Agile Interconnected Energy Systems

• Co-Investigator: Rush Robinett III
• College/School: College of Engineering
• Department(s): Mechanical and Aerospace Engineering
• Awarded Amount: $776,231
• Sponsor: U.S. Department of Defense, Office of Naval Research

Project Summary:

Near-shore wave energy converter arrays may be designed to provide uninterrupted power to a number of coastal sensing applications, including sensors monitoring meteorological conditions, sea-water chemical/physical properties, tsunamis and storm surges, fish and other marine life, coastal and sea-floor conditions, etc. Active control seeking near-optimum hydrodynamic operation has been shown to enable a dramatic reduction in device size for required amounts of power. Certain features of the control strategies developed make them particularly amenable to incorporation of additional sensing capability based on the wave patterns generated by intruding submerged objects (at distances on the order of 1000 m), in particular, the phase changes to the approaching wave field that occur in the presence of an object.

This project investigates schemes for actively controlled wave energy converter arrays in coastal waters which enable detection of intruding marine vessels by monitoring the spatial and temporal energy conversion rates over the arrays. The proposed approach mainly utilizes a linear-theory based understanding of wave propagation, body hydrodynamics, and controller design, but also incorporates nonlinear extensions based on Volterra series modeling. Of particular interest, is using small device sizes, for which response nonlinearities can be significant. Therefore, it is proposed to exploit the nonlinearities to enhance energy generation. Furthermore, also investigate ways to utilize features of the nonlinear response that enable preferential coupling to certain phase signatures, so that energy conversion by certain array elements would imply the presence of an object. Analysis and simulation results on arrays of moored devices will be extended to free-floating arrays.

The first objective of the overall effort is to evaluate the proposed techniques through analysis and simulation. For near-shore sea areas to be identified, two categories or types of array designs with their own particular control strategies will be investigated, using Hydrodynamics and Controls based analytical techniques and detailed simulations (linear and nonlinear). Necessary in this process is the characterization of the phase-change signatures of various submerged objects when stationary and when in translation. This knowledge will provide the test parameters for the designs to be investigated. The first two years of the overall, 4-year long, effort are expected to provide the groundwork for the development of a prototype system. Prior to 'at-sea' prototype testing, first test the prototype in a wave-basin environment. To provide reliable designs for the testing in the wave basin, wave tank testing under simplified conditions is also proposed. The overall testing sequence from wave tank tests through wave-basin tests to 'at sea' tests is expected to occur over years 3 and 4.

• College/School: College of Engineering
• Department(s): Mechanical and Aerospace Engineering
• Awarded Amount: $592,243
• Sponsor: National Science Foundation

Overview:

Batteries are increasingly relied upon to provide multiple services during applications (e.g. traction in an electric vehicle, vehicle-to-grid, ancillary services) and to act as the ultimate resiliency element (e.g. electric vehicles used as power units during Hurricane Sandy). However, the ability to perform these diverse services is compromised by battery aging phenomena that eventually lead to failure. Understanding of how service conditions and context affect battery aging is limited due to a) battery high context dependency on generation and load dynamics, and environmental conditions; b) the multi-scale cell and module nature of battery systems; and c) the fact that a battery itself varies with age, as batteries are repurposed after a first life (e.g. electric vehicle) into a second life (e.g. grid or residential).

This CAREER project aims to understand battery aging dynamics as context-dependent, and to provide a unified theory that links application-level events and conditions with cell- and module-level aging events. The Pl hypothesizes that a battery electrochemical nature and aging, multi-scale system, observability challenges, and its context-dependency can all be modeled using ecological tools, with ecology defined as a branch of biology that explores organism relationships to one another and to their environment. Therefore, methods proven useful to study ecological relationships are well suited to study battery life, and can provide new knowledge, testing and estimation techniques. This project draws from two pertinent areas in ecology: 1) multi-scale field testing and 2) modeling of interrelationships among ecosystem elements to understand coupled effects and improve remaining life predictions. Hence, the research objectives are: 1 ) Identify a battery context and its observability through sensors and data in real deployment conditions for two lives (electric vehicle and grid); 2) Optimize a methodology to translate real-life conditions into the laboratory; 3) Design a large multi-scale testing platform in the laboratory for new and aged cells and modules that mimics real-life conditions; 4) Explore multi-scale battery dynamics and aging by developing reasoning networks that capture the whole battery context variations throughout its scales, reaching the application level; develop theories that link these networks across lives; design battery management systems that can learn to construct and apply these networks to improve their decision making and prediction.

