The electric power industry has undergone extensive changes over the past several decades and become substantially more complex, dynamic, and uncertain, as new market rules, regulatory policies, and technologies have been adopted. The availability of more detailed data about system conditions from devices, such as phasor measurement units (PMUs) for wide area visibility and advanced meter infrastructure (AMI) for dynamic pricing and demand response, can be a great benefit for electric system reliability and flexibility. However, this large volume (and variety) of data poses its own challenges.
Shifting operational data analytics from a traditionally off-line environment to real-time situational awareness (e.g., visibility) to measurement-based, fast control will require significant advancements in algorithms and computational approaches. The Advanced Modeling Grid Research Program leverages scientific research in mathematics for application to power system models and software tools. In achieving this goal, the Program also fosters strategic, university-based power systems research capabilities.
Advanced Modeling Grid Research Awards
Based on a competitive solicitation issued in May 2012 to leverage scientific advancements in mathematics and computation for application to power system models and software tools, the Office of Electricity Delivery and Energy Reliability has selected the following five projects for awards totaling $6.8 million. These projects will result in a new class of decision support tools that will simulate dynamic events and help inform operators on real-time conditions to maintain stability. The awards and final funding levels are subject to negotiations.
Electric Power Research Institute (EPRI) – Knoxville, TN
DOE share: $1.5 million; Recipient share: $622,812
This project will develop a comprehensive set of innovative technical approaches and software tools to support operators’ situational awareness and decision-making. The integrated tools will combine high-performance dynamic simulation results with synchrophasor measurement data to assess in real time the system dynamic performance and operational security risk.
Michigan State University (MSU) – East Lansing, MI
DOE share: $1.5 million; Recipient share: $375,000
This project will develop a Lyapunov function based remedial action screening (L-RAS) tool that will use real-time data. This approach supports selection of appropriate remedial actions that are most likely to result in stabilizing trajectories.
Illinois Institute of Technology (IIT) – Chicago, IL
DOE share: $1.5 million; Recipient share: $375,206
This project will accelerate performance and enhance accuracy of dynamics simulations, enabling operators to maintain reliability and steer clear of blackouts. This effort forms the backbone of a hybrid real-time protection and control architecture.
General Electric Global Research (GE) – Niskayuna, NY
DOE share: $1,279,959; Recipient share: $319,990
This project will apply advanced computational techniques to the Positive Sequence Load Flow (PSLF) dynamic simulation software to demonstrate faster than real-time dynamic simulation. This will be coupled with expertise in small signal stability to develop a proof-of-concept for a fast contingency screening and control action engine.
PowerWorld Corporation – Champaign, IL
DOE share: $1,033,040; Recipient share: $258,260
This project will develop a faster than real-time dynamic simulation tool in the transient stability to short-term voltage instability or oscillatory stability time frame (from cycles to minutes) that can be used by operators of large, interconnected power grids for enhanced near real-time dynamic operational awareness and security decision-making.