterize subcycle events in continuous streaming of synchro-waveforms. The measurements in this study are collected by the authors in a practical test-bed in California. The measurements are made at low-voltage circuits under two different substations, using GridSweep devices with GPS time stamping. Over 40 billion data points were collected during one month. Several practical challenges are addressed, including the computational complexity due to the enormous size of data, the need for realignment between waveform samples and cycles, and the challenges in extracting differential waveforms to reveal the event signatures.

This paper presents a novel concept: active measurements of electric power distribution grids, proposed as a new method for studying subtle dynamics such as oscillations associated with inverter-based resources. We introduce the new GridSweep instrument, with a focus on hardware design and techniques for making very precise voltage measurements. Examples of early field measurements illustrate the ability to recover a small probing signal in situ from a standard 120-volt outlet.

When designing a measuring instrument for electric power grids, it is a common mistake to think that meeting the normal specifications - cost, accuracy, measurement rate, measured parameters, size, weight, and the like - is sufficient. This paper briefly discusses other practical considerations that are often overlooked, but are important for a successful instrument: safety, operating environment, grounding, labelling, front panel design, enclosures, emissions & immunity, fasteners, mechanical shock and vibration, predictable component failures, component suppliers and instrument life cycle, tech support and documentation, and managing expectations.

This paper describes the performance of switched mode computer power supplies under voltage sags and harmonic distortions. The tests were carried out in a controlled lab environment where the basic parameters were recorded to allow a detailed analysis of the condition of the power supply under the different voltage excitations. The results show the impact of the waveforms that may affect the performance of the supplied load, but did not cause any observable damage on the power supply. With the massive use of power electronic converters for generation and load supply it is expected that higher levels of voltage distortions be present on the electric distribution system. The experiments show the need for more investigation with different types and topologies of power supplies for a comprehensive assessment of their performance.

Conventional cyber-security intrusion detection systems monitor network traffic for malicious activity and indications that an adversary has gained access to the system. The approach discussed here expands the idea of a traditional intrusion detection system within electrical power systems, specifically power distribution networks, by monitoring the physical behavior of the grid. This is achieved through the use of high-rate distribution Phasor Measurement Units (PMUs), alongside SCADA packets analysis, for the purpose of monitoring the behavior of discrete control devices. In this work we present a set of algorithms for passively learning the control logic of voltage regulators and switched capacitor banks. Upon detection of an abnormal operation, the operator is alerted and further action can be taken. The proposed learning algorithms are validated on both simulated data and on measured PMU data from a utility pilot deployment site.

Presents a collection of slides covering the following topics: power quality measurement methods; power factor correction capacitors; power line carrier coupling; power grid; semiconductor switching; smart meter measurement errors; touch-controls; dimmers; PLC interference; and IEC 61000-4-30.

As the distribution grid moves toward a tightly-monitored network, it is important to automate the analysis of the enormous amount of data produced by the sensors to increase the operators situational awareness about the system. In this paper, focusing on Micro-Phasor Measurement Unit ($μ$PMU) data, we propose a hierarchical architecture for monitoring the grid and establish a set of analytics and sensor fusion primitives for the detection of abnormal behavior in the control perimeter. Due to the key role of the $μ$PMU devices in our architecture, a source-constrained optimal $μ$PMU placement is also described that finds the best location of the devices with respect to our rules. The effectiveness of the proposed methods are tested through the synthetic and real $μ$PMU data.

Power supplies for electronic devices are now a significant segment of the total load on AC power grids. Many standards and recommendations have been developed to improve compatibility between power grids and electronic devices, including standards that set limits on voltage distortion. This work experimentally tests the compatibility of computer power supplies with high levels of voltage harmonics. It is demonstrated that the tested power supplies can tolerate much higher voltage distortions than typical limits recommended by standards. The work also shows that switched mode power supplies with unity-power-factor control (PFC) tolerate even higher levels of voltage distortion than traditional power supply designs.

The impact of Phasor Measurement Units (PMUs) for providing situational awareness to transmission system operators has been widely documented. Micro-PMUs ($μ$PMUs) are an emerging sensing technology that can provide similar benefits to Distribution System Operators (DSOs), enabling a level of visibility into the distribution grid that was previously unattainable. In order to support the deployment of these high resolution sensors, the automation of data analysis and prioritizing communication to the DSO becomes crucial. In this paper, we explore the use of $μ$PMUs to detect anomalies on the distribution grid. Our methodology is motivated by growing concern about failures and attacks to distribution automation equipment. The effectiveness of our approach is demonstrated through both real and simulated data.

This paper describes high-level findings from an innovative network of high-precision phasor measurement units (PMUs), or micro-PMUs ( ${\mu }$ PMUs), designed to provide an unprecedented level of visibility for power distribution systems. We present capabilities of the technology developed in the course of a three-year ARPA-E funded project, along with challenges and lessons learned through field deployments in collaboration with multiple electric utilities. Beyond specific applications and use cases for ${\mu }$ PMU data studied in the context of this project, this paper discusses a broader range of diagnostic applications that appear promising for future work, especially in the presence of high penetrations of variable distributed energy resources.

There is significant interest in smart grid analytics based on phasor measurement data. One application is estimation of the Thevenin equivalent model of the grid from local measurements. In this paper, we propose methods using phasor measurement data to track Thevenin parameters at substations delivering power to both an unbalanced and balanced feeder. We show that for an unbalanced grid, it is possible to estimate the Thevenin parameters at each instant of time using only instantaneous phasor measurements. For balanced grids, we propose a method that is well-suited for online applications when the data is highly temporally-correlated over a short window of time. The effectiveness of the two methods is tested via simulation for two use-cases, one for monitoring voltage stability and the other for identifying cyber attackers performing "reconnaissance" in a distribution substation.

Because electric power distribution systems are undergoing many technological changes, concerns are emerging about additional vulnerabilities that might arise. Resilient cyber-physical systems (CPSs) must leverage state measures and operational models that interlink their physical and cyber assets, to assess their global state. Here, the authors describe a viable process of abstraction to obtain this holistic state exploration tool by analyzing data from micro-phasor measurement units (μPMUs) and monitoring distribution supervisory control and data acquisition (DSCADA) traffic. To interpret the data, they use semantics that express the specific physical and operational constraints of the system in both cyber and physical realms.