Publications

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Paper targets SPEEDAM 2024 (https://www.speedam.org). The paper provides details of a model predictive control designed to operate a four-zone medium-voltage AC/DC electric ship.

Our present electric power grid maximizes spinning inertia of fossil fuel generators (inherent energy storage) to meet stability and performance requirements. Our goal is to begin to investigate the replacement of the large spinning inertia of fossil fuel generators with energy storage systems (ESS) including information flow as a necessary part of the renewable energy sources (RES) and subject to certain criteria. General criteria metrics include: energy storage, information flow, estimation, communication links, central versus decentralized, etc. Our focus is on evaluating the Fisher Information Equivalency (FIE) metric as a multi-criteria trade-off cost function for the minimization of ESS options and information flow. This paper begins with a formal conceptual definition of an infinite bus. Then a simple example of a One Machine Infinite Bus (OMIB) system with a Unified Power Flow Controller (UPFC) to demonstrate the FIE-based approach to minimize the ESS. A second more detailed example of several spinning machines are included with representative power electronic and ESS for RES that are attached to the electric power grid. A simple trade-study begins to highlight requirements to support large penetration of RES. Keep in mind for a large scale high penetration of RES will require large investments in ESS which we want to minimize.

The National Aeronautics and Space Administration’s (NASA) Artemis program seeks to establish the first long-term presence on the Moon as part of a larger goal of sending the first astronauts to Mars. To accomplish this, the Artemis program is designed to develop, test, and demonstrate many technologies needed for deep space exploration and supporting life on another planet. Long-term operations on the lunar base include habitation, science, logistics, and in-situ resource utilization (ISRU). In this paper, a Lunar DC microgrid (LDCMG) structure is the backbone of the energy distribution, storage, and utilization infrastructure. The method to analyze the LDCMG power distribution network and ESS design is the Hamiltonian surface shaping and power flow control (HSSPFC). This ISRU system will include a networked three-microgrid system which includes a Photo-voltaic (PV) array (generation) on one sub-microgrid and water extraction (loads) on the other two microgrids. A system's reduced-order model (ROM) will be used to create a closed-form analytical model. Ideal ESS devices will be placed alongside each state of the ROM. The ideal ESS devices determine the response needed to conform to a specific operating scenario and system specifications.

The following article describes an optimal control algorithm for the operation and study of an electric microgrid designed to power a lunar habitat. A photovoltaic (PV) generator powers the habitat and the presence of predictable lunar eclipses necessitates a system to prioritize and control loads within the microgrid. The algorithm consists of a reduced order model (ROM) that describes the microgrid, a discretization of the equations that result from the ROM, and an optimization formulation that controls the microgrid’s behavior. In order to validate this approach, the paper presents results from simulation based on lunar eclipse information and a schedule of intended loads.

A high altitude electromagnetic pulse (HEMP) caused by a nuclear explosion has the potential to severely impact the operation of large-scale electric power grids. This paper presents a top-down mitigation design strategy that considers grid-wide dynamic behavior during a simulated HEMP event - and uses optimal control theory to determine the compensation signals required to protect critical grid assets. The approach is applied to both a standalone transformer system and a demonstrative 3-bus grid model. The performance of the top-down approach relative to conventional protection solutions is evaluated, and several optimal control objective functions are explored. Finally, directions for future research are proposed.

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This new research provides transformative marine energy technology to effectively power the blue economy. Harmonizing the energy capture and power from Wave Energy Converter (WEC) arrays require innovative designs for the buoy, electric machines, energy storage systems (ESS), and coordinated onshore electric power grid (EPG) integration. This paper introduces two innovative elements that are co-designed to extract the maximum power from; i) individual WEC buoys with a multi-resonance controller design and ii) synchronized with power packet network phase control through the physical placement of the WEC arrays reducing ESS requirements. MATLAB/Simulink models were created for the WEC array dynamics and control systems with Bretschneider irregular wave spectrum as inputs. The numerical simulation results show that for ideal physical WEC buoy array phasing of 60 degrees the ESS peak power and energy capacity requirements are minimized while the multi-resonant controllers optimize EPG power output for each WEC buoy.

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Pulse power loads are becoming increasingly more common in many applications primarily due to applications like radar, lasers, and the technologies such as EMALS (ElectroMagnetic Aircraft Launch Systems) on next-generation aircraft carriers. Pulse power loads are notorious for causing stability issues. Stability for pulse power loads can be defined as metastable, where the system can be unstable for a portion of the pulse as long as the stability is re-established over the entire pulse. Dynamic characteristics for step changes in load can be improved with a modified boost converter topology in conjunction with bang-bang control. Improvement in the metastability margins will be presented through simulations with the application of the modified topology to pulse power loads.

