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ProsumerGrid, Inc.

Distribution System Operator Simulation Studio

ProsumerGrid, Inc, with its partners, will develop a highly specialized and interactive software tool capable of simulating the operation of emerging DSOs at the physical, information, and market levels while capturing the interactions among the various market participants. The software will offer electricity industry analysts, engineers, economists, and policy makers a "design studio environment" in which various propositions of participant roles, market rules, business processes, and services exchange can be studied to achieve a robust DSO design. The software will utilize a powerful decentralized decision-making algorithm, and extend state-of-the-art grid solvers with the ability to develop DER scheduling, DSO market rules, and energy service transactions. The tool could ensure correctness and reduce risk in upcoming regulatory decisions as various states move towards the formation of DSOs.

RamGoss, Inc.

Development of High-Performance Gallium Nitride Transistors

RamGoss is using innovative device designs and high-performance materials to develop utility-scale electronic switches that would significantly outperform today's state-of-the-art devices. Switches are the fundamental building blocks of electronic devices, controlling the electrical energy that flows around an electrical circuit. Today's best electronic switches for large power applications are bulky and inefficient, which leads to higher cost and wasted power. RamGoss is optimizing new, low-cost materials and developing a new, completely different switch designs. Combined, these innovations would increase the efficiency and reduce the overall size and cost of power converters for a variety of electronic devices and grid-scale applications, including electric vehicle (EV) chargers, large-scale wind plants, and solar power arrays.

Rensselaer Polytechnic Institute

High-Voltage, Bi-Directional MOS-Gated SiC Power Switches for Smart Grid Utility Applications

RPI is working to develop and demonstrate a new bi-directional transistor switch that would significantly simplify the power conversion process for high-voltage, high-power electronics systems. A transistor switch helps control electricity, converting it from one voltage to another or from an Alternating Current (A/C) to a Direct Current (D/C). High-power systems, including solar and wind plants, usually require multiple switches to convert energy into electricity that can be transmitted through the grid. These multi-level switch configurations are costly and complex, which drives down their overall efficiency and reliability. RPI's new switch would require fewer components than conventional high-power switches. This simple design would in turn simplify the overall power conversion process and enable renewable energy sources to more easily connect to the grid.

Sandia National Laboratory

Improved Power System Operations Using Advanced Stochastic Optimization

Sandia National Laboratories is working with several commercial and university partners to develop software for market management systems (MMSs) that enable greater use of renewable energy sources throughout the grid. MMSs are used to securely and optimally determine which energy resources should be used to service energy demand across the country. Contributions of electricity to the grid from renewable energy sources such as wind and solar are intermittent, introducing complications for MMSs, which have trouble accommodating the multiple sources of price and supply uncertainties associated with bringing these new types of energy into the grid. Sandia's software will bring a new, probability-based formulation to account for these uncertainties. By factoring in various probability scenarios for electricity production from renewable energy sources in real time, Sandia's formula can reduce the risk of inefficient electricity transmission, save ratepayers money, conserve power, and support the future use of renewable energy.

Silicon Power Corporation

Optically-Switched 15kV SiC Single-Bias High-Frequency Thyristor

Silicon Power is developing a semiconducting device that switches high-power and high-voltage electricity using optical signals as triggers for the switches, instead of conventional signals carried through wires. A switch helps control electricity, converting it from one voltage or current to another. High-power systems generally require multiple switches to convert energy into electricity that can be transmitted through the grid. These multi-level switch configurations use many switches which may be costly and inefficient. Additionally, most switching mechanisms use silicon, which cannot handle the high switching frequencies or voltages that high-power systems demand. Silicon Power is using light to trigger its switching mechanisms, which could greatly simplify the overall power conversion process. Additionally, Silicon Power's switching device is made of silicon carbide instead of straight silicon, which is more efficient and allows it to handle higher frequencies and voltages.

Smart Wire Grid, Inc.

Distributed Power Flow Control Using Smart Wires for Energy Routing

Smart Wire Grid is developing a solution for controlling power flow within the electric grid to better manage unused and overall transmission capacity. The 300,000 miles of high-voltage transmission line in the U.S. today are congested and inefficient, with only around 50% of all transmission capacity utilized at any given time. Increased consumer demand should be met in part with a more efficient and economical power flow. Smart Wire Grid's devices clamp onto existing transmission lines and control the flow of power within--much like how internet routers help allocate bandwidth throughout the web. Smart wires could support greater use of renewable energy by providing more consistent control over how that energy is routed within the grid on a real-time basis. This would lessen the concerns surrounding the grid's inability to effectively store intermittent energy from renewables for later use.

