Publications

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Optimal control theory is applied to compute control for a single-degree-of-freedom heave wave energy converter. The goal is to maximize the energy extraction per cycle. Both constrained and unconstrained optimal control problems are presented. Both periodic and non-periodic excitation forces are considered. In contrast to prior work, it is shown that for this non-autonomous system, the optimal control, in general, includes both singular arc and bang-bang modes. Conditions that determine the switching times to/from the singular arc are derived. Simulation results show that the proposed optimal control solution matches the solution obtained using the complex conjugate control. A generic linear dynamic model is used in the simulations. The main advantage of the proposed control is that it finds the optimal control without the need for wave prediction; it only requires the knowledge of the excitation force and its derivatives at the current time.

A linear dynamic model for a wave energy converter (WEC) has been developed based on the results of experimental wave tank testing. Based on this model, a model predictive control (MPC) strategy has been designed and implemented. To assess the performance of this control strategy, a deployment environment off the coast of Newport, OR has been selected and the controller has been used to simulate the WEC response in a set of irregular sea states. To better understand the influence of model accuracy on control performance, an uncertainty analysis has been performed by varying the parameters of the model used for the design of the controller (i.e. the control model), while keeping the WEC dynamic model employed in these simulations (i.e. the plant model) unaltered. The results of this study indicate a relative low sensitivity of the MPC control strategy to uncertainties in the controller model for the specific case studied here.

A study was performed to optimize the geometry of a point absorber style wave energy converter (WEC). An axisymmetric single-body device, moving in heave only, was considered. Design geometries, generated using a parametric definition, were optimized using genetic algorithms. Each geometry was analyzed using a boundary element model (BEM) tool to obtain corresponding frequency domain models. Based on these models, a pseudo-spectral method was applied to develop a control methodology for each geometry. The performance of each design was assessed using a Bretschneider sea state. The objective of optimization is to maximize harvested energy. In this preliminary investigation, a constraint is imposed on the the geometry to guarantee a linear dynamic model would be valid for all geometries generated by the optimization tool. Numerical results are presented for axisymmetric buoy shapes.

Many of the control strategies for wave energy converters (WECs) that have been studied in the literature rely on the availability of estimates for either the wave elevation or the exciting force caused by the incoming wave; with the objective of addressing this issue, this paper presents the design of a state estimator for a WEC. In particular, the work described in this paper is based on an extended Kalman filter that uses measurements from pressure sensors located on the hull of the WEC to estimate the wave exciting force. Simulation results conducted on a heaving point absorber WEC shows that the extended Kalman filter provides a good estimation of the exciting force in the presence of measurement noise combined with a simplified model of the system, thus making it a suitable candidate for the implementation in an experimental set-up.

A model-scale wave tank test was conducted in the interest of improving control systems design of wave energy converters (WECs). The success of most control strategies is based directly upon the availability of a reduced-order model with the ability to capture the dynamics of the system with sufficient accuracy. For this reason, the test described in this report, which is the first in a series of planned tests on WEC controls, focused on system identification (system ID) and model validation.

This paper presents a novel approach to the modeling and control of AC microgrids that contain spinning machines, power electronic inverters and energy storage devices. The inverters in the system can adjust their frequencies and power angles very quickly, so the modeling focuses on establishing a common references frequency and angle in the microgrid based on the spinning machines. From this dynamic model, nonlinear Hamiltonians surface shaping power flow control method is applied and shown to stabilize. From this approach the energy flow in the system is used to show the energy storage device requirements and limitations for the system. The modeling and control approach presented in this paper enables a unified, stable response to system disturbances, thus increasing resiliency. This paper first describes the dynamic model for a AC microgrid used for the controls development. Then a Hamiltonian energy based control is developed and shown to be stable and robust. A simulation example demonstrate the efficacy of the approach in stabilizing and optimization of the AC microgrid.

This paper presents a control design methodology that begins to address high penetration of renewable energy sources into networked AC microgrid systems. To bring about high performing microgrid systems that contain large amounts of stochastic sources and loads is a major goal for the future of electric power systems. Alternative methods for controlling and analyzing AC microgrid systems will provide understanding into tradeoffs that can be made during the design phase. This paper utilizes a control design methodology, based on Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) [1] that regulates renewable energy sources, loads and identifies energy storage requirements for an AC microgrid system. Both static and dynamic stability conditions are derived for the AC microgrid system. Numerical simulations are performed to demonstrate stability and performance. Two scenarios are considered; i) simple random stochastic renewable source and load AC Microgrid example and ii) a random variable pulse load application for Navy ship AC microgrid systems.

With increasing renewable penetrations and advancements in power electronics associated with smart grid technologies, distributed control of the power grid is quickly becoming a necessity. Once communications are introduced into a control system, the impacts of latency and unreliable communications quickly become a priority. Vector Lyapunov techniques are well suited for the analysis of control systems with structured perturbations. These perturbations can be employed to model uncertainty in communications as well as parameter uncertainty. In this paper, we present results for small signal stability of a simplified two area power system model for several scenarios: bandwidth limited local communications and tie line uncertainty; local communications and bandwidth limited global communications combined with tie line uncertainty; and uncertainty in global communications. These results are intended to be a starting point for the analysis of the impact of communications uncertainty on the stability of power systems.