Intellectual Merit:

This novel project will provide knowledge and perspectives to two fields by capitalizing upon the similarities between battery context-dependencies, battery life, and ecological systems. This new outlook will provide a unified theory for testing, estimation and management of batteries across cell, module, pack, and application scales and life scales in a research field that up to this point has been disconnected between scales. Testing approaches, interrelationship models, and estimation methods used in ecology are predicted to improve upon present, state-of-the-art battery research methods to provide economic, resiliency and environmental benefits by better understanding and leveraging the unique, time-dependent relationships each battery has with its context.

Broader Impacts:

This work will benefit all battery portable, transportation, and grid applications as well as multiple sectors. It will include the emerging battery repurposing sector, by providing tangible methods to improve testing, estimation and management techniques. The result will be longer battery life, better performance, and less environmental waste. Educational impacts include active learning opportunities for undergraduate and graduate students via research and educational interactions with individualized testing boards linked to the newly created large multi-scale testing platform. This strategy will enable low cost, highly distributed testing environments. The Pl will disseminate tools via national education conferences to improve the nearly nonexistent battery testing training of students. This project will facilitate new paths in multi-disciplinary graduate courses. The Pl has a passion to increase representation of Hispanic females in STEM. Outreach will include hosting 4 diverse Community College students for summer research through the Michigan College and University Partnership, and participating in Society for Hispanic Professional Engineers conferences, specifically in the female Hispanic track.

• College/School: College of Engineering
• Department(s): Mechanical and Aerospace Engineering
• Awarded Amount: $193,729
• Sponsor: National Science Foundation

Work Plan:

Task 1: Wave-by-wave control and Multi-resonant control

(a-i) Wave-by-Wave Control: Generalize to conversion from relative oscillation in surge, heave, and pitch modes. This step places high expectations on geometry design, because the chosen geometry needs to maximize wave radiation (radiation damping) by relative oscillation in all three modes. Typically, for small axi-symmetric buoys, radiation damping in surge and pitch modes is considerably smaller than that in heave mode. Therefore, greater oscillation excursions are typically required for optimal conversion in these modes. In addition, the power requirements of the wave measurement hardware also need to be included in the daily/annual power calculations. For the X-band Radar hardware applicable to the up-wave distances of interest to us (on the order of 1000 m), the power consumption is expected to be less than 300 W (average). This could pose a challenge in some wave conditions, but it is likely that the use of multiple modes and optimized geometries will help to provide sufficient usable power for the iFCB application we are pursuing in this work. We plan to extend the current simulations to address these needs.

(a-ii) Geometry Design: New geometry design/utilization approaches to maximize the radiation damping for the 3 relative oscillation modes are being considered. These will be evaluated through detailed simulations in the forthcoming period.

(b) Multi-resonant Control: Current implementations need to be extended to incorporate realistic oscillation constraints. Further extensions to 2-body systems with power capture from relative oscillation are also required, and are planned for the forthcoming period. Finally, the procedure also needs to be extended to investigate multiple-mode conversion (i.e. relative heave, pitch, and surge oscillations).

Task 2: Actuator Design and Energy Storage

Work is planned for the forthcoming period where propose to examine favorably interacting buoy-instrument cage geometries that will minimize the need for large amounts of reactive power to flow through the system. Particular attention will be given to hydrodynamic and mechanical coupling effects and ways to provide negative stiffness through geometry design.

In addition, non-polluting high-lubricity hydraulic fluids will be evaluated through actuator dynamic models over the frequency range of interest.

Task 3: Simulation of Complete System and Wave Tank Testing

This is an important part of the project. The complete system will be simulated following inclusion of multiple-mode relative oscillation conversion and more detailed actuator design. Besides the power requirements of the wave measurement system, all other non-function-critical power needs embedded within the overall system (on-board electronics, etc.) will be included in this simulation.

