HVDC Distribution Study of Intelligent Power System

University of Dayton Research Institute

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.

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.

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

Investigators: Wayne Weaver, Gordon Parker

Bo Chen


Dr. Chen is the Dave House Associate Professor of Mechanical Engineering and Electrical Engineering in the Department of Mechanical Engineering – Engineering Mechanics and Department of Electrical and Computer Engineering at Michigan Technological University. She received her Ph.D. degree from the University of California, Davis, in 2005. Dr. Chen conducts interdisciplinary researches in the areas of mechatronics and embedded systems, agent technology, modeling and control of hybrid electric vehicles, cyber-physical systems, and automation. Her research projects are funded by National Science Foundation, Department of Energy, and industrial partners. Dr. Chen has authored or co-authored over 70 peer-reviewed journal and conference papers. She received the Best Paper Award at 2008 IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications.

Dr. Chen is currently serving as the Chair of the Technical Committee on Mechatronics and Embedded Systems of IEEE Intelligent Transportation Systems Society and the Chair of the Technical Committee on Mechatronic and Embedded Systems and Applications of ASME Design Engineering Division. She is an Associate Editor of the IEEE Transactions on Intelligent Transportation Systems. Dr. Chen has served as Program Chair, Symposium Chair, and Session Chair for a number of international conferences. She was the General Chair of 2013 ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications.
Areas of Expertise
Mechatronics and embedded systems
Agent Technology
Monitoring and control networks
Hybrid electric vehicles
Smart grid

Research Interests
Modeling and control of hybrid electric vehicles
EV-smart grid integration
Distributed monitoring and control
Battery control for HEV and energy storage systems
IC engine management systems
Sensor information fusion

Making Small Wave Energy Converters Cost-Effective for Underwater Microgrids through a 10-Fold Improvement in Year-Round Productivity

South Dakota School of Mines and Technology


Proposed Work
Drivetrain and Actuator
1- Conceptual Design of actuators with large stroke and large rated force.
2- Conceptual Design of a high efficient drivetrain and energy storage for low frequency oscillatory systems (WECs)
3- Evaluate several technologies (electrical, mechanical, and hydraulic) for the design of the actuator and powertrain, with the requirement of limiting the overall cost.

Investigators: Ossama Abdelkhalik and Mark Vaughn

Toward Undersea Persistence

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.

Investigator: Nina Mahmoudian

“CRISP Type 2: Revolution through Evolution: A Controls Approach to Improve How Society Interacts with Electricity.”

National Science Foundation

This CRISP project addresses the challenges associated with the rapid evolution of the electricity grid to a highly distributed infrastructure. The keystone of this research is the transformation of power distribution feeders, from relatively passive channels for delivering electricity to customers, to distribution microgrids, entities that actively manage local production, storage and use of electricity, with participation from individual customers. Distribution microgrids combine the advantages of the traditional electricity grid with the advantages of emerging distributed technologies, including the ability to produce and use power locally in the event of grid outages. The project will result in a unified model that incorporates key aspects of power generation and delivery, information flow, market design and human behavior. The model predictions can be used by policymakers to guide a transition to clean energy via distribution microgrids. The expectation is to enable at least 50% of electric power to come from renewable resources. This cannot be done with either the traditional grid, due to its limited capacity to accommodate intermittent renewable power sources, or with fully decentralized approaches, which would not be affordable for most utility customers.

This project addresses many socio-technological gaps necessary to translate from research discovery to commercial applications. To date, there is no theoretical framework to ensure system stability as renewable energy routed through power electronics replaces traditional rotating machinery. To achieve an optimal mix of storage performance and information bandwidth and to design nonlinear controllers, we will use Hamiltonian Surface Shaping Power Flow Control theory. We will study methods to detect malicious tampering with information flows. The complex interaction of intermittent resources, human behavior and market structures will be modeled in an agent-based simulation. System inputs will be provided by utility and meteorological data, and by behavioral models that incorporate information obtained by surveys, interviews and metering data. Emergent system dynamics will be abstracted and studied using dynamical complex network theory, to explore stability limits as a function of human behavior and market design. Finally, the effect of enhanced controllability of distribution systems on the robustness of large energy-information-social networks will be analyzed using interdependent Markov-chain models. Graduate students involved in this program will be exposed to a unique combination of skills from engineering, data analysis and social sciences; such cross-disciplinary training will prepare them for leadership roles in the emerging energy economy of tomorrow.