This paper presents a nonlinear control design technique that capitalizes on an hour glass (HG) variable geometry wave energy converter (WEC). The HG buoy is assumed to operate in the heave motion of the wave. The unique interaction between the HG buoy and the wave creates a nonlinear cubic storage effect that produces actual energy storage or reactive power during operation. A multi-frequency Bretschneider spectrum wave excitation input is reviewed for the HG design both with constant and varying steepness angle profiles which demonstrates further increased power generation. Numerical simulations are performed to demonstrate the increase in power generation with changing sea states. The objective is to increase the power generation from multi-frequency nonlinear dynamic sources.

An array of Wave Energy Converters (WEC) is required to supply a significant power level to the grid. However, the control and optimization of such an array is still an open research question. This paper analyzes two aspects that have a significant impact on the power production. First the spacing of the buoys in a WEC array will be analyzed to determine the optimal shift between the buoys in an array. Then the wave force interacting with the buoys will be angled to create additional sequencing between the electrical signals. A cost function is proposed to minimize the power variation and energy storage while maximizing the delivered energy to the onshore point of common coupling to the electrical grid.

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Typical Type-4 wind turbines use DC-link inverters to couple the electrical machine to the power grid. Each wind turbine has two power conversion steps. Therefore, an N-turbine farm will have 2N power converters. This work presents a DC bus collection system for a type-4 wind farm that reduces the overall required number of converters and minimizes the energy storage system (ESS) requirements. This approach requires one conversion step per turbine, one converter for the ESS and a single grid coupling converter, which leads to N + 2 converters for the wind farm which will result in significant cost savings. However, one of the trade-offs for a DC collection system is the need for increased energy storage to filter the power variations and improve power quality to the grid. This paper presents a novel approach to an effective DC bus collection system design. The DC collection for the wind farm implements a power phasing control method between turbines that filter the variations and improves power quality while minimizing the need for added energy storage system hardware and improved power quality. The phasing control takes advantage of a novel power packet network concept with nonlinear power flow control design techniques that guarantees both stable and enhanced dynamic performance. This paper presents the theoretical design of the DC collection and phasing control. To demonstrate the efficacy of this approach detailed numerical simulation examples are presented.

This study presents a numerical model of a WEC array. The model will be used in subsequent work to study the ability of data assimilation to support power prediction from WEC arrays and WEC array design. In this study, we focus on design, modeling, and control of the WEC array. A case study is performed for a small remote Alaskan town. Using an efficient method for modeling the linear interactions within a homogeneous array, we produce a model and predictionless feedback controllers for the devices within the array. The model is applied to study the effects of spectral wave forecast errors on power output. The results of this analysis show that the power performance of the WEC array will be most strongly affected by errors in prediction of the spectral period, but that reductions in performance can realistically be limited to less than 10% based on typical data assimilation based spectral forecasting accuracy levels.

This paper develops a power packet network (PPN) for integrating wave energy converter (WEC) arrays into microgrids. First a simple AC Resistor-Inductor-Capacitor (RLC) circuit operating at a power factor of one is introduced and shown to be a PPN. Next, an AC inverter-based network is analyzed and shown to be a PPN. Then this basic idea is utilized to asynchronously connect a WEC array to an idealized microgrid without additional energy storage. Specifically, NWECs can be physically positioned such that the incoming regular waves will produce an output emulating an N-phase AC system such that the PPN output power is constant. In the final example, the benefits of utilizing PPN phasing is demonstrated that analyzes a grid to substation to WEC array configuration. The numerical simulation results show that for ideal physical WEC buoy phasing of 60 and 120 degrees the energy storage system (ESS) peak power and energy capacity requirements are at the minimum.

The following research presents an optimal control framework called Oxtimal that facilitates the efficient use and control of photovoltaic (PV) solar arrays. This framework consists of reduced order models (ROM) of photovoltaics and DC connection components connected to an electric power grid (EPG), a discretization of the resulting state equations using an orthogonal spline collocation method (OSCM), and an optimization driver to solve the resulting formulation. Once formulated, the framework is validated using realistic solar profiles and loads from actual residential applications.