Wave tank tests are planned as part of this project. Preparations are currently underway to install a wave tank (with flap type absorbing wave makers) capable of providing accurate and repeatable sea states for this project. 1/2 or 1/5 scale models are planned.

• Co-Investigator: Gordon Parker
• College/School: College of Engineering
• Department(s): Electrical & Computer Engineering
• Awarded Amount: $220,244
• Sponsor: University of Dayton Research Institute

Scope:

High Voltage Direct Current (HVDC) aviation electrical power systems (EPS) provide many advantages, particularly in the area of weight savings. Despite the advantages, there are technical challenges for these systems as the power and dynamic response demanded by high power and more-electric loads increases. High power HVDC systems require low source impedance which makes larger fault energy available to the system. In addition, flight and mission critical loads demand constant power and fast response by a tightly regulated EPS. These loads on a HVDC distribution can cause dynamically negative resistance resulting in poor power quality and/or loss of system stability.

Objectives:

AFRL' s objective is to develop an intelligent power system to advance the state of the art in system efficiency and safety. This is a far-reaching and broad area of research that is best served by the participation of multiple research institutions that have developed expertise in specific areas. To that end, this Statement of Objectives outlines work where Michigan Technological University (MTU) has demonstrated outstanding research.

Specific areas of research that AFRL is interested in having MTU participate in this program are outlined below. The results of this research and development effort shall be available to all other parties collaborating on the AFRL Intelligent Power System Program as well as industry concerns involved with United States aviation power systems so that best practices and recommendations can be incorporated in future power system design concepts.

Reesearch Tasks:

1.1 Analysis, Design, and Control of components (ns - ms level)

1.2 Distributed management/optimization of source and loads (ms - s level):

1.3 Mission level load planning (> 1 s level)

1.4 Energy Storage (ES) for pulsed power loads

• College/School: College of Engineering
• Department(s): Mechanical and Aerospace Engineering
• Awarded Amount: $339,996
• Sponsor: U.S. Department of Defense; Naval Facilities Engineering Command

The current approach for designing wave energy converters is to use a floating-body tuned to the wave climate, which results in a very large device that is expensive to build, service and deploy. Additionally, because the device is designed to be tuned to a specific climate, it will not work effectively in a different location ·with a different climate. Therefore, the current approach for designing wave energy converters is not conducive to long-term economic application.

Economically significant size reduction and year-round power increases are only possible through operation near theoretical efficiency limits in constantly changing wave conditions, which requires active hydrodynamic control. However, the wave-by-wave control necessary for best conversion is not possible without wave-elevation information up to some duration into the future (this in large part is because of the force due to the waves generated by body oscillation in response to the incident wave field). By incorporating wave-elevation prediction based on a deterministic propagation model that accounts for a realistic range of wave-group velocities in conjunction with wave measurements in the up-wave directions, we have been able to confirm, through simulations, a 10-fold increase in power conversion under a swept-volume oscillation constraint for an omni-directional heaving buoy type device.

Availability of instantaneous wave profile ("wave surface elevation" or "wave elevation") measurements and wave surface elevation predictions is important to the success of the control approach being pursued in this work. Equally important is the near-optimal wave-by-wave control approach itself.

Proposed Research:

1. A method for obtaining instantaneous wave surface elevation information on a wave-by wave basis using a low-cost X-band Radar (the state of the art, as represented by the commercially available WaMOS system is optimized to provide spectral information.
2. A method for providing constrained near-optimal wave-by-wave control for maximizing the energy conversion by small wave energy converters.
3. Although the focus of the proposed research is wave energy converter technology, the results of this work are expected to find application in other forthcoming Navy developments. Wave-by-wave surface elevation prediction and near-optimal power absorption techniques demonstrated in this effort can be extended to facilitate critical mid-sea shipboard operations such as helicopter/ aircraft landing, cargo handling, etc. The techniques demonstrated as part of this research will also provide technology to enhance and optimize seakeeping characteristics of Navy ocean platforms.

