Publications

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The following paper presents a framework for the optimal control of an electric warship using a load profile derived from an operational vignette. This framework consists of three key components: a reduced order model of an electric ship, a discretization of the resulting constitutive equations using an orthogonal spline collocation method, and an optimization engine to solve the resulting formulation. Once assembled, this control framework is validated through its application to a four zone model of a medium voltage DC (MVDC) electric ship using a load profile from an operational vignette,

The models of multi-zone electric ship is important to the development of ship operational capability and performance. However, there is not one best model type that can fit all the needs of the engineering process. High-fidelity models are needed to act as a digital twin to the system hardware for testing and validation purposes. However, a highly detailed digital model of a MVDC does not enable insight and development of analytical control and optimization algorithms. This paper presents a reduced order model (ROM) of a notional four-zone medium voltage ship. This ROM can be written in a closed-form analytical expression that is appropriate for analysis and high-level supervisory control synthesis.

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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.

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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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.

The purpose of this paper is to investigate Wave Energy Converter (WEC) technologies that are required to transform power from the waves to the electrical grid. WEC system components are reviewed that reveal the performance, stability, and efficiency. These WEC system individual components consists of; control methods, electro-mechanical drive-train, generator machines, power electronic converters, energy storage systems, and electrical grid integration. Initially, the transformation of energy from the wave to the electric grid is explored in detail for an individual WEC system. A control design methodology is then presented that addresses high penetration of Renewable Energy Sources (RES) and loads for networked AC/DC microgrid islanded subsystems. Both static and dynamic stability conditions are identified for the networked AC/DC microgrid system. Detailed numerical simulations were conducted for the electro-mechanical drivetrain system which includes; the dynamic responses, power generation for multiple wave conditions, and total efficiency of the energy/power conversion process. As a renewable energy scenario, the AC/DC microgrid islanded subsystem is employed to integrate an array of WECs. Preliminary Energy Storage System (ESS) power requirements are determined for the renewable energy scenario.

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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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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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.