The U.S. Navy is investing in the development of new technologies that broaden warship capabilities and maintain U.S. naval superiority. Specifically, Naval Sea Systems Command (NAVSEA) is supporting the development of power systems technologies that enable the Navy to realise an all-electric warship. A challenge to fielding an all-electric power system architecture includes minimising the size of energy storage systems (ESS) while maintaining the response times necessary to support potential pulsed loads. This work explores the trade-off between energy storage size requirements (i.e. mass) and performance (i.e. peak power, energy storage, and control bandwidth) in the context of a power system architecture that meets the needs of the U.S. Navy. In this work, the simulated time domain responses of a representative power system were evaluated under different loading conditions and control parameters, and the results were considered in conjunction with sizing constraints of and estimated specific power and energy densities of various storage technologies. The simulation scenarios were based on representative operational vignettes, and a Ragone plot was used to illustrate the intersection of potential energy storage sizing with the energy and power density requirements of the system. Furthermore, the energy storage control bandwidth requirements were evaluated by simulation for different loading scenarios. Two approaches were taken to design an ESS: one based only on time domain power and energy requirements from simulation and another based on bandwidth (specific frequency) limitations of various technologies.

Through the use of advanced control techniques, wave energy converters (WECs) can achieve substantial increases in energy absorption. The motion of the WEC device is a significant contribution to the energy absorbed by the device. Reactive (complex conjugate) control maximizes the energy absorption due to the impedance matching. The issue with complex conjugate control is that, in general, the controller is noncausal, which requires prediction of the incoming waves. This article explores the potential of employing system identification techniques to build a causal transfer function that approximates the complex conjugate controller over a finite frequency band of interest. This approach is quite viable given the band-limited nature of ocean waves. The resulting controller is stable, and the average efficiency of the power captured by the causal controller in realistic ocean waves is 99%, when compared to the noncausal complex conjugate.

This paper presents a nonlinear geometric buoy design for Wave Energy Converters (WECs). A nonlinear dynamic model is presented for an hour glass (HG) configured WEC. The HG buoy operates in heave motion or as a single Degree-of-Freedom (DOF). The unique formulation of the interaction between the buoy and the waves produces a nonlinear stiffening effect that provides the actual energy storage or reactive power during operation. A Complex Conjugate Control (C3) with a practical Proportional-Derivative (PD) controller is employed to optimize power absorption for off-resonance conditions and applied to a linear right circular cylinder (RCC) WEC. For a single frequency the PDC3 RCC buoy is compared with the HG buoy design. A Bretschneider spectrum of wave excitation input conditions are reviewed and evaluated for the HG buoy. Numerical simulations demonstrate power and energy capture for the HG geometric buoy design which incorporates and capitalizes on the nonlinear geometry to provide reactive power for the single DOF WEC. By exploiting the nonlinear physics in the HG design simplified operational performance is observed when compared to an optimized linear cylindrical WEC. The HG steepness angle α with respect to the wave is varied and initially optimized for improved energy capture.

Wave Energy Converter (WEC) technologies transform power from the waves to the electrical grid. WEC system components are investigated that support the performance, stability, and efficiency as part of a WEC array. To this end, Aquaharmonics Inc took home the 1.5 million grand prize in the 2016 U.S. Department of Energy Wave Energy Prize, an 18-month design-build-test competition to increase the energy capture potential of wave energy devices. Aquaharmonics intends to develop, build, and perform open ocean testing on a 1: 7 scale device. Preliminary wave tank testing on the mechanical system of the 1: 20 scale device has yielded a data-set of operational conditions and performance. In this paper, the Hamiltonian surface shaping and power flow control (HSSPFC) method is used in conjunction with scaled wave tank test data to explore the design space for the electrical transmission of energy to the shore-side power grid. Of primary interest is the energy storage system (ESS) that will electrically link the WEC to the shore. Initial analysis results contained in this paper provide a trade-off in storage device performance and design selection.

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Pulsed power loads (PPLs) are highly non-linear and can cause significant stability and power quality issues in a microgrid. One way to mitigate many of these issues is by designing an Energy Storage System (ESS) to offset the PPL. This paper provides a baseline for ESS control and specifications to mitigate the effects of PPL's. ESS will maintain a constant bus voltage and decouple the generation sources from the PPL. The ESS specifications are realized with ideal, band-limited hybrid battery and flywheels models and simulated to demonstrate the efficacy of the control system.