• Co-Investigator: Seong-Young Lee
• Co-Investigator: Jaclyn Johnson
• College/School: College of Engineering
• Department(s): Mechanical and Aerospace Engineering
• Awarded Amount: $159,888
• Sponsor: Fian Chrysler Automobiles, LLC

Project Description and Research Objectives:

Michigan Technological University (MTU) will investigate and characterize one FCA US supplied fuel injector to provide data for injector evaluation and model validation. The Injector driver will be supplied by FCA US. Tests will be conducted under a set of ambient and injection conditions as defined by FCA US. Results will include vapor and liquid penetration length from Schlieren and Mie Scatter imaging and quantitative fuel vapor distribution via PLIF (Planar Laser-Induced Fluorescence). Tests will be conducted in MTU's optically accessible combustion vessel (CV) research facility. Existing hardware in the facility will be used; including a gasoline fuel system to reach the target injection pressure of 300 bar, high speed imaging for liquid and vapor, and simultaneous single shot PLIF diagnostics for fuel vapor distribution. A new diffraction based instrument is planned for measuring spray droplet sizing.

• Co-Investigator: Rush Robinett III
• College/School: College of Engineering
• Department(s): Mechanical and Aerospace Engineering
• Awarded Amount: $499,059
• Sponsor: U.S. Dept of Defense: Office of Naval Research

The main objective of this effort is to develop an exergy control strategy, applied to a ship medium voltage de (MVDC) grid that exploits exergy flow coupling between multiple subsystems. This work involves: 1) exergy control strategy development and 2) mapping exergy control system performance to ship-relevant metrics. A ship power grid Challenge Problem model will be developed to illustrate and resolve the fundamental gaps of exergy control. The model will also compare and contrast feedforward and feedback exergy control with conventional strategies.

Introduction:

Ship subsystems and mission modules perform energy conversion during their operation resulting in a combination of electricity consumption, heat generation and mechanical work. Mission module thermal management requirements further impact the ship's electrical grid, for example, via chiller operation. Subsystems often have opportunities for performing an energy storage role during their operation cycle. A ship crane is one example where potential energy is stored in the raised load and can be converted into electrical energy during lowering. Whether subsystem requirements are dominated by electrical, thermal or mechanical functions, they are coupled through energy and information flows, often by the ship's electrical power grid. Treating each subsystem as a disconnected entity reduces the potential for exploiting their inherent interconnection and likely results in over designed shipboard systems with higher than necessary weight and volume. Realizing the opportunity of coupled subsystem operation requires modeling and control schemes that are unavailable today, but that we believe should require few infrastructure changes. We propose that the design and control of coupled ship subsystems should be based on exergy- the amount of energy available for useful work. A recent study, applied to a room heating system, showed that exergy control increased the overall efficiency by 18%. Since the system was powered electrically, this translated directly to a decrease in the electrical load. The main objective of this effort is to develop an exergy control strategy, applied to a ship medium voltage de (MVDC) grid that exploits exergy flow coupling between multiple subsystems.

An exergy approach to control permits consideration of both mission modules and the platform infrastructure as mixed physics power systems that may act as loads, storage or sources depending on the situation. Instead of separately designed and managed subsystems that satisfy electrical and thermal requirements via static design margins a, multi-physics, unified system-of-systems approach is needed to enable affordable mid-life upgrades as requirements and mission systems evolve over the platform's lifespan. Being able to translate the benefits of exergy control into savings in mass, volume, energy storage requirements and fuel usage is necessary for making rational design decisions for new ship platforms and for increasing the efficiency of legacy ship systems. Currently, there does not exist an analysis technique to map control system performance into ship-relevant performance metrics. This restricts ship designers from understanding the tradeoffs of adopting advanced control schemes that may exploit subsystem coupling. One of the objectives of this work is to develop a method for extrapolating control system performance into ship-relevant metrics that impact mass, volume, energy storage, and fuel usage.

As described above, there are two main thrusts to this work: (1) exergy control strategy development and (2) mapping exergy control system perfo1mance to ship-relevant metrics. We will develop a ship power grid Challenge Problem model that will illustrate the fundamental gaps of exergy control that will be addressed. The model will also be used to compare and contrast feedforward and feedback exergy control with conventional strategies. Techniques for mapping the results of the exergy control to weight, volume, and energy storage requirements will be developed and applied to the Challenge Problem throughout the project.