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Future U.S. Navy ships will require power systems that meet more stringent agility, efficiency, scalability, controllability and resiliency requirements. Modularity and the ability to interconnect power systems having their own energy storage, generation, and loads is an enabling capability. To aid in the design of power system controls, much of what has been learned from advances in the control of networked microgrids is being applied. Developing alternative methods for controlling and analyzing these systems will provide insight into tradeoffs that can be made during the design phase. This paper considers the problem of electric ship power disturbances in response to pulsed loads, in particular, to electromagnetic launch systems. Recent literature has indicated that there exists a trade-off in information and power flow and that intelligent, coordinated control of power flow in a microgrid system (i.e. such as an electric ship) can modify energy storage hardware requirements. The control presented herein was developed to provide the necessary flexibility with little computational burden. It is described analytically and then demonstrated in simulation and hardware.

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The operation of Wave Energy Converter (WEC) devices can pose many challenging problems to the Water Power Community. A key research question is how to significantly improve the performance of these WEC devices through improving the control system design. This report summarizes an effort to analyze and improve the performance of WEC through the design and implementation of control systems. Controllers were selected to span the WEC control design space with the aim of building a more comprehensive understanding of different controller capabilities and requirements. To design and evaluate these control strategies, a model scale test-bed WEC was designed for both numerical and experimental testing (see Section 1.1). Seven control strategies have been developed and applied on a numerical model of the selected WEC. This model is capable of performing at a range of levels, spanning from a fully-linear realization to varying levels of nonlinearity. The details of this model and its ongoing development are described in Section 1.2.

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This paper puts forward a new underwater profiler. The mass of the whole machine is about 7Kg, with smaller volume. It can be air-dropped and suitable for fast deployment, as well as uses pneumatic method to adjust buoyancy, which is reliable with low cost, and can be used for a large scale of deployment. Its attitude can be adjusted throughout modulating barycenter, and with the assistance of wings, water power is utilized for path planning and achieve localized or larger range of supervision. The biggest dive depth is 1000m, in which situation 50 times' profile survey can be achieved, and it is suitable to be applied for emergent maritime search and rescue, etc.

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The goal of this effort was to apply four potential control analysis/design approaches to the design of distributed grid control systems to address the impact of latency and communications uncertainty with high penetrations of photovoltaic (PV) generation. The four techniques considered were: optimal fixed structure control; Nyquist stability criterion; vector Lyapunov analysis; and Hamiltonian design methods. A reduced order model of the Western Electricity Coordinating Council (WECC) developed for the Matlab Power Systems Toolbox (PST) was employed for the study, as well as representative smaller systems (e.g., a two-area, three-area, and four-area power system). Excellent results were obtained with the optimal fixed structure approach, and the methodology we developed was published in a journal article. This approach is promising because it offers a method for designing optimal control systems with the feedback signals available from Phasor Measurement Unit (PMU) data as opposed to full state feedback or the design of an observer. The Nyquist approach inherently handles time delay and incorporates performance guarantees (e.g., gain and phase margin). We developed a technique that works for moderate sized systems, but the approach does not scale well to extremely large system because of computational complexity. The vector Lyapunov approach was applied to a two area model to demonstrate the utility for modeling communications uncertainty. Application to large power systems requires a method to automatically expand/contract the state space and partition the system so that communications uncertainty can be considered. The Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) design methodology was selected to investigate grid systems for energy storage requirements to support high penetration of variable or stochastic generation (such as wind and PV) and loads. This method was applied to several small system models.

This paper will present the model formulation and testing for the integration of renewable energy into networked ac bus microgrid. This paper presents a model of an inverter based ac microgrid that is appropriate for use in advanced control schemes, such as Hamiltonian Surface Shaping and Power Flow Control (HSSPFC). A two inverter three phase ac system with a wye connected resistor-capacitor load is developed, and an example system is presented. The model development will show the electrical power network transformation from the abc to the 0dq domain. Testing and verification procedures will also be discussed demonstrating its behavior.

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To achieve high performance operation of micro-grids that contain stochastic sources and loads is a challenge that will impact cost and complexity. Developing alternative methods for controlling and analyzing these systems will provide insight into tradeoffs that can be made during the design phase. This paper presents a design methodology, based on Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) [1] for a hierarchical control scheme that regulates renewable energy sources and energy storage in a DC micro-grid. Recent literature has indicated that there exists a trade-off in information and power flow and that intelligent, coordinated control of power flow in a microgrid system can modify energy storage hardware requirements. Two scenarios are considered; i) simple two stochastic source with variable load renewable DC Microgrid example and ii) a three zone electric ship with DC Microgrid and varying pulse load profiles. © 2014 IEEE.