Our work extends the concepts and tools of Hamiltonian Surface Shaping and Power Flow Control (HS SPFC) for electro-mechanical (EM) systems(i.e., adiabatic irreversible work processes and Hamiltonian natural systems)to Exergy Surface Shaping and Thermodynamic Flow Control (ESSTFC) for electro-mechanical-thermal (EMT) systems (i.e., irreversible work processes with heat and mass flows). The extension of HSSPFC requires the development of exergy potential functions, irreversible entropy production terms of the entropy balance equation to obtain the exergy destruction terms for inclusion in the exergy balance equation, and variational principles for producing consistent equations of motion for coupled EMT systems. The Hamiltonian for natural EM systems is an exergy potential function which leaves the development of exergy potential functions for the thermal part of the coupled models. This development is completed by integrating the exergy function over the control volume subject to the modeling assumptions. The irreversible entropy production terms are the exergy destruction terms of the exergy balance equation and the generalization of the mechanical dissipation and electrical resistance within EM systems. These generalized dissipation terms enable the derivation of a consistent set of coupled equations of motion for EMT systems. For this paper, Extended Irreversible Thermodynamics will be utilized to produce consistent thermal equations of motion that directly include the exergy destruction terms. There are several variational principles that are available for application to EMT systems. We focus on the variational principles developed by Biot and Fung [1, 2]. Furthermore, a simplified EMT system that models the EMT dynamics of a Navy ship equipped with a railgun is used to demonstrate the application of ESSTFC for designing high performance, stable nonlinear controllers for EMT systems.

The dynamic model ofWave Energy Converters (WECs) may have nonlinearities due to several reasons such as a nonuniform buoy shape and/or nonlinear power takeoff units. This paper presents the Hamiltonian Surface-Shaping (HSS) approach as a tool for the analysis and design of nonlinear control of WECs. The Hamiltonian represents the stored energy in the system and can be constructed as a function of the WEC's system states, its position, and velocity. The Hamiltonian surface is defined by the energy storage, while the system trajectories are constrained to this surface and determined by the power flows of the applied non-conservative forces. The HSS approach presented in this paper can be used as a tool for the design of nonlinear control systems that are guaranteed to be stable. The optimality of the obtained solutions is not addressed in this paper. The case studies presented here cover regular and irregular waves and demonstrate that a nonlinear control system can result in a multiple fold increase in the harvested energy.

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Through the use of advanced control techniques, wave energy converters have significantly improved energy absorption. The motion of the WEC device is a significant contribution to the energy absorbed by the device. Reactive control (complex conjugate control) maximizes the energy absorption due to the impedance matching. The issue with complex conjugate control is that the controller is non-causal, which requires prediction into the oncoming waves to the device. This paper explores the potential of using system identification (SID) techniques to build a causal transfer function that approximates the complex conjugate controller over a specific frequency band of interest. The resulting controller is stable, and the average efficiency of the power captured by the causal controller is 99%, when compared to the non-causal complex conjugate.

This paper presents a control design methodology that addresses high penetration of variable generation or renewable energy sources and loads for networked AC /DC microgrid systems as an islanded subsystem or as part of larger electric power grid systems. High performance microgrid systems that contain large amounts of stochastic sources and loads is a major goal for the future of electric power systems. Alternatively, methods for controlling and analyzing AC/ DC microgrid systems will provide an understanding into the tradeoffs that can be made during the design phase. This method develops both a control design methodology and realizable hierarchical controllers that are based on the Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) methodology that regulates renewable energy sources, varying loads and identifies energy storage requirements for a networked AC/DC microgrid system. Both static and dynamic stability conditions are derived. A renewable energy scenario is considered for a networked three DC microgrids tied into an AC ringbus configuration. Numerical simulation results are presented.

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This paper presents a solution to the optimal control problem of a three degrees-of-freedom (3DOF) wave energy converter (WEC). The three modes are the heave, pitch, and surge. The dynamic model is characterized by a coupling between the pitch and surge modes, while the heave is decoupled. The heave, however, excites the pitch motion through nonlinear parametric excitation in the pitch mode. This paper uses Fourier series (FS) as basis functions to approximate the states and the control. A simplified model is first used where the parametric excitation term is neglected and a closed-form solution for the optimal control is developed. For the parametrically excited case, a sequential quadratic programming approach is implemented to solve for the optimal control numerically. Numerical results show that the harvested energy from three modes is greater than three times the harvested energy from the heave mode alone. Moreover, the harvested energy using a control that accounts for the parametric excitation is significantly higher than the energy harvested when neglecting this nonlinear parametric excitation term.

