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The Buzz About Micro-Synchrophasors at IEEE PES

August 29, 2016 / Jill Feblowitz / Integrating Renewables, Synchrophasors

There is no question that distributed energy resources (DER) will continue to proliferate on the grid.  However, there are questions about how best to plan for, monitor and manage the two-way flow of electricity on the distribution grid.  It is not surprising, then, that the industry is beginning to look technologies that can cost-effectively provide benefits to the distribution grid, compared to other technologies.  One of those technologies – the micro-synchrophasor – was the subject of at least eight papers presented at the annual IEEE Power and Energy Society Annual meeting in July.

Synchrophasor technology has already seen success in improving transmission grid planning and operations.  The August 2003 Northeast blackout raised concerns insufficient situational awareness of the state of the transmission grid.  In response, the DOE and industry partners, under the ARRA, invested more than $357 million to deploy synchrophasor technology.  Over 1,700 phasor measurement units (PMUs) are now in place providing almost complete visibility to the North American transmission grid.  Just as important, the funding helped advance synchro-phasor technology, communications design and cybersecurity, as well as information sharing among the ISOs/RTOs.  Operational and planning capabilities now support improvements in reliability, power and organizational efficiency, and asset utilization (see Advancement of Synchrophasor Technology, March, 2016).

While synchrophasors have already proven valuable for transmission, conditions are different for distribution.    Distribution networks have smaller voltage angle differences, more noise in measurements, different ratios between reactance and resistance, unbalanced three phase systems.  Besides, distribution network models have poorer fidelity.  There are distinct implications for distribution vs. transmission:

  • Deployment of significantly more geo-located PMUs
  • Handling of large volumes of data
  • Capabilities to filter noise, data validation
  • Development of methodologies and corresponding algorithms for analysis of the data


Adding to potential cost and complexity is whether micro-synchrophasor technology is used for minute- by-minute operational control vs. planning that can be done over weeks and months.

Probably the most visible micro-synchrophasor study to date is one funded by ARPA-E.  In 2012, ARPA-E funded a three year, $4.4M project – Micro-Synchrophasors for Distribution Systems –  with research partners the California Institute of Energy and the Environment, UC Berkeley, Lawrence Berkeley Lab and the Power Standards Lab.  The studies included field installations of micro-PMUs at several utilities. The project developed a framework for handling data and analytics (see Figure 1) using wired and wireless micro-PMU connections, data center/cloud, visualization and third party analytics.  There is also an architecture for event search and diagnostics (see Figure 2).

Data Collection - Micro PMUs

Iterative Learning - Micro Synchrophasor

Researchers tested approaches to using micro-PMUs and synchrophasor analytics for:

  • Model validation – to confirm, deny or correct existing distribution network models
  • Distribution state estimation – along with AMI and SCADA data, to estimate voltage phasors throughout the entire distribution network, including unmonitored areas
  • Topology detection – to detect whether switches are open or closed
  • Fault location –to detect faults on the network
  • Event identification – to detect and explain disturbance events
  • Distribution generation load characterization – to measure and understand time variation among distributed generation (DG) and loads, and how DG affects distribution networks
  • Phasor-based control – to explore whether devices can be used for multiple control objectives such as voltage profile management, loss minimization, ancillary services coordination, balancing generation and load on a micro-grid, micro-grid islanding decisions based on grid behavior, assisted network reconfiguration


There is still work to be done.   For commercialization of the technology bundle, work is needed to develop software and applications, plan for PV, and support cybersecurity.  Additional research is required to facilitate the use of other data (AMI, SCADA) with micro-PMU data, to build algorithms – a painstaking process that could be helped by machine learning, to architect predictive analytics, and to enable micro-synchrophasors for control.

The micro-PMU was developed to be lower cost than the transmission PMU which have proven to be quite costly where there is insufficient communications infrastructure.  The micro-PMU can communicate wirelessly, but that raises the specter of cybersecurity breaches.   Even with a much lower hardware costs, are many more units to be deployed, raising installation costs.  Utilities will need to develop a plan to deploy micro-PMUs that allows for efficiency, along with the ability to estimate “missing” nodes.

Many utilities are piloting various technologies, but there also needs to be a comprehensive review of available technologies in the context of objectives to arrive at the most cost-effective approaches.  In an age where software and control systems are embedded in equipment, it may be difficult to sort out.    For example, smart meters, smart inverters, and advanced distribution management may be able to provide data and/or control capabilities, but will these technologies be complementary or competing with micro-synchrophasors? Edge computing using mesh connected equipment with embedded computing will likely also play a role in the future, but may not provide the centralized command and control needed to manage the distribution network.  The challenge for the industry is to juggle the time to development and deployment of the best technology with the rapidly changing distribution grid.

What do you think?



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