• Co-Investigator: Rush Robinett III
• College/School: College of Engineering
• Department(s): Mechanical and Aerospace Engineering
• Awarded Amount: $132,541
• Sponsor: National Science Foundation

• Co-Investigator: Rush Robinett III
• College/School: College of Engineering
• Department(s): Electrical & Computer Engineering
• Awarded Amount: $869,980
• Sponsor: U.S. Department of Defense, Office of Naval Research

Project Description and Research Objectives:

From large scale electric power grids and microgrids down to small scale electronics, power networks are typically deployed using a fixed infrastructure architecture that cannot expand or contract without significant human intervention. Mobile, monolithic power systems exist but are also not readily scalable to exploit surrounding power sources and storage devices. However, if a power network is constructed from physically independent and autonomous building blocks, then it would be infinitely reconfigurable and adaptable to changing needs and environments. The aim of this project is to integrate vehicle robotics with intelligent power electronics to create self-organizing, ad-hoc, hybrid AC/DC microgrids. The main benefits of this system would be the establishment and operation of an electrical power networks independent of human interaction and can adapt to changing environments, resource and mission. In the context of U.S. Naval platforms, this autonomous electrical network could be used in land, air or sea systems.

The focus of this work will be on land based autonomous microgrid systems, but the fundamental theory developed may be applicable to air and sea based systems as well. Investigators at Michigan Technological University have developed initial hardware and testbeds to study this problem. However, a more detailed theoretical foundation is needed to be developed to apply autonomous microgrids to a wide variety of operational scenarios with various resources. It is also hypothesized that given the flexibility of this approach that it could be equally applied over a vast scale of energy assets. A microgrid that grows in situ from 10 s to 100 s to 1000 s of energy assets can be equally managed, controlled and optimized through the highly scalable approach proposed in this project.

These applications are examples of the critical need for autonomous mobile microgrid capable of operating in highly dynamic and potentially hazardous environments. Our overall goal is to create a scalable architecture to develop a system that accounts for uncertainty in predictions and disturbances, is redundant, requires minimal communication between agents, provides real-time guarantees on the performance of path planning, and reaches the targets while making electrical connections. Such architecture provide a coherent layout for the interconnection between different disciplines on this topic and minimizes the integration concerns for future developments.

Description of the Proposed Work:

• Microgrid Planning and Control
• Microgrid Topology and Optimization
• Electrical Components and Power Flow
• Game-Theoretic Control
• Physical Autonomous Positioning and Connections

• College/School: College of Engineering
• Department(s): Mechanical and Aerospace Engineering
• Awarded Amount: $652,931
• Sponsor: U.S. Department of Defense Office of Naval Research

The current challenge impeding advances in the U.S. Navy’s mobility is significant interruptions during undersea missions. Missions such as studying arctic physical environments; understanding the effects of sound on marine mammals; submarine detection and classification; and mine detection and neutralization in both the ocean and littoral environment require persistent operation of unmanned systems in challenging and dynamic environments. The proposed work will create an architecture that integrates three elements of energy, communication, and docking to guarantee undersea persistence where limited power resources and unknown environmental dynamics pose major constraints. The architecture will take into account: the number of operational AUVs required for different operation periods, recharging specifications, communication and localization means, and environmental variables.

The overall goal of this project is: to develop a mobile power delivery system that lowers deployment and operating costs while simultaneously increasing network efficiency and response in dynamic and often dangerous physical conditions. The aim is to create network optimization and formation strategies that will enable a mobile power deliver system to meet overall mission specifications by: 1) reconfiguring itself depending on the number of operational AUVs and; 2) responding to energy consumption needs of the network, situational condition, and environmental variables. The outcome of this work will be a theoretical, computational, and experimental roadmap for building and implementing an autonomous distributed system with mobile power delivery and onsite recharging capability. This roadmap will address fundamental hardware and network science challenges. The long-term outcome of this work will be a persistent and stealthy large area presence of AUV fleets able to perform undersea Navy missions by accurately and autonomously responding to energy needs, situational dynamics and environmental variables.