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 reference frequency and angle in the microgrid based on the spinning machines. From this dynamic model, nonlinear Hamiltonian surface shaping and 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. This paper first describes the model for a single bus AC microgrid with a Hamiltonian control, then extends this model and control to a more general class of multiple bus AC microgrids. Simulation results demonstrate the efficacy of the approach in stabilizing and optimization of the microgrid.

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Many candidate power system architectures are being evaluated for the Navy’s next generation all-electric warship. One proposed power system concept involves the use of dual-wound generators to power both the Port and Starboard side buses using different 3-phase sets from the same machine (Doerry, 2015). This offers the benefit of improved efficiency through reduced engine light-loading and improved dispatch flexibility, but the approach couples the two busses through a common generator, making one bus vulnerable to faults and other dynamic events on the other bus. Thus, understanding the dynamics of cross-bus coupling is imperative to the successful implementation of a dual-wound generator system. In (Rashkin, 2017), a kilowatt-scale system was analysed that considered the use of a dual-wound permanent magnet machine, two passive rectifiers, and two DC buses with resistive loads. For this system, dc voltage variation on one bus was evaluated in the time domain as a function of load changes on the other bus. Therein, substantive cross-bus coupling was demonstrated in simulation and hardware experiments. The voltage disturbances were attributed to electromechanical (i.e. speed disturbances) as well as electromagnetic coupling mechanisms. In this work, a 25 MVA dual-wound generator was considered, and active rectifier models were implemented in Matlab both using average value modelling and switching (space vector modulation) simulation models. The frequency dynamics of the system between the load on one side and the dc voltage on the other side was studied. The coupling is depicted in the frequency domain as a transfer function with amplitude and phase and is shown to have distinct characteristics (i.e. frequency regimes) associated with physical coupling mechanisms such as electromechanical and electromagnetic coupling as well as response characteristics associated with control action by the active rectifiers. In addition, based on requirements outlined in draft Military Standard 1399-MVDC, an approach to derive specifications will be discussed and presented. This method will aid in quantifying the allowable coupling of energy from one bus to another in various frequency regimes as a function of other power system parameters. Finally, design and control strategies will be discussed to mitigate cross-bus coupling. The findings of this work will inform the design, control, and operation of future naval warship power systems.

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In this study, we employ a numerical model to compare the performance of a number of wave energy converter control strategies. The controllers selected for evaluation span a wide range in their requirements for implementation. Each control strategy is evaluated using a single numerical model with a set of sea states to represent a deployment site off the coast of Newport, OR. A number of metrics, ranging from power absorption to kinematics, are employed to provide a comparison of each control strategy's performance that accounts for both relative benefits and costs. The results show a wide range of performances from the different controllers and highlight the need for a holistic design approach which considers control design as a parallel component within the larger process WEC design.

This report summarizes collaborative efforts between Secure Scalable Microgrid and Korean Institute of Energy Research team members . The efforts aim to advance microgrid research and development towards the efficient utilization of networked microgrids . The collaboration resulted in the identification of experimental and real time simulation capabilities that may be leveraged for networked microgrids research, development, and demonstration . Additional research was performed to support the demonstration of control techniques within real time simulation and with hardware in the loop for DC microgrids .

This research presents a predictive engine that integrates into an on-line optimal control planner for electrical microgrids. This controller models the behavior of the underlying system over a specified time horizon and then solves for a control over this period. In an electrical microgrid, such predictions are challenging to obtain in the presence of errors in the sensor information. The likelihood of instrumentation errors increases as microgrids become more complex and cyber threats more common. In order to overcome these difficulties, details are provided about a predictive engine robust to errors.

For a three-degree-of-freedom wave energy converter (heave, pitch, and surge), the equations of motion could be coupled depending on the buoy shape. This paper presents a multiresonant feedback control, in a general framework, for this type of a wave energy converter that is modeled by linear time invariant dynamic systems. The proposed control strategy finds the optimal control in the sense that it computes the control based on the complex conjugate criteria. This control strategy is relatively easy to implement since it is a feedback control in the time domain that requires only measurements of the buoy motion. Numerical tests are presented for two different buoy shapes: a sphere and a cylinder. Regular, Bretschnieder, and Ochi-Hubble waves are tested. Simulation results show that the proposed controller harvests energy in the pitch-surge-heave modes that is about three times the energy that can be harvested using a heave-only device. This multiresonant control can also be used to shift the energy harvesting between the coupled modes, which can be exploited to eliminate one of the actuators while maintaining about the same level of energy harvesting.

