Agile Interconnected Microgrids (AIM)

1. To prepare for the next phase of controller-in-the-loop, an additional communication mechanism between Opal-RT and CIP.io will be explored. Currently, the Opal-RT simulator can communicate with CIP.io through Modbus TCP/IP. To enable the Opal-RT simulator directly communicating with an MQTI broker, the implementation of an MQTI client in Opal-RT will be developed.

Deliverables: Fully functional, tested and debugged Opal-RT MQTI communication blocks for interfacing anMQTI broker with an Opal-RT simulation (publish and subscribe).

1. A method for obtaining instantaneous wave surface elevation information on a wave-by wave basis using a low-cost X-band Radar (the state of the art, as represented by the commercially available WaMOS system is optimized to provide spectral information.
2. A method for providing constrained near-optimal wave-by-wave control for maximizing the energy conversion by small wave energy converters.
3. Although the focus of the proposed research is wave energy converter technology, the results of this work are expected to find application in other forthcoming Navy developments. Wave-by-wave surface elevation prediction and near-optimal power absorption techniques demonstrated in this effort can be extended to facilitate critical mid-sea shipboard operations such as helicopter/ aircraft landing, cargo handling, etc. The techniques demonstrated as part of this research will also provide technology to enhance and optimize seakeeping characteristics of Navy ocean platforms.

A continuation of a previous project:

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.

• Microgrid Planning and Control
• Microgrid Topology and Optimization
• Electrical Components and Power Flow
• Game-Theoretic Control
• Physical Autonomous Positioning and Connections

Collaborate with Mohammadia School of Engineering (EMI), Rabat, Morocco within the framework of the Project: "MicroCSPs Contribution on the Management of an Electrical Grid Including Renewable Energy Sources."

Statement of Work:

• Support the Design of an intelligent monitoring system for load balancing of a network based on a CSP with storage and photovoltaic panels.
• Help and support in the study of the integration of CSP in the Moroccan grid.
• Support the Economic Survey of the implementation of the CSP in the Moroccan power grid in the short term.
• Support the calculations of the cost of energy generation by the CSP.
• Support the calculations of an appropriate cost price PPA (Power Purchase Agreement).
• Transfer of skills where desired.

Overview:

Success of numerous long-term robotic network missions in space, air, ground, and water is measured by the ability of the robots to operate for extended time in highly dynamic and potentially hazardous operating environments. The proposed work responds to the urgency for development of innovative mobile power distribution systems that lower deployment and operating costs, while simultaneously increasing mission efficiency, and supporting the network's need to be responsive to changing physical conditions. The overall CAREER goal is to develop a power distribution system that responds to individual robot needs, as well as, overall robotic network goals to guarantee persistence of long-term operation in uncertain and unstructured environments.

The proposed work is informed by the hypothesis that network persistence hinges on the ability to establish stable energy transfer cycles necessary to accomplish coverage specifications, while simultaneously dealing with physical and environmental constraints. To test this hypothesis and as an example of such a system, this work will focus on creating a reliable autonomous recharging system for autonomous underwater vehicles (AUVs) that enables continuous real-time marine observation and data collection in the presence of continuously changing underwater environmental circumstances. The key challenges are two-fold: there are fundamental hardware challenges connected to energy transfer in the harsh underwater environment, but more importantly there are basic network science needs that are novel to a mobile power network. The specific research thrusts for this CAREER work include: 1) Task and Energy Routing Scheduling for Persistent Mission Planning. 2) Efficient Network Path Planning and Coordination to Accomplish Persistent Mission Plan. 3) Experimental Validation through Test-bed Development. 4) Design-based, Research-integrated Education Plan for Broadening Underrepresented Participation in STEM.

Intellectual Merit:

This project builds a roadmap to achieve robust continuous marine autonomy that advances unmanned marine systems ability to perform autonomous long-term missions. More specifically the proposed work will provide: 1) resource based task scheduling, 2) path planning formation for mission and charging, and 3) integration tools for testing. Expected outcomes will overcome the current challenge of significant interruptions during underwater missions due to battery limitations and recharging needs. Through this CAREER proposal, the Pl will establish the theoretical, computational, and experimental foundation for mobile power delivery and onsite recharging capability for autonomous underwater vehicles (AUVs). The developed power distribution system will be able to reconfigure itself depending on the scope of the mission, as well as, the energy consumption needs of the network, the number of operational AUVs and required operation time, recharging specifications, communication and localization means, and environmental variables.

