On Integrating Object Detection Capability into a Coastal Energy Conversion System

U.S. Department of Defense, Office of Naval Research

Project Summary
Near-shore wave energy converter arrays may be designed to provide uninterrupted power to a number of coastal sensing applications, including sensors monitoring meteorological conditions, sea-water chemical/physical properties, tsunamis and storm surges, fish and other marine life, coastal and sea-floor conditions, etc. Active control seeking near-optimum hydrodynamic operation has been shown to enable a dramatic reduction in device size for required amounts of power. Certain features of the control strategies developed make them particularly amenable to incorporation of additional sensing capability based on the wave patterns generated by intruding submerged objects (at distances on the order of 1000 m), in particular, the phase changes to the approaching wave field that occur in the presence of an object.

This project investigates schemes for actively controlled wave energy converter arrays in coastal waters which enable detection of intruding marine vessels by monitoring the spatial and temporal energy conversion rates over the arrays. The proposed approach mainly utilizes a linear-theory based understanding of wave propagation, body hydrodynamics, and controller design, but also incorporates nonlinear extensions based on Volterra series modeling. Of particular interest, is using small device sizes, for which response nonlinearities can be significant. Therefore, it is proposed to exploit the nonlinearities to enhance energy generation. Furthermore, also investigate ways to utilize features of the nonlinear response that enable preferential coupling to certain phase signatures, so that energy conversion by certain array elements would imply the presence of an object. Analysis and simulation results on arrays of moored devices will be extended to free-floating arrays.

The first objective of the overall effort is to evaluate the proposed techniques through analysis and simulation. For near-shore sea areas to be identified, two categories or types of array designs with their own particular control strategies will be investigated, using Hydrodynamics and Controls based analytical techniques and detailed simulations (linear and nonlinear). Necessary in this process is the characterization of the phase-change signatures of various submerged objects when stationary and when in translation. This knowledge will provide the test parameters for the designs to be investigated. The first two years of the overall, 4-year long, effort are expected to provide the groundwork for the development of a prototype system. Prior to ‘at-sea’ prototype testing, first test the prototype in a wave-basin environment. To provide reliable designs for the testing in the wave basin, wave tank testing under simplified conditions is also proposed. The overall testing sequence from wave tank tests through wave-basin tests to ‘at sea’ tests is expected to occur over years 3 and 4.

Investigators: Umesh Korde, Rush Robinett, Ossama Abdelkhalik

Collaborative Research: On Making Wave Energy an Economical and Reliable Power Source for Ocean Measurement Applications

National Science Foundation

Work Plan:
Task 1: Wave-by-wave control and Multi-resonant control
(a-i) Wave-by-Wave Control: Generalize to conversion from relative oscillation in surge, heave, and pitch modes. This step places high expectations on geometry design, because the chosen geometry needs to maximize wave radiation (radiation damping) by relative oscillation in all three modes. Typically, for small axi-symmetric buoys, radiation damping in surge and pitch modes is considerably smaller than that in heave mode. Therefore, greater oscillation excursions are typically required for optimal conversion in these modes. In addition, the power requirements of the wave measurement hardware also need to be included in the daily/annual powver calculations. For the X-band Radar hardware applicable to the up-wave distances of interest to us (on the order of 1000 m), the power consumption is expected to be less than 300 W (average). This could pose a challenge in some wave conditions, but it is likely that the use of multiple modes and optimized geometries will help to provide sufficient usable power for the iFCB application we are pursuing in this work. We plan to extend the current simulations to address these needs.
(a-ii) Geometry Design: New geometry design/utilization approaches to maximize the radiation damping for the 3 relative oscillation modes are being considered. These will be evaluated through detailed simulations in the forthcoming period.
(b) Multi-resonant Control: Current implementations need to be extended to incorporate realistic oscillation constraints. Further extensions to 2-body systems with power capture from relative oscillation are also required, and are planned for the forthcoming period. Finally, the procedure also needs to be extended to investigate multiple-mode conversion (i.e. relative heave, pitch, and surge oscillations).
Task 2: Actuator Design and Energy Storage
Work is planned for the forthcoming period where propose to examine favorably interacting buoy-instrument cage geometries that will minimize the need for large amounts of reactive power to flow through the system. Particular attention will be given to hydrodynamic and mechanical coupling effects and ways to provide negative stiffness through geometry design.
In addition, non-polluting high-lubricity hydraulic fluids will be evaluated through actuator dynamic models over the frequency range of interest.
Task 3: Simulation of Complete System and Wave Tank Testing
This is an important part of the project. The complete system will be simulated following inclusion of multiple-mode relative oscillation conversion and more detailed actuator design. Besides the power requirements of the wave measurement system, all other non-function-critical power needs embedded within the overall system (on-board electronics, etc.) will be included in this simulation.
Wave tank tests are planned as part of this project. Preparations are currently underway to install a wave tank (with flap type absorbing wave makers) capable of providing accurate and repeatable sea states for this project. 1/2 or 1/5 scale models are planned.