For a heave-pitch-surge three-degrees-of-freedom wave energy converter, the heave mode is usually decoupled from the pitch-surge modes for small motions. The pitch-surge modes are usually coupled and are parametrically excited by the heave mode, depending on the buoy geometry. In this paper, a Model Predictive Control is applied to the parametric excited pitch-surge motion, while the heave motion is optimized independently. The optimality conditions are derived, and a gradient-based numerical optimization algorithm is used to search for the optimal control. Numerical tests are conducted for regular and Bretschneider waves. The results demonstrate that the proposed control can be implemented to harvest more than three times the energy that can be harvested using a heave-only wave energy converter. The energy harvested using a parametrically excited model is higher than that is harvested when using a linear model.

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Empirically based modeling is an essential aspect of design for a wave energy converter. Empirically based models are used in structural, mechanical and control design processes, as well as for performance prediction. Both the design of experiments and methods used in system identification have a strong impact on the quality of the resulting model. This study considers the system identification and model validation process based on data collected from a wave tank test of a model-scale wave energy converter. Experimental design and data processing techniques based on general system identification procedures are discussed and compared with the practices often followed for wave tank testing. The general system identification processes are shown to have a number of advantages, including an increased signal-to-noise ratio, reduced experimental time and higher frequency resolution. The experimental wave tank data is used to produce multiple models using different formulations to represent the dynamics of the wave energy converter. These models are validated and their performance is compared against one another. While most models of wave energy converters use a formulation with surface elevation as an input, this study shows that a model using a hull pressure measurement to incorporate the wave excitation phenomenon has better accuracy.

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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.

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.

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. In conclusion, 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 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.

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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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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.

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Laboratory Directed Research and Design (LDRD) originating technologies are being developed to address challenges inherent to highly stochastic energy sources and loads, to conceivably satisfy the electrical energy needs of national/international power systems. The Enabling Secure, Scalable Microgrids with High Penetration Renewables Grand Challenge LDRD (FY11-FY13) aimed to develop a novel intelligent grid architecture, Secure Scalable Microgrid (SSM), based on closed loop controls and an agent-based architecture supporting intelligent power flow control. The approach was to enable self-healing, self-adapting, self-organizing architectures and allow a trade-off between storage in the grid versus information flow to control generation sources, power distribution, and where necessary, loads. L

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.

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In this paper, 1 the equations are formulated to model the dynamic behavior of a wind turbine coupled to the electric grid through a Unified Power Flow Controller (UPFC). This concept is demonstrated in order to treat wind plants more as a controllable energy source rather than a negative load, which is the current trend among renewable energy systems. The results of this research include the determination of the required performance of a proposed Flexible AC Transmission System (FACTS)/storage device, such as a UPFC, to enable the maximum power output of a wind turbine while meeting the constraints of the bulk electric system. The UPFC is required to operate as both a generator and load (energy storage) on the power system in this design. An illustrative example demonstrates this concept applied to a UPFC with a 1MW fixed speed wind turbine. The wind turbine is operated with multiple wind profiles for below-rated wind power conditions. The wind turbine is connected in series through a UPFC to the infinite bus. Numerical simulation cases are reviewed that best demonstrate the stability and performance of a UPFC as applied to a renewable energy system. © 2012 IEEE.

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In this paper, the swing equations for renewable generators are formulated as a natural Hamiltonian system with externally applied non-conservative forces. A two-step process referred to as Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) is used to analyze and design feedback controllers for the renewable generator system. The results of this research include the determination of the required performance of a proposed Flexible AC Transmission System (FACTS)/storage device, such as a Unified Power Flow Controller (UPFC), to enable the maximum power output of a wind turbine while meeting the power system constraints on frequency and phase. The UPFC is required to operate as both a generator and load (energy storage) on the power system in this design. Necessary and sufficient conditions for stability of renewable generator systems are determined based on the concepts of Hamiltonian systems, power flow, exergy (the maximum work that can be extracted from an energy flow) rate, and entropy rate. An illustrative example demonstrates this HSSPFC methodology. It includes a 600 kW wind turbine, variable speed variable pitch configuration. The wind turbine is operated with a turbulent wind profile for below-rated wind power conditions. The wind turbine is connected in series through a UPFC to the infinite bus. Numerical simulation cases are reviewed that best demonstrate the stability and performance of HSSPFC as applied to a renewable energy system. © 2011 IEEE.