• College/School: College of Engineering
• Department(s): Mechanical and Aerospace Engineering
• Awarded Amount: $681,124
• Sponsor: National Science Foundation

Overview:

Success of numerous long-term robotic network missions in space, air, ground, and water is measured by the ability of the robots to operate for extended time in highly dynamic and potentially hazardous operating environments. The proposed work responds to the urgency for development of innovative mobile power distribution systems that lower deployment and operating costs, while simultaneously increasing mission efficiency, and supporting the network's need to be responsive to changing physical conditions. The overall CAREER goal is to develop a power distribution system that responds to individual robot needs, as well as, overall robotic network goals to guarantee persistence of long-term operation in uncertain and unstructured environments.

The proposed work is informed by the hypothesis that network persistence hinges on the ability to establish stable energy transfer cycles necessary to accomplish coverage specifications, while simultaneously dealing with physical and environmental constraints. To test this hypothesis and as an example of such a system, this work will focus on creating a reliable autonomous recharging system for autonomous underwater vehicles (AUVs) that enables continuous real-time marine observation and data collection in the presence of continuously changing underwater environmental circumstances. The key challenges are two-fold: there are fundamental hardware challenges connected to energy transfer in the harsh underwater environment, but more importantly there are basic network science needs that are novel to a mobile power network. The specific research thrusts for this CAREER work include: 1) Task and Energy Routing Scheduling for Persistent Mission Planning. 2) Efficient Network Path Planning and Coordination to Accomplish Persistent Mission Plan. 3) Experimental Validation through Test-bed Development. 4) Design-based, Research-integrated Education Plan for Broadening Underrepresented Participation in STEM.

Intellectual Merit:

This project builds a roadmap to achieve robust continuous marine autonomy that advances unmanned marine systems ability to perform autonomous long-term missions. More specifically the proposed work will provide: 1) resource based task scheduling, 2) path planning formation for mission and charging, and 3) integration tools for testing. Expected outcomes will overcome the current challenge of significant interruptions during underwater missions due to battery limitations and recharging needs. Through this CAREER proposal, the Pl will establish the theoretical, computational, and experimental foundation for mobile power delivery and onsite recharging capability for autonomous underwater vehicles (AUVs). The developed power distribution system will be able to reconfigure itself depending on the scope of the mission, as well as, the energy consumption needs of the network, the number of operational AUVs and required operation time, recharging specifications, communication and localization means, and environmental variables.

Such a system will play a vital role in real-time controlled applications across multiple disciplines, such as: sensor networks, robotics, and transportation systems where limited power resources and unknown environmental dynamics pose major constraints. All developed tools will be suited for the capabilities of not only low-cost AUVs with limited sensing and computational resources, but also high-tech AUVs with state of the art sensor packages.

Broader Impacts:

The developed active power distribution system focuses on underwater scenarios, but will be transferrable to space, air, and ground missions as well. This type of feasible power distribution solution can be used to optimize: 1) immediate high-risk disaster recovery missions like the Fukushima nuclear plant accident; 2) search missions that require vast underwater inspection and detection like the Malaysia MH370 passenger aircraft; and 3) long-term space observation and monitoring like that of the lunar skylight or Europa space mission. The findings from this project will be disseminated through publications, software sharing, and technology commercialization. The project provides interdisciplinary training opportunities for graduate, undergraduate, and pre-college students, including those from underrepresented groups. Research activities will be integrated with education through curriculum development, outreach and improved GUPPIE design.

• Co-Investigator: Steven Goldsmith
• Co-Investigator: Wayne Weaver
• College/School: College of Engineering
• Department(s): Mechanical and Aerospace Engineering
• Awarded Amount: $148,433
• Sponsor: Mississippi State University

Overview:

The existing communication layer for Vehicle to Grid (V2G) operations has sufficient throughput and capabilities for basic connectivity, but may not have enough for tasks such as operating military vehicle systems remotely. They cyber security approach to V2G operations has had some development in industry; however military vehicles demand more scrutiny from a cyber security perspective.

