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Measuring Phase Angle Change in Power Lines

University of California, Berkeley (UC Berkeley)

Micro-Synchrophasors for Distribution Systems

Program: 
ARPA-E Award: 
$6,182,674
Location: 
Berkeley, CA
Project Term: 
03/01/2013 to 06/30/2018
Project Status: 
ALUMNI
Technical Categories: 
Critical Need: 

Today, power generally flows in one direction along the grid: from the generation source to the end user. In the power grid of the future, many electricity generators--including home solar power arrays and wind turbines--will cause power to flow in multiple directions along distribution lines. As the grid matures and expands in complexity to accommodate multi-directional power flow, new technologies are needed to monitor the direction of power flow along the distribution lines to ensure grid stability and reliability.

Project Innovation + Advantages: 

The University of California, Berkeley (UC Berkeley) is developing a device to monitor and measure electric power data from the grid's distribution system. The new instrument--known as a micro-phasor measurement unit (µPMU)--is designed to measure critical parameters such as voltage and phase angle at different locations, and correlate them in time via extremely precise GPS clocks. The amount of phase angle difference provides information about the stability and direction of power flow. Data collected from a network of these µPMUs would facilitate better monitoring and control of grid power flow--a critical element for integrating intermittent and renewable resources, such as rooftop solar and wind energy, and other technologies such as electric vehicles and distributed storage.

Potential Impact: 

If successful, utilities will be able to use UC Berkeley's µPMU micro-synchrophasor data to enhance grid reliability and transform the electric power industry by providing new information about grid stability at local, regional, and system-wide levels.

Security: 

This project could contribute to a smarter, more reliable, more advanced, and secure electric grid.

Environment: 

Enabling more renewable energy sources--such as wind and solar--would reduce the need for coal-fired power plants for electricity generation, reducing the harmful emissions that come from these plants.

Economy: 

Improving local management of energy resources and increasing deployment of renewable generation could position the U.S. as the technological and economic leader in developing and deploying advanced energy technologies.

Innovation Update: 
(As of December 2016) 
The UC Berkeley team and its partners have developed new µPMU and database infrastructure capable of quickly analyzing and processing µPMU data streams. Their technology is enabling the development of utility-grade real-time distribution network monitoring and control applications. 
 
Partner company Power Standards Lab (PSL) is already making commercial hardware sales of the µPMU in the United States and internationally. Customers to date include Tesla, SolarEdge, the National Institute of Standards & Technology, Sandia National Laboratories, and researchers in Japan, Belgium, France, and Poland. PSL is also selling µPMU QuickStart kits that include a small number of devices and the software needed to collect and analyze data. 
 
In addition, three commercialization partners—Smarter Grid Solutions, Doosan GridTech, and Ping Things—are facilitating the development of utility-ready applications using the team’s database software. Initial applications will focus on giving utilities the tools to monitor and manage distribution feeders with higher penetrations of photovoltaic solar generation and/or energy storage. The project has directly resulted in five full-time equivalent manufacturing jobs in California, with the potential to reach more than 100 in five years. 
 
The UC Berkeley team’s objective was to develop and test µPMU hardware and explore and validate potential µPMU data applications valuable for utilities. 
 
The team also engineered a new, unified and commercially viable sensor that achieves the resolutions and sensitivities necessary for distribution system management. They developed a completely new database infrastructure for high-resolution, time-synchronized data to enable processing and analysis of µPMU data streams. They also built new firmware for existing “PQube” power quality measurement devices and integrated it with a GPS receiver in order to achieve extremely high precision and temporal resolution. In order to gather tens of terabytes of data, they tested and deployed an integrated network of 44 µPMUs both within the lab and in various field settings with five partner utilities. 
 
The team also developed an innovative software named Berkeley Tree Database (BTrDB). BTrDB allows for extremely fast multi-scale analysis of data, thereby enabling prediction and anomaly detection across the range of voltage, current, and time-scales that affect distribution performance. 
 
Using µPMU data, the team empirically characterized the steady-state and dynamic behavior of a set of electricity distribution circuits, developed a set of basic diagnostic applications, and laid the theoretical foundation for leveraging µPMU data in future control applications. The team’s study of early µPMU measurements revealed numerous conditions that were either unknown or suspected but not previously verifiable for distribution system operators. They developed early versions of working diagnostic tools with empirical µPMU data, including applications for model validation and for detection and classification of disturbance events (e.g. to identify causes of outages). 
 
For a detailed assessment of the UC Berkeley project and impact, please click here.
 
 
Contacts
ARPA-E Program Director: 
Dr. Kory Hedman
Project Contact: 
Dr. Alexandra von Meier
Partners
Doosan GridTech
Lawrence Berkeley National Laboratory
PingThings Inc.
Power Standards Lab
Smarter Grid Solutions
Release Date: 
11/28/2012