Such a system will play a vital role in real-time controlled applications across multiple disciplines, such as: sensor networks, robotics, and transportation systems where limited power resources and unknown environmental dynamics pose major constraints. All developed tools will be suited for the capabilities of not only low-cost AUVs with limited sensing and computational resources, but also high-tech AUVs with state of the art sensor packages.

Broader Impacts:

The developed active power distribution system focuses on underwater scenarios, but will be transferrable to space, air, and ground missions as well. This type of feasible power distribution solution can be used to optimize: 1) immediate high-risk disaster recovery missions like the Fukushima nuclear plant accident; 2) search missions that require vast underwater inspection and detection like the Malaysia MH370 passenger aircraft; and 3) long-term space observation and monitoring like that of the lunar skylight or Europa space mission. The findings from this project will be disseminated through publications, software sharing, and technology commercialization. The project provides interdisciplinary training opportunities for graduate, undergraduate, and pre-college students, including those from underrepresented groups. Research activities will be integrated with education through curriculum development, outreach and improved GUPPIE design.

Problem Statement

EMT's current cutoff blade is controlled by a Bosch indexer, which provides "cam" profile programming to allow for varying cut lengths and feed rates. There is uncertainty that a given profile will provide optimal performance for all cut lengths and feed rates.

1. To reduce design and process time, an analytical model based approach will be developed to determine the required machine performance for varying cut lengths and feed rates. The machine model will include cutter inertia, position, velocity and acceleration, indexer "cam" profiles, constant velocity zone, and determine motor torque. Other variables could be added to improve model fidelity once the machine dynamics are better understood. The current cutter design will provide a starting point for the analytical model.

EMT must achieve web speeds of at least 700 Ft/min to remain competitive with the goal of 1000 Ft/min. Therefore, the cutter design and efficiency must be improved. A key part of the design is understanding cutting forces for different materials and feed rates. By instrumenting the current design, these forces can be measured experimentally.

a. MTU would assist EMT in setting up strain gage testing to measure the forces. This would include recommending the equipment & process that would provide the most accurate & useful data.

b. EMT would conduct the test in accordance to MTU direction.

Assistance in developing a new cutter blade design to allow for faster more efficient performance based on force finding in 2 above.

a. MTU will provide analysis necessary to include best material, lowest inertia, best cam profiling. This includes considerations for vibration, bearing systems, stiffness, & any other criteria that is critical to this design.

Design/Experimental Considerations

EMT has been successful in designing and manufacturing the paper cutters with web speeds below 600 Ft/min. To determine if MTU can assist EMT reach the 1,000 Ft/min speeds, we propose the following in the first phase of the proposal.

• Strain gage the shaft and measure the stress for various cutting speeds and material thickness. The preliminary analysis indicates values of <10 microstrain for a 50 lbf applied at the shaft center, this is approaching the limit of a strain gage.
• Measure the drive motor position, velocity, acceleration and torque for several of the cam profiles.
• Compare the measured dynamic values to the analytical values predicted.

Background

A new multi-year effort has been launched by the Department of Energy to validate the extent to which control strategies can increase the power produced by resonant WEC devices. A large number of theoretical studies have shown promising results in the additional energy that can be captured through control of the power conversion chains of resonant WEC devices.

However, most of the previous work has been completed on highly idealized systems and there is little to no validation work. This program will specifically target controls development for nonlinear, multi-degree of freedom WEC devices. Multiple control strategies will be developed and the efficacy of the strategies will be compared within the "metric matrix."

Objective: The purpose of this contract is to provide the labor to develop and implement custom control strategies for a specified WEC device.

Scope of Work

Michigan Technological University {MTU} will provide optimization expertise {Dynamic Programming, pseudo-spectral, shape optimization, others) to support MTPA-FF {mid-targeting phase and amplitude-feedforward) designs and analysis specific to the performance model WEC. This will include numerical simulations specific to the metric matrix requirements. In addition, MTU will provide expertise and support for feedforward real-time implementation and investigations.

Deliverables: Software codes, report, and a presentation

Justification Statement

Ossama Abdelkhalik is a well-known expert in optimization theory and implementation for spacecraft trajectory orbit designs. He has recently entered the renewable