Investigators: Laura Brown, Chee-Wooi Ten, Wayne Weaver

Revolution through Evolution: A Controls Approach to Improve How Society Interacts with Electricity

September 20, 2015

Laura Brown (PI) received a $699,796 NSF grant. The title of the project is “CRISP Type 2: Revolution through Evolution: A Controls Approach to Improve How Society Interacts with Electricity.” The co-principal investigators of this project are Chee-Wooi Ten (ECE) and Wayne Weaver (ECE). This is a three-year collaborative project with four other institutions with a total budget of $2,499,801. The project addresses the rapid evolution of the electricity grid, from one based on few centralized generators providing power to millions of users to one where many distributed energy resources. The keystone of this research is the transformation of power distribution feeders, from relatively passive channels that deliver electricity from the transmission grid to customers, to distribution microgrids, highly intelligent entities that actively manage production, storage and use of electricity.



Advanced Control of Wave Energy Converters

Sandia National Laboratory

A new multi-year effort has been launched by the Department of Energy to validate the extent to which control strategies can increase the power produced by resonant Wave Energy Converters (WEC) devices. A large number of theoretical studies have shown promising results in the additional energy that can be captured through control of the power conversion chains of resonant WEC devices.
However, most of the previous work has been completed on highly idealized systems and there is little to no validation work. This program will specifically target controls development for nonlinear, multi-degree of freedom WEC devices. Multiple control strategies will be developed and the efficacy of the strategies will be compared within the “metric matrix.”
Objective: The purpose of this contract is to provide the labor to develop and implement custom control strategies for a specified WEC device.

Scope of Work
Michigan Technological University (MTU) will provide optimization expertise (Dynamic Programing, pseudo-spectral, shape optimization, others) to support MTPA-FF (mid-targeting phase and amplitude-feedforward) designs and analysis specific to the performance model WEC. This will include numerical simulations specific to the metric matrix requirements. In addition, MTU will provide expertise and support for feedforward real-time implementation and investigations.

Investigator: Ossama Abdelkhalik

Advanced Control and Energy Storage Architectures for Microgrids

Sandia National Laboratory

Consult on advanced control and energy storage architectures for microgrids.
1) Multiple Spinning Machines on a Single AC Bus – Finish the development of the Hamiltonian Surface Shaping Power Flow Controller (HSSPFC), controller design for multiple spinning machines on a single AC Bus.
2) Unstable Pulse Power Controller – Perform simulation studies on the unstable pulse power controller relative to the optimal feedforward (stable) controller for a single DC bus in order to determine the effectiveness of the unstable controller design relative to performance and stability.

Help characterize path forward for nonlinear control design.
1) Review dynamic programming interior point method (DPIP) for feedforward/optimal reference trajectory,
2) HSSPFC (Hamiltonian Surface Shaping Power Flow Controller (nonlinear dynamic structure for feedback),
3) Preliminary assessment of nonlinear wave model and impact on power absorbed.

Investigators: Wayne Weaver, Ossama Abdelkhalik

SGAS Drive Train Model Calibration


Calibration is an important step in creating a physical model that can be used for predictive control system design. IMECO has a MATLAB/Simulink model of their Steering Gear Actuation System (SGAS). It contains parameters that can be classified as known (e.g. control system gains), known with uncertainty (e.g. mass properties) and unknown (e.g. damping coefficients). IMECO has also obtained experimental data that can be used to run the model and compare model outputs to sensor measurements. An optimization-based method for identifying the model parameters is needed to help automate the calibration process.

Statement of Work
Using the model and experimental data supplied by IMECO, calibrate the model using advanced numerical optimization strategies. Separate calibration parameters for several data sets will be developed in addition to a single calibration across multiple data sets. While the calibration is of primary importance, development of a methodology for automating the process will also be developed.

Investigators: Gordon Parker, Ed Trinklein

Agent Based Control with Application to Microgrids with High Penetration Renewables

Sandia National Laboratory

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.

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.

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.

Investigators: Gordon Parker, Wayne Weaver, Steven Goldsmith