Stanford University

Open and Scalable Distributed Energy Resource Networks

Stanford University will develop Powernet, an open-source and open architecture platform for scalable and secure coordination of consumer flexible load and DERs. Powernet will be based on the principle of connecting information networks to the power network (connecting bits and watts). It uses a layered architecture that enables real-time coordination of centralized resources with millions of DERs by integrating embedded sensing and computing, power electronics, and networking with cloud computing. The team will develop a Home Hub system capable of networking with existing inverters and appliances in a home and controlling power via smart switches that replace traditional fuses. The Home Hub will also use algorithms for aggregating local customer resources to meet local constraints and global coordination objectives. A cloud-based cloud coordinator platform will be developed that executes optimization and monitoring functions to coordinate Home Hubs by minimizing costs while increasing aggregate consumer quality-of-service.

Switched Source LLC

Unified Power Flow Controller

Texas Engineering Experiment Station

Robust Adaptive Topology Control (RATC)

The RATC research team is using topology control as a mechanism to improve system operations and manage disruptions within the electric grid. The grid is subject to interruption from cascading faults caused by extreme operating conditions, malicious external attacks, and intermittent electricity generation from renewable energy sources. The RATC system is capable of detecting, classifying, and responding to grid disturbances by reconfiguring the grid in order to maintain economically efficient operations while guaranteeing reliability. The RATC system would help prevent future power outages, which account for roughly $80 billion in losses for businesses and consumers each year. Minimizing the time it takes for the grid to respond to expensive interruptions will also make it easier to integrate intermittent renewable energy sources into the grid.

University of California, Berkeley

Micro-Synchrophasors for Distribution Systems

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.

University of California, San Diego

Distributed Grid Control of Flexible Loads and DERs for Optimized Provision of Synthetic Regulation Reserves 

The University of California, San Diego (UCSD) will develop coordination algorithms and software using intelligent control and optimization for flexible load and DERs to provide reliable frequency regulation services for the bulk power grid. The project will develop a multi-layer framework for larger-scale energy aggregators to act on behalf of their smaller-sized customers to help respond to incoming requests from regional transmission operators. The team will develop approaches that aggregators can use to quantify reserves, system objectives and constraints, customer usage patterns, and generation forecasts. Aggregators will use distributed coordination algorithms to rapidly respond to operators while considering network constraints and quality of services for customers. The UCSD's technology to manage flexible loads and DERs offers economic and operational advantages for utilities, operators and customers.

University of Illinois, Urbana Champaign

Cyber-Physical Modeling and Analysis for a Smart and Resilient Grid

UIUC is developing scalable grid modeling, monitoring, and analysis tools that would improve its resiliency to system failures as well as cyber attacks, which can significantly improve the reliability of grid operations. Power system operators today lack the ability to assess the grid's reliability with respect to potential cyber failures and attacks. UIUC is using theoretical and practical techniques from both the cyber security and power engineering domains to develop new algorithms and software tools capable of analyzing real-world threats against power grid critical infrastructures including cyber components (e.g. communication networks), physical components (e.g. power lines), and interdependencies between the two in its models and simulations.

University of Illinois, Urbana Champaign

Synthetic Data for Power Grid R&D

The University of Illinois at Urbana-Champaign, with partners from Cornell University, Virginia Commonwealth University, and Arizona State University will develop a set of entirely synthetic electric transmission system models. Their 10 open-source system models and associated scenarios will match the complexity of the actual power grid. By utilizing statistics derived from real data, the team's models will have coordinates based on North American geography with network structure, characteristics, and consumer demand that mimics real grid profiles. Smaller models will be based on smaller areas, such as part of a U.S. state, while the large models will cover much of the continent. All models and their scenarios will be validated using security-constrained optimal power flows, with parameters tuned to emulate the statistical characteristics of actual transmission system models.

University of Michigan

High Fidelity, Year Long Power Network Data Sets for Replicable Power System Research

The University of Michigan, with partners from Los Alamos National Laboratory, the California Institute of Technology, and Columbia University, will develop a transmission system data set with greater reliability, size, and scope compared to current models. The project combines existing power systems data with advanced obfuscation techniques to anonymize the data while still creating realistic models. In addition, the project delivers year-long test cases that capture grid network behavior over time, enabling the analysis of optimization algorithms over different time scales. These realistic datasets will be used to develop synthetic test cases to examine the scalability and robustness of optimization algorithms. The team is also developing a new format for capturing power system model data using JavaScript Object Notation and will provide open-source tools for data quality control and validation, format translation, synthetic test case generation, and obfuscation. Finally, the project aims at developing an infrastructure for ensuring replicable research and easing experimentation, using the concept of virtual machines to enable comparison of algorithms as hardware and software evolve over time.