Vehicle-to-Vehicle (V2V) resource sharing would enable a greatly expanded flexibility for utilization of assets for forward operating bases (FOB). Consider a FOB with a variety of vehicle assets, each with different levels of functionality. The ability to daisy-chain the vehicle assets together (including partially disabled vehicles), have the vehicles automatically determine their net capability and then share resources to accomplish a common goal (force protection for example), would enable a level of capability not currently available.

Specific Tasks: Vehicle-to-Grid Simulation, Connection Protocol Assessment, Connection Protocol Development, Throughput Assessment, and Simulation Studies.

• Co-Investigator: Gordon Parker
• College/School: College of Engineering
• Department(s): Mechanical and Aerospace Engineering
• Awarded Amount: $250,000
• Sponsor: Argonne National Laboratory

Introduction:

Microgrids offer attractive options for enhancing energy surety and increasing renewable energy penetration. Within a single microgrid energy generation, storage and utilization is localized. Greater enhancements to energy surety can be accomplished by networking multiple microgrids into a collective which can lead to almost unlimited use of renewable sources, reduction of fossil fuels and self-healing and adaptive systems. However, one pitfall to avoid is losing the surety within the individual microgrids. This produces design and control challenges that are currently unsolved in networked microgrids. To help solve this dilemma, development of analysis methods for design and control of networked microgrids is the general focus of this activity.

Specific tasks include:

1. Collaborate and form a coalition with national labs and other microgrid stakeholders to identify key R&D topics in networked microgrids.
2. Look at near term solutions that can quickly and easily be integrated into existing microgrids,
3. Determine best practices and optimized control strategies for the ground-up design of future networked microgrids.
4. Work within the DOE and national lab partnerships to produce the FOA whitepaper on single microgrid systems.

Tasks 1 through 3 will include microgrid modeling, control and optimizations of single and networked microgrids with focus on achieving DOE 2020 microgrid targets. Specifically, targets include developing commercial scale microgrid systems that reduce outage time, improve reliability and reduce emissions.

• Task 1: Collaborate and form a coalition with national labs and other microgrid stakeholders to identify key R&D topics in networked microgrids.
• Task 2: Look at near term solutions that can quickly and easily be integrated into existing microgrids Model development is one of the first steps in the microgrid control design process and incurs trade-offs between fidelity and computational expense. Models used for model-based control implementation must be real-time while having sufficient accuracy so that feed-forward information can be maximized to achieve specified requirements. The expected outcomes of this study are (1) determination of appropriate time scales for networked microgrid modeling (2) a MATLAB/ Simulink reduced order model library of networked microgrid components and (3) lab scale hardware validation of networked microgrid models. These model libraries will then be used to construct models and develop control and optimization algorithms of current microgrid systems and equipment.
• Task 3: Determine best practices and optimized control strategies for the ground-up design of future networked microgrids. Demonstrating robust networked microgrids will require system-level optimization. This includes both its physical and control system designs. This task will build upon the models and optimizations achieved in task 2 applied to the design of future networked microgrids. The expected outcomes of this study are (1) energy-optimal design methods suitable for networked microgrid design and control of future long-term application architectures and (2) integration of these strategies with the microgrid model environment and bench scale hardware described in task 2.

• Co-Investigator: Wayne Weaver
• College/School: College of Engineering
• Department(s): Mechanical and Aerospace Engineering
• Awarded Amount: $386,490
• Sponsor: Sandia National Laboratory

Abstract:

Future microgrids are envisioned having a large renewable energy penetration. While this feature is attractive it also produces design and control challenges that are currently unsolved. To help solve this dilemma, development of analysis methods for design and control of microgrids with high renewable penetration is the general focus of this activity. The specific foci are (1) reduced order microgrid modeling and (2) optimization strategies to facilitate improved design and control. This will be investigated over a multi-year process that will include simplified microgrid modeling and control, single microgrid modeling and control, collective microgrid modeling and control, and microgrid (single and collective) testing and validation.

