Phase Identification in Power Distribution Grids Using Synchrophasors

Introduction

As the demand for energy increases and power distribution networks become more complex, phase information awareness has become crucial for effective network management, maintenance operations, and power quality. Accurate phase identification is vital for several reasons:

1. Accurate Analytics and Power Flow Calculations: With the advancement of digitalization in power distribution networks, advanced analytical functions rely on accurate three-phase models. These models provide significant benefits, including precise power-flow calculations and reliable analytics, especially in low-voltage networks. This ensures that the network conditions are well-understood and managed effectively.

2. Maintaining Correct Phase Information: As the power system network evolves daily, accurate phase information in all backend IT (Information Technology) systems is essential. Changes made in the field must be properly accounted for to ensure that the database reflects the current state of the network.

3. Improved Service and Maintenance Procedures: Accurate phase information in backend systems enables efficient execution of service and maintenance procedures. For example, only customers connected to specific phases should be notified about power cuts due to maintenance procedures. Additionally, accurate phase data helps assess the customers affected by single-phase faults or tripped fuses, improving response times and service quality.

4. Enhanced Operational Efficiency: With correct phase identification, utilities can optimize load balancing, reduce the risk of phase overloads, and improve overall network stability. This leads to fewer outages and better resource management.

Accurate phase identification with modern digital tools in power distribution networks is beneficial and necessary for these systems' correct and efficient operation. The adoption of synchrophasor technology enables this.

Underlying technology

A brief history of synchrophasors

Synchronized phasor measurements, also called Synchrophasors, measure voltage and current signals synchronously at different locations of power grids. The concept of synchrophasors and their development can be attributed to Dr. Arun G. Phadke and Dr. James S. Thorp from Virginia Tech. These men pioneered using GPS technology to synchronize phasor measurements across broad areas of the power grid in the 1980s (see Figure 1 with a basic schematic of a PMU setup). 

Over the decades, synchrophasor technology has evolved significantly and applied in numerous power grid applications, ranging from observability to control.

Synchrophasor adoption by Phasor Measurement Units

A Phasor Measurement Unit (PMU) measures electrical signals on an electricity grid. PMU data includes voltage and current magnitude, phase angles, frequency, and Rate of Change of Frequency (ROCOF). They time-stamp these measurements via GPS, providing real-time data essential for monitoring and managing the stability and efficiency of power grids.

PMUs broadly utilize synchrophasor technology. The first PMUs were developed in the late 1980s, primarily for research. By the late 1990s and early 2000s, the technology had matured, and transmission grid system operators began to recognize the benefits of using PMUs for real-time grid monitoring and control.

The 2003 blackout in North America highlighted the need for better grid monitoring and control, leading to increased interest and investment in PMU technology. In response, the North American SynchroPhasor Initiative (NASPI) was established in 2006. NASPI is a collaborative effort between the U.S. Department of Energy, the Electric Power Research Institute (EPRI), utilities, vendors, and other stakeholders to advance the development and deployment of synchrophasor technology.

NASPI promoted the widespread adoption of PMUs by providing a platform for knowledge sharing, best practices, and standards development. The US Department of Energy and other organizations funded the deployment of PMUs across the power grid. By the 2010s, the technology became a standard tool for modern grid management, and PMUs were widely deployed.

In addition to traditional PMUs, developing micro-PMUs (or micro phasor measurement units – µPMUs) have advanced synchrophasor technology. Micro-PMUs are high-precision, small-scale versions of traditional PMUs that provide even more granular data on the electrical grid's performance. 

They were developed to meet the needs of distribution networks, which require higher precision than transmission grids because of smaller power flows and smaller reactance to resistance ratios (X/R) of the conductors. The first micro-PMUs were developed in the early 2010s via collaborations among universities, research institutions, and industry partners. These devices enable enhanced visibility into the distribution grid, supporting applications like fault detection, load monitoring, and distributed resource integration.

Application of synchrophasors to phase identification

Synchrophasor technology is highly effective for phase identification on energized conductors between geographically distinct locations. This identification process involves comparing time-synchronized measurements from two devices. One device is the reference point, while the second measures the unknown phase. By comparing the phase angle measured at the second location with the reference phase, the unknown phase can be accurately identified, as shown in Figure 2.

Voltage phase angle shift due to transformer connection

This type of phase identification is typically performed at the same voltage level. However, measurements spanning different voltage levels introduce additional complications. Specifically, a transformer between the voltage levels can introduce a phase shift between its primary and secondary sides due to its very nature. 

This phase shift is a known design parameter specified by the transformer's vector group. Figure 3 shows a typical distribution transformer and its windings.

The vector group indicates the phase difference between the primary and secondary windings due to the transformer's design. Consider, for instance, the distribution transformer with a Dy5 connection depicted in Figure 4. 

In this setup, the phase of the flux on the primary winding excited by the winding connected to the line-to-line voltage between phases L1 and L2 will be coupled with the secondary winding on the same column. The induced voltage on the secondary winding will be in phase with the flux in the column and thus in phase with the L1 to L2 line-to-line voltage.

However, changing the phase sequence on the primary winding alters the phase relationship. If the primary winding's phase sequence is reversed from 1-2-3 to 1-3-2, the phase of the voltage on the primary winding will be 210°, equivalent to vector group 7. 

Consequently, the phase of the voltage on the secondary winding of the first column will be 210°, equivalent to vector group 7. Instead of the typical 150° rotation for vector group 5, this results in a -150° rotation (or 210°), as shown in Figure 5. Therefore, the field rotation on the primary winding of D-connected transformers is also a crucial parameter in correctly determining the phase.