University of Minnesota

Enabling the Grid of the Future

The University of Minnesota will develop a comprehensive approach that addresses the challenges to system reliability and power quality presented by widespread renewable power generation. By developing techniques for both centralized cloud-based and distributed peer-to-peer networks, the proposed system will enable coordinated response of many local units to adjust consumption and generation of energy, satisfy physical constraints, and provide ancillary services requested by a grid operator. The project will apply concepts from nonlinear and robust control theory to design self-organizing power systems that effectively respond to the grid events and variability. A key feature enabled by the proposed methodology is a flexible plug-and-play architecture wherein devices and small power networks can easily engage or disengage from other power networks or the grid. The project's design approach will be tested across many different scenarios while using more than 100 actual physical devices such as photovoltaics, battery storage inverters, and home appliances.

University of Tennessee

A Smart and Flexible Microgrid with a Low-Cost Scalable Open-Source Controller

The University of Tennessee at Knoxville, along with their partners, will develop a new type of microgrid design, along with its corresponding controller. Like most other microgrids, it will have solar PV-based distributed generation and be capable of grid-connected or disconnected (islanded) operations. Unlike other microgrids, this design will incorporate smart grid capabilities including intelligent switches and high-speed communication links. The included controller will accommodate and utilize these smart grid features for enhanced performance and reduced costs. The microgrid controller will be open source, offering a flexible and robust development and implementation environment. The microgrid and controller design will also be scalable for different geographic areas, load sizes, distributed generation source number and types, and even multiple microgrids within an area.

University of Vermont

Packetized Energy Management: Coordinating Transmission and Distribution

The University of Vermont (UVM) will develop and test a new approach for demand-side management called packetized energy management (PEM) that builds on approaches used to manage data packets in communication networks without centralized control and with a high level of privacy. The PEM system will allow millions of small end-use devices to cooperatively balance energy supply and demand in real time without jeopardizing the reliability of the grid or the quality of service to consumers. The project will develop the PEM method to optimally manage the rapid fluctuations that come with large amounts of renewable power generation, while simultaneously managing reliability constraints in the bulk transmission and local distribution infrastructure. To ensure UVM's PEM methods are effective, the integrated system will undergo extensive simulation testing with large-scale hardware implementation for the bulk power grid and an industry-scale micro-grid environments.

University of Washington

Energy Positioning: Control and Economics

The University of Washington and the University of Michigan are developing an integrated system to match well-positioned energy storage facilities with precise control technologies so the electric grid can more easily include energy from renewable power sources like wind and solar. Because renewable energy sources provide intermittent power, it is difficult for the grid to efficiently allocate those resources without developing solutions to store their energy for later use. The two universities are working with utilities, regulators, and the private sector to position renewable energy storage facilities in locations that optimize their ability to provide and transmit electricity where and when it is needed most. Expanding the network of transmission lines is prohibitively expensive, so combining well-placed storage facilities with robust control systems to efficiently route their power will save consumers money and enable the widespread use of safe, renewable sources of power.

University of Wisconsin

EPIGRIDS:Electric Power Infrastructure & Grid Representation in Interoperable Data Sets

The University of Wisconsin-Madison and its partners will develop realistic transmission system models and scenarios that will serve as test cases to reduce barriers to the development and adoption of new technologies in grid optimization and control. The EPIGRIDS project aims to construct realistic grid models by using software to emulate the transmission and generation expansion decision processes used by utility planners. This synthetic model development will utilize Geographic Information Systems (GIS) data on population density, industrial and commercial energy consumption patterns, and land use, over sizes ranging from the city-level to continental-scale. In order to test the robustness of the system's solutions, it will allow users to tailor specific data sets and scenarios to challenge particular aspects of optimization and control algorithm development. Flexible methodologies for data set construction and connecting features of these data sets to geographically described energy use and land use constraints will enable collaborative development of new models, far beyond those directly delivered by this project.

Vanderbilt University

Resilient Information Architecture Platform for the Smart Grid

Vanderbilt University will develop a foundation platform for developing and deploying robust, reliable, effective and secure software applications for the Smart Grid. The Resilient Information Architecture Platform for the Smart Grid (RIAPS) provides core services for building effective and powerful smart grid applications. It offers unique services for real-time data dissemination, fault tolerance, and coordination across apps distributed over the network. The platform will allow plug-and-play architecture by providing a software layer that isolates the hardware details making software applications portable across multiple devices and enabling interoperability among heterogeneous devices and applications. Additionally, the RIAPS will be supported by a model-driven development toolchain to reduce development costs. The platform will allow apps to be upgraded and dynamically reconfigured in the field and will enable a marketplace of hardware device vendors, app developers, and end users to sell and buy products and services that will interoperate. Vanderbilt's team will develop and prototype the platform using an open source code base. The team will also construct representative open source energy management software apps that will demonstrate the effectiveness and dependability of the system, while offering a starting point for commercial implementations. The team expects the platform to become an industry standard on which Smart Grid applications can reliably run, much in the same way Android and iOS have become industry standard platforms for smartphones.


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