Microgrid Reduced Order Modeling (ROM)

Model development is one of the first steps in the microgrid control design process and incurs trade-offs between fidelity and computational expense. Models used for model-based control implementation must be real-time while having sufficient accuracy so that feedforward information can be maximized to achieve specified requirements. The expected outcomes of this study are (1) quantification of model uncertainty as a function of the assumptions with particular interest given to reduced order models (2) determination of appropriate time scales for reduced order modeling and (3) a MATLAB / Simulink reduced order model library of microgrid components. Contrasting different microgrid reduced order modeling approaches and simulation results that demonstrate the reduced order microgrid simulation.

Microgrid Optimization

Demonstrating microgrids with robust and high renewable penetration requires system-level extremization. This includes both its physical and control system designs. The expected outcomes of this study are (1) energy-optimal design methods suitable for microgrid design and control and (2) integration of these strategies with the microgrid reduced order model environment described above. How energy-optimal design can be exploited for microgrid design and control.

• Co-Investigator: Laura Brown
• Co-Investigator: Wayne Weaver
• Co-Investigator: Steven Goldsmith
• College/School: College of Engineering
• Department(s): Computer Science
• Awarded Amount: $1,907,135
• Sponsor: US Department of Defense, Army Research Laboratory

Overview:

This project plan (APP) describes the second year of the four year program for distributed agent-based management of agile microgrids. In year 1, the team has evaluated modeling and forecasting techniques for renewable energy sources as well as developed relevant case studies. In year 2 the team will further develop the models and forecasting techniques as well as begin implementation of simulations and hardware test cases.

• Topic area 1: Core electrical power networks and control technology research with the focus on modeling of networks and control methods, conceptual hardware evaluation and analysis and identification of Army modes of operation.
• Topic Area 2: Modeling and optimization of tactical energy networks control systems with a focus on short term load forecasting and simulation.
• Topic area 3: Research focused on machine learning, long-term prediction and forecasting of loads. Research into optimization and distributed control of power distribution systems.

• Co-Investigator: Steven Goldsmith
• Co-Investigator: Wayne Weaver
• College/School: College of Engineering
• Department(s): Mechanical and Aerospace Engineering
• Awarded Amount: $117,500
• Sponsor: Sandia National Laboratory

Abstract:

Prior Work is leveraged; MTU has developed and demonstrated through simulation a prototype multiagent system that coordinates the life cycle operations of a microgrid collective composed of independent electric power sources, loads, and storage. MTU has performed simulations of DC micro grids of varying compositions and characteristics. MTU has analyzed simulation results, and developed candidate architectures and protocols for agent-based microgrid controls.

Objective:

Execution of this project will further technical innovations associated with multi-agent software controlling microgrid collectives. The microgrid control algorithms for microgrid collectives will be developed and refined using Michigan Tech microgrid models and simulations validated against the MTU test bench. The algorithms will then be applied to SNL hardware models in simulation and finally against the SNL hardware test bed.

Scope:

Agent-based control systems will be further developed by MTU in Matlab/Simulink blocks, tested, and refined through simulations. Once control performance objectives have been achieved, the systems will be ported to the MTU situated multi-agent system (MAS) and supporting servo loop controllers on the MTU test bench for evaluation. New Matlab simulations will be tailored and tuned to control the SNL test bed models and verified in simulation. SNL will re-apply the MTU MAS to the physical SNL test bed. SNL will collaborate with MTU on implementation and validation. Collaborative efforts will ensure that SNL attains the technology necessary to achieve the final project objectives for the SNL test bed

Required Research Innovations:

1. Identify control system performance issues between agent informatics and DC nonlinear controls. Since global computations require input from various points, processor speed and network bandwidth may dominate the performance of collaborative protocols that rely on nonlinear control approaches. Research must identify the computational and communication limits for porting nonlinear controls to agent control layers.
2. Investigate scaling properties for controls applied to increasing the number of interconnected DC microgrids. Trading power between microgrids may not be feasible due to geographical distances or communication time latencies. There may also be thresholds identified for collaboration considerations, such as partnering with 10 microgrids or less, due to the global computation requirements. Control scaling results should describe the appropriate considerations at various time scales (seconds, minutes, hours, and days). Additional considerations for scalability may include increasing the number of components within a single microgrid and increasing the variety of components within the microgrid.