My research focuses on the design and control of energy systems. Applications include power systems (marine, naval, terrestrial, and microgrid), transportation, power converters, and renewables.
See below for some specific projects, with more to come.
Minimizing Inverter Self-synchronization due to Reactive Power Injection on Weak Grids
Reactive power injection on high-impedance grids can cause oscillatory behavior as a result of “self-synchronization” of an inverter's phase detection unit (PDU). This phenomenon is particularly of concern in renewable energy applications and it occurs when the converter's injected current changes the voltage angle at the point-of-common coupling (PCC) and synchronizes to itself through its PDU. One of the most prevalent PDUs in industry is based on the synchronous-reference frame (SRF) phase-locked loop (PLL).
In this work a method to provide very fast synchronization and reduce instability due to interaction between the current controller and SRF-PLL during self-synchronization is demonstrated. The method uses a phase estimate of the stiff grid phase along with a phase adjustment. The proposed modification is referred to as the grid-sync (GS) PLL. It is shown that estimating the grid contribution to the phase angle decouples the current and PLL controllers to improve stability. A phase adjustment aids in providing rapid phase tracking.
Reconfigurable Adaptive Network Power System (RANPS) Test-Bed for Microgrid Research
The field of naval and commercial electric power “microgrids” has advanced rapidly driven by distributed generation, power electronic converters, energy storage, computation, communication, and control. Effectively integrating and controlling a wide variety of disparate sources and loads without the presence of large rotating machines is difficult. Microgrids often use communications to control multiple sources and loads and achieve maximum performance. However, this communication may be unreliable, unknown in advance, or subject to attack. Many methods have been proposed to solve these issues, but few are tested in hardware.
A Reconfigurable Adaptive Network Power System (RANPS) test-bed is being developed to allow rapid and simple testing of the control, stability, dynamic performance, and communications of advanced microgrid power systems. The system will operate at low power (~200W elements), but have many nodes (~30) interconnected through complex electrical and communications networks. The electrical network can be arbitrarily configured into any number of AC and DC buses at different voltage levels, with line impedances, switches, and circuit breakers, and sensing. The system elements can communicate with each other over a configurable communications network of arbitrary topology and quality using Ethernet, CAN, or other protocols. Thus the system can be easily reconfigured to represent destroyers, carriers, aircraft, commercial microgrids, and small and large bases, each with their own mix of DC/AC, voltage levels, and communications.
This test-bed will be unique among other systems in existence. The system will directly further the education of future officers at the Naval Academy, and a much broader audience of students and scientists through collaboration with the Naval Postgraduate School, other ONR-funded universities conducting power research, local universities, industry, and government entities including NAVSEA Philadelphia, and Navy/Army Research Labs. As both an academic and military installation, the Academy is an ideal location for such a test bed.
Microgrid design and control for shipboard integrated power systems with dynamically interdependent engineering plant subsystems
Next generation shipboard integrated power systems must provide affordable and robust power system solutions in support of a transformation to an electric naval force. These micro-grid systems of systems are composed of dynamically interdependent engineering plant subsystems including power generation, power distribution, heating and cooling managed by multi-level control and communication networks. This research is performed in collaboration with fellow Electric Ship Research and Development Consortium (see: www.ESRDC.com) universities.
Nonlinear Control Method for Synchronization of Converter-Interfaced Generators (Trident Scholar Project)
Microgrids are small power systems that utilize several frequency-synchronized, low inertia, local energy resources. Microgrids that contain no high-inertia rotating machinery cannot absorb common disturbances to the balance between source generation and load consumption. Such systems are typically fitted with complex communication systems to ensure synchronization and avoid disastrous transients due to such imbalances, but new research suggests that the behavior of coupled nonlinear oscillators can be leveraged to achieve synchronization with no communication required. This project aims to assess, through simulation and testing, the feasibility and effectiveness of that control scheme.
The success of this project would promote the use of a microgrid control scheme that addresses the problem of generator synchronization without the use of a complex communication network. The benefits of such a control scheme would be to significantly decrease the complexity of microgrid power systems, make the implementation of low inertia power systems practical, and reduce the vulnerability of microgrids to cyber and electromagnetic attacks. The data collected over the course of the project would not only provide validation for this control scheme, but also serve as a practical demonstration.
Dynamic Power Management Controller (PMC) for Ships
This project was sponsored by ONR with the goal of developing control strategies for the Electric Ship Next Generation Integrated Power System. The Power Management Controller (PMC):
- Ensures compatibility of pulse loads throughout the ship
- Monitors and controls power generating capacities
- Controls the loading placed on prime power sources
- Maintains overall power system stability
- Enables reduction of system mass/volume through reduction of energy storage requirements
The project team included the GE Power Conversion, GE Global Research Center, Raytheon, the University of Michigan, and Purdue University, with 10 faculty or industry members and 7 students.
Hybrid Vehicle Energy Management
Hybrid vehicles have become increasingly popular in the automotive marketplace in the past decade. Their fuel economy and drivability performance are very sensitive to the "Energy Management" controller that regulates power flow among the various energy sources and sinks. This project focuses on control design methods that are systematic, optimal, and highly automated. Most controllers in production hybrid electric vehicles are designed largely by hand with no explicit optimality guarantees. These new design methods allow much faster design cycles, simplify tradeoffs among conflicting goals and constraints, and provide an implementable real-time controller that meets or beats existing performance. This research was conducted in partnership with Ford Motor Company and uses their vehicle controller as a benchmark.
There are six main components of this work:
- Optimal, systematic control design methods that address not only fuel economy, but other major design constraints using Stochastic Dynamic Programming
- Evaluating if the performance of these methods justifies their complexity.
- Evaluating performance compared to existing industrial controllers on hundreds of real-world drive cycles to demonstrate robustness to different drivers.
- Quantifying the potential value of exact future knowledge using Deterministic Dynamic Programming, again on hundreds of cycles. Many authors propose using on-board GPS to obtain future information.
- Studying the industrial controllers to determine if their architecture imposes any fundamental limitations that could be avoided with these new techniques.
- Hardware testing to validate the performance of these methods.
While hybrid vehicles are studied here, the methods developed in this work are general and can be applied to other energy systems, including fuel cell vehicles, plug-in hybrids, wind turbines, etc.
Hardware testing of a route-based energy management algorithm on a fuel cell bus using historical and live traffic data.
In the context of alternative powertrains like hybrid, plug-in, electric, and fuel cell vehicles, the “energy management” method refers to the selection of how best to use multiple energy or power components. Many methods are proposed, but few involve actual vehicle testing. This project will implement and test an energy management algorithm on a fuel-cell bus at the University of Delaware. The future vehicle speed will be predicted based on historical and live traffic data along the expected route, and an optimal power flow will be computed on the fly. No other work has used live and future traffic data for energy management in a real vehicle.
Wind Farm Control
This problem is similar to the HEV control problem: time-varying inputs and disturbances, multiple nonlinear actuators, hard and soft constraints, etc. The sheer number of components in the system requires careful assumptions and model reduction to get a feasible, accurate solution.
I have also worked in electromechanical system design, embedded systems, control of thermal and fluid systems, and vibration isolation. My activities in these areas are limited now, but I may return to them in the future.