Synchrophasor technology can be applied to accurate phase identification across different voltage levels by understanding and compensating for these phase shifts.

Voltage phase angle shift due to current flow in power lines

Before integrating all the concepts, it's essential to understand another electrical phenomenon: the shift in voltage phase angle due to current flow in power lines. Power lines are typically aluminum conductors with a steel core for reinforcement. These conductors have specific properties dependent on their material and geometry, influencing electrical current and voltage along the line.

Power lines are commonly modeled using a pi model, as shown in Figure 6, which includes three relevant parameters: series resistance, series reactance, and shunt susceptance. When current flows through the line, the voltage phase will shift based on the ratio of series reactance to series resistance.

In power networks, the conductor properties cause voltage phase shifts due to current flow. These phase shifts also need to be considered for accurate phase identification.

The Dewesoft Gridphase solution

Dewesoft Gridphase is the first solution to integrate synchrophasor measurement technology with comprehensive network information, including transformers and their vector groups. This integration simplifies phase identification to a process as straightforward as measuring voltage. It works by placing a reference device where the phase reference is defined, typically at the point of coupling with the transmission network. Figure 7 shows a substation with incoming high-voltage lines and their phases tagged on the portals. 

The background model incorporates information about transformers and their connections, including the location of reference devices. This allows the system to compensate accurately for phase shifts introduced by transformers at any network point. The schematic in Figure 8 illustrates the conditions. 

The field rotations on the primary windings of distribution transformers are often unknown. However, information about the vector groups can be inferred from the measurements. Dewesoft Gridphase will also indicate field rotation on the primary windings of the transformer when the measurement is performed downstream, as shown in Figure 9.

Phase shifts due to current flows in conductors are not directly compensated. Instead, Dewesoft introduces the concept of angle zones (see Figure 10). The power network is divided into geographical areas, each within which the voltage phase angle deviation from the reference point is expected to be no more than ±20°. These areas are called angle zones. Since voltage phases are 120° apart, a ±20° margin on any of the phases is tolerable, still allowing for accurate phase identification. 

The backend application assigns each handheld device to the appropriate angle zone based on its location and selects the appropriate reference device within the angle zone. Based on the network model, the application compensates for the phase shifts due to vector groups, and the user selects the distribution transformer suggested by the mobile application.

This is shown in the video below.

Application of Dewesoft Gridphase in distribution grids

Phase grouping of measurement points, such as smart meters in distribution grids, is typically performed using data analytics or, when available, PLC communication. All protocol versions of PLC communication offer integrated phase identification for meters downstream from the data concentrator. 

This information is usually propagated back into IT and OT systems such as GIS (Geographic Information System), SCADA (Supervisory Control and Data Acquisition), or ADMS (Advanced Distribution Management) systems, which aggregate and display measurements and real-time data from sensors such as PMUs and PLCs, providing operators with insights into grid performance and stability.

It is important to note that regardless of the technology used, the results are not referenced to an actual electrical phase frame but are instead grouped by phases that are not aligned to an actual electrical phase frame. Consequently, the phase designated as L1 on distribution transformer A may not correspond to the phase designated as L1 on distribution transformer B. This discrepancy means that there can be no direct comparison between phases across different distribution transformers, even if they are on the same medium voltage feeder, especially across different medium voltage feeders.

Maintaining alignment to actual electrical phases across the entire network is crucial for accurate calculations and simulations, such as power-flow analysis in power distribution networks. Without a unified phase frame, these simulations will not yield correct results.

From a scalability perspective, data analytics and phase identification using a PLC are practical approaches, enabling power grid operators to quickly identify where power meters are available across the entire network. However, an additional step is needed to align the identified groups to an actual electrical phase frame. This can be efficiently achieved with a single measurement at a load or substation using Dewesoft Gridphase. By doing so, utilities can compare phases across the network, providing several advantages: three-phase power flow calculations will yield accurate results, and the impact of single-phase faults can be correctly evaluated down to the last customer on the low-voltage network.

Maintaining a unified phase frame is even more important from a maintenance perspective. For example, during service restoration after a fault, restoring the absolute phase sequence is crucial to ensure the information in backend systems remains correct. Additionally, when connecting new assets to the network, such as distribution transformers, potential transformers, switchgear, cables, and lines, proper phase connections can be maintained, ensuring the integrity and accuracy of the network's phase information, enhanced fieldwork safety, and more efficient work execution.

Dewesoft Gridphase thus ensures a coherent and unified phase framework, enhancing the reliability and accuracy of power distribution management.

Conclusion

Dewesoft Gridphase represents a significant advancement in phase identification for power distribution networks. Leveraging synchrophasor technology addresses the critical need for precise and reliable phase identification across complex and evolving power grids. The ability to accurately identify phases without the need for cumbersome installations simplifies the process, making it accessible and efficient for linemen on the field.

The implementation of Dewesoft Gridphase ensures that power distribution networks maintain a unified phase framework, which is crucial for accurate analytics, effective maintenance, and operational efficiency. With features like compensation for transformer phase shifts and the innovative concept of angle zones, Dewesoft overcomes traditional challenges associated with phase identification.

In practical applications, Dewesoft Gridphase enhances the accuracy of power-flow calculations, improves response to faults, and ensures consistent phase information across different voltage levels. This optimizes resource management and reduces operational costs. As power networks continue to expand and digitalize, tools like Dewesoft Gridphase are indispensable for maintaining them.