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The swing equations for renewable generators connected to the grid are developed and a wind turbine is used as an example. The swing equations for the renewable generators are formulated as a natural Hamiltonian system with externally applied non-conservative forces. A two-step process referred to as Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) is used to analyze and design feedback controllers for the renewable generators system. This formulation extends previous results on the analytical verification of the Potential Energy Boundary Surface (PEBS) method to nonlinear control analysis and design and justifies the decomposition of the system into conservative and non-conservative systems to enable a two-step, serial analysis and design procedure. The first step is to analyze the system as a conservative natural Hamiltonian system with no externally applied non-conservative forces. The Hamiltonian surface of the swing equations is related to the Equal-Area Criterion and the PEBS method to formulate the nonlinear transient stability problem. This formulation demonstrates the effectiveness of proportional feedback control to expand the stability region. The second step is to analyze the system as natural Hamiltonian system with externally applied non-conservative forces. The time derivative of the Hamiltonian produces the work/rate (power flow) equations which is used to ensure balanced power flows from the renewable generators to the loads. The Second Law of Thermodynamics is applied to the power flow equations to determine the stability boundaries (limit cycles) of the renewable generators system and enable design of feedback controllers that meet stability requirements while maximizing the power generation and flow to the load. Necessary and sufficient conditions for stability of renewable generators systems are determined based on the concepts of Hamiltonian systems, power flow, exergy (the maximum work that can be extracted from an energy flow) rate, and entropy rate. © 2010 IEEE.

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In this paper, the swing equations for renewable generators are formulated as a natural Hamiltonian system with externally applied non-conservative forces. A two-step process referred to as Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) is used to analyze and design feedback controllers for the renewable generator system. This formulation extends previous results on the analytical verification of the Potential Energy Boundary Surface (PEBS) method to nonlinear control analysis and design and justifies the decomposition of the system into conservative and non-conservative systems to enable a two-step, serial analysis and design procedure. In particular, this approach extends the work done by developing a formulation which applies to a larger set of Hamiltonian Systems that has Nearly Hamiltonian Systems as a subset. The results of this research include the determination of the required performance of a proposed Flexible AC Transmission System (FACTS)/storage device to enable the maximum power output of a wind turbine while meeting the power system constraints on frequency and phase. The FACTS/storage device is required to operate as both a generator and load (energy storage) on the power system in this design. The Second Law of Thermodynamics is applied to the power flow equations to determine the stability boundaries (limit cycles) of the renewable generator system and enable design of feedback controllers that meet stability requirements while maximizing the power generation and flow to the load. Necessary and sufficient conditions for stability of renewable generators systems are determined based on the concepts of Hamiltonian systems, power flow, exergy (the maximum work that can be extracted from an energy flow) rate, and entropy rate.

Active aerodynamic load control of wind turbine blades has been heavily researched for years by the wind energy research community and shows great promise for reducing turbine fatigue damage. One way to benefit from this technology is to choose to utilize a larger rotor on a turbine tower and drive train to realize increased turbine energy capture while keeping the fatigue damage of critical turbine components at the original levels. To assess this rotor-increase potential, Sandia National Laboratories and FlexSys Inc. performed aero/structural simulations of a 1.5MW wind turbine at mean wind speeds spanning the entire operating range. Moment loads at several critical system locations were post-processed and evaluated for fatigue damage accumulation at each mean wind speed. Combining these fatigue damage estimates with a Rayleigh wind-speed distribution yielded estimates of the total fatigue damage accumulation for the turbine. This simulation procedure was performed for both the turbine baseline system and the turbine system incorporating a rotor equipped with FlexSys active aerodynamic load control devices. The simulation results were post-processed to evaluate the decrease in the blade root flap fatigue damage accumulation provided by the active aero technology. The blade length was increased until the blade root flap fatigue damage accumulation values matched those of the baseline rotor. With the new rotor size determined, the additional energy capture potential was calculated. These analyses resulted in an energy capture increase of 11% for a mean wind speed of 6.5m/s.

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This paper presents a new nonlinear control methodology for slewing spacecraft, which provides both necessary and sufficient conditions for stability by identifying the stability boundaries, rigid body modes, and limit cycles. Conservative Hamiltonian system concepts, which are equivalent to static stability of airplanes, are used to find and deal with the static stability boundaries: rigid body modes. The application of exergy and entropy thermodynamic concepts to the work-rate principle provides a natural partitioning through the second law of thermodynamics of power flows into exergy generator, dissipator, and storage for Hamiltonian systems that is employed to find the dynamic stability boundaries: limit cycles. This partitioning process enables the control system designer to directly evaluate and enhance the stability and performance of the system by balancing the power flowing into versus the power dissipated within the system subject to the Hamiltonian surface (power storage). Relationships are developed between exergy, power flow, static and dynamic stability, and Lyapunov analysis. The methodology is demonstrated with two illustrative examples: (1) a nonlinear oscillator with sinusoidal damping and (2) a multi-input-multioutput three-axis slewing spacecraft that employs proportional-integral-derivative tracking control with numerical simulation results.