Investigator: Umesh Korde

Increasing Ship Power System Capability throught Exergy Control

U.S. Dept. of Defense, Office of Naval Research

The main objective of this effort is to develop an exergy control strategy, applied to a ship medium voltage de (MVDC) grid that exploits exergy flow coupling between multiple subsystems. This work involves: 1) exergy control strategy development and 2) mapping exergy control system performance to ship-relevant metrics. A ship power grid Challenge Problem model will be developed to illustrate and resolve the fundamental gaps of exergy control. The model will also compare and contrast feedforward and feedback exergy control with conventional strategies.

Ship subsystems and mission modules perform energy conversion during their operation resulting in a combination of electricity consumption, heat generation and mechanical work. Mission module thermal management requirements further impact the ship’s electrical grid, for example, via chiller operation. Subsystems often have opportunities for performing an energy storage role during their operation cycle. A ship crane is one example where potential energy is stored in the raised load and can be converted into electrical energy during lowering. Whether subsystem requirements are dominated by electrical, thermal or mechanical functions, they are coupled through energy and information flows, often by the ship’s electrical power grid. Treating each subsystem as a disconnected entity reduces the potential for exploiting their inherent interconnection and likely results in over designed shipboard systems with higher than necessary weight and volume. Realizing the opportunity of coupled subsystem operation requires modeling and control schemes that are unavailable today, but that we believe should require few infrastructure changes. We propose that the design and control of coupled ship subsystems should be based on exergy- the amount of energy available for useful work. A recent study, applied to a room heating system, showed that exergy control increased the overall efficiency by 18%. Since the system was powered electrically, this translated directly to a decrease in the electrical load. The main objective of this effort is to develop an exergy control strategy, applied to a ship medium voltage de (MVDC) grid that exploits exergy flow coupling between multiple subsystems.

An exergy approach to control permits consideration of both mission modules and the platform infrastructure as mixed physics power systems that may act as loads, storage or sources depending on the situation. Instead of separately designed and managed subsystems that satisfy electrical and thermal requirements via static design margins a, multi-physics, unified system-of-systems approach is needed to enable affordable mid-life upgrades as requirements and mission systems evolve over the platform’s lifespan. Being able to translate the benefits of exergy control into savings in mass, volume, energy storage requirements and fuel usage is necessary for making rational design decisions for new ship platforms and for increasing the efficiency of legacy ship systems. Currently, there does not exist an analysis technique to map control system performance into ship-relevant performance metrics. This restricts ship designers from understanding the tradeoffs of adopting advanced control schemes that may exploit subsystem coupling. One of the objectives of this work is to develop a method for extrapolating control system performance into ship-relevant metrics that impact mass, volume, energy storage, and fuel usage.

As described above, there are two main thrusts to this work: (1) exergy control strategy development and (2) mapping exergy control system performance to ship-relevant metrics. We will develop a ship power grid Challenge Problem model that will illustrate the fundamental gaps of exergy control that will be addressed. The model will also be used to compare and contrast feedforward and feedback exergy control with conventional strategies. Techniques for mapping the results of the exergy control to weight, volume, and energy storage requirements will be developed and applied to the Challenge Problem throughout the project.

Investigators: Gordon Parker and Rush Robinett, and Ed Trinklein.

Advanced Controls in Wave Eergy Conversion

Sandia National Labs

Wave energy converter (WEC) control analysis and development within the Water Power Technologies department at Sandia National Laboratory. Design an advanced control strategy for WEC and ongoing research focused on the development and analysis of novel control strategies for WECs.

Investigator: Ossama Abdelkhalik

On Integrating New Capability into Coastal Energy Conversion Systems

National Science Foundation -South Dakota School of Mines & Technology

Analyze and simulate the power capture from arrays of wave energy converters (WECs) with and without the presence of an object. Nonlinear WECs will be analyzed and exploited for more energy capture. For object detection, MTU will develop an estimator. In addition to having a model that detects the presence of an object, the estimator will use that model and account for uncertainties that we have in the model and also measurement errors; in any case we need to know statistical characteristics about these uncertainties and errors. MTU will participate in the WEC array overall design, analysis, modeling and simulations; control design for Design 2, nonlinear modeling and control, and topology optimization.

Investigator: Ossama Abdelkhalik and Mark Vaughn

Wave Energy Conversion (WECs)

WECS are devices with moving elements that are directly activated by the cyclic oscillation of the waves for Ocean wave energy utilization and energy harvesting. Power is extracted by converting the kinetic energy of these displacing parts into electric current; dynamics, control, and hydrodynamics of oscillating bodies and pressure distributions performing as the primary working element of a wave energy converter. Specific recent research has been on small devices capable of integration into measurement and sensing systems in the ocean, as well as shore and ocean based microgrids serving a variety of applications. A focal area of this current research has been new techniques for modeling and control, including novel ways to utilize existing approaches.

Sumit Paudyal

Assistant Professor, Electrical and Computer Engineering
Areas of Interest

  • Distribution Grid Modeling and Optimization
  • Building-to-grid (B2G) and Vehicle-to-grid (V2G) Integration
  • Wide-area Control and Protection, Synchrophasor applications in Smart Grid
    Energy Hub, Distributed Energy Resources, Demand Response, and Demand Dispatch
    Distribution Level Energy Market
  • Advanced Control and Energy Storage Architectures for Microgrids

    Sandia National Laboratory

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

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

    Investigators: Wayne Weaver, Ossama Abdelkhalik

    Modeling and Control Technologies for Near-Term and Long-Term Networked Microgrids

    Argonne National Laboratory

    Microgrids offer attractive options for enhancing energy surety and increasing renewable energy penetration. Within a single microgrid energy generation, storage and utilization is localized. Greater enhancements to energy surety can be accomplished by networking multiple microgrids into a collective which can lead to almost unlimited use of renewable sources, reduction of fossil fuels and self-healing and adaptive systems. However, one pitfall to avoid is losing the surety within the individual microgrids. This produces design and control challenges that are currently unsolved in networked microgrids. To help solve this dilemma, development of analysis methods for design and control of networked microgrids is the general focus of this activity.

    Specific tasks include:
    1. Collaborate and form a coalition with national labs and other microgrid stakeholders to identify key R&D topics in networked microgrids.
    2. Look at near term solutions that can quickly and easily be integrated into existing microgrids,
    3. Determine best practices and optimized control strategies for the ground-up design of future networked microgrids.
    4. Work within the DOE and national lab partnerships to produce the FOA whitepaper on single microgrid systems.
    Tasks 1 through 3 will include microgrid modeling, control and optimizations of single and networked microgrids with focus on achieving DOE 2020 microgrid targets. Specifically, targets include developing commercial scale microgrid systems that reduce outage time, improve reliability and reduce emissions.

    TASK 1: Collaborate and form a coalition with national labs and other microgrid stakeholders to identify key R&D topics in networked microgrids.

    TASK 2: Look at near term solutions that can quickly and easily be integrated into existing microgrids Model development is one of the first steps in the microgrid control design process and incurs trade-offs between fidelity and computational expense. Models used for modelbased control implementation must be real-time while having sufficient accuracy so that feed-forward information can be maximized to achieve specified requirements. The expected outcomes of this study are (1) determination of appropriate time scales for networked microgrid modeling (2) a MATLAB/ Simulink reduced order model library of networked microgrid components and (3) lab scale hardware validation of networked microgrid models. These model libraries will then be used to construct models and develop control and optimization algorithms of current microgrid systems and equipment.

    Task 3: Determine best practices and optimized control strategies for the ground-up design of future networked microgrids. Demonstrating robust networked microgrids will require system-level optimization. This includes both its physical and control system designs. This task will build upon the models and optimizations achieved in task 2 applied to the design of future networked microgrids. The expected outcomes of this study are (1) energy-optimal design methods suitable for networked microgrid design and control of future long-term application architectures and (2) integration of these strategies with the microgrid model environment and bench scale hardware described in task 2.

    Investigators: Wayne Weaver, Gordon Parker

    Agent Based Control with Application to Microgrids with High Penetration Renewables

    Sandia National Laboratory

    Prior Work is leveraged; MTU has developed and demonstrated through simulation a prototype multiagent system that coordinates the life cycle operations of a microgrid collective composed of independent electric power sources, loads, and storage. MTU has performed simulations of DC micro grids of varying compositions and characteristics. MTU has analyzed simulation results, and developed candidate architectures and protocols for agent-based microgrid controls.

    Execution of this project will further technical innovations associated with multi-agent software controlling microgrid collectives. The microgrid control algorithms for microgrid collectives will be developed and refined using Michigan Tech microgrid models and simulations validated against the MTU test bench. The algorithms will then be applied to SNL hardware models in simulation and finally against the SNL hardware test bed.

    Agent-based control systems will be further developed by MTU in Matlab/Simulink blocks, tested, and refined through simulations. Once control performance objectives have been achieved, the systems will be ported to the MTU situated multi-agent system (MAS) and supporting servo loop controllers on the MTU test bench for evaluation. New Matlab simulations will be tailored and tuned to control the SNL test bed models and verified in simulation. SNL will re-apply the MTU MAS to the physical SNL test bed. SNL will collaborate with MTU on implementation and validation. Collaborative efforts will ensure that SNL attains the technology necessary to achieve the final project objectives for the SNL test bed

    Required Research Innovations:
    1. Identify control system performance issues between agent informatics and DC nonlinear controls. Since global computations require input from various points, processor speed and network bandwidth may dominate the performance of collaborative protocols that rely on nonlinear control approaches. Research must identify the computational and communication limits for porting nonlinear controls to agent control layers.
    2. Investigate scaling properties for controls applied to increasing the number of interconnected DC microgrids. Trading power between microgrids may not be feasible due to geographical distances or communication time latencies. There may also be thresholds identified for collaboration considerations, such as partnering with 10 microgrids or less, due to the global computation requirements. Control scaling results should describe the appropriate considerations at various time scales (seconds, minutes, hours, and days). Additional considerations for scalability may include increasing the number of components within a single microgrid and increasing the variety of components within the microgrid.

    Investigators: Gordon Parker, Wayne Weaver, Steven Goldsmith