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This paper develops a novel control system design methodology that uniquely combines: concepts from thermodynamic exergy and entropy; Hamiltonian systems; Lyapunov's direct method and Lyapunov optimal analysis; electric AC power concepts; and power flow analysis. Relationships are derived between exergy/entropy and Lyapunov optimal functions for Hamiltonian systems. The methodology is demonstrated with a couple of fundamental numerical simulation examples: 1) a PID regulator control for a linear mass-spring-damper system and 2) a Duffing oscillator/Coulomb friction nonlinear model that employs PID regulator control. The control system performances are partitioned and evaluated based on exergy generation and exergy dissipation terms. This novel nonlinear control methodology results in both necessary and sufficient conditions for stability of nonlinear systems. © 2006 IEEE.

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Collective systems are typically defined as a group of agents (physical and/or cyber) that work together to produce a collective behavior with a value greater than the sum of the individual parts. This amplification or synergy can be harnessed by solving an inverse problem via an information-flow/communications grid: given a desired macroscopic/collective behavior find the required microscopic/individual behavior of each agent and the required communications grid. The goal of this report is to describe the fundamental nature of the Hamiltonian function in the design of collective systems (solve the inverse problem) and the connections between and values of physical and information exergies intrinsic to collective systems. In particular, physical and information exergies are shown to be equivalent based on thermodynamics and Hamiltonian mechanics.

The development of tools for complex dynamic security systems is not a straight forward engineering task but, rather, a scientific task where discovery of new scientific principles and math is necessary. For years, scientists have observed complex behavior but have had difficulty understanding it. Prominent examples include: insect colony organization, the stock market, molecular interactions, fractals, and emergent behavior. Engineering such systems will be an even greater challenge. This report explores four tools for engineered complex dynamic security systems: Partially Observable Markov Decision Process, Percolation Theory, Graph Theory, and Exergy/Entropy Theory. Additionally, enabling hardware technology for next generation security systems are described: a 100 node wireless sensor network, unmanned ground vehicle and unmanned aerial vehicle.

This report contains the results of a research effort on advanced robot locomotion. The majority of this work focuses on walking robots. Walking robot applications include delivery of special payloads to unique locations that require human locomotion to exo-skeleton human assistance applications. A walking robot could step over obstacles and move through narrow openings that a wheeled or tracked vehicle could not overcome. It could pick up and manipulate objects in ways that a standard robot gripper could not. Most importantly, a walking robot would be able to rapidly perform these tasks through an intuitive user interface that mimics natural human motion. The largest obstacle arises in emulating stability and balance control naturally present in humans but needed for bipedal locomotion in a robot. A tracked robot is bulky and limited, but a wide wheel base assures passive stability. Human bipedal motion is so common that it is taken for granted, but bipedal motion requires active balance and stability control for which the analysis is non-trivial. This report contains an extensive literature study on the state-of-the-art of legged robotics, and it additionally provides the analysis, simulation, and hardware verification of two variants of a proto-type leg design.

This paper 1 develops a novel control system design methodology that uniquely combines: concepts from thermodynamic exergy and entropy; Hamiltonian systems; Lyapunov's direct method and Lyapunov optimal analysis; electric AC power concepts; and power flow analysis. Relationships are derived between exergy/entropy and Lyapunov optimal functions for Hamiltonian systems. The methodology is demonstrated with two fundamental numerical simulation examples: 1) a Duffing oscillator/Coulomb friction nonlinear model that employs PID regulator control and 2) a van der Pol nonlinear oscillator system. The control system performances and/or appropriately identified terms are partitioned and evaluated based on exergy generation and exergy dissipation terms. This novel nonlinear control methodology results in both necessary and sufficient conditions for stability of nonlinear systems.

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The development of lightweight flexible structures that include both advanced control and active material will impact several space application areas. One way to reduce vibration is the combination of advanced control methods such as nonlinear adaptive control plus active structure technology. Active structures with both sensors and actuators, strategically placed along the structure, can suppress vibrations and enhance slewing performance. Active vibration suppression is accomplished with a graphite/epoxy composite structure that includes embedded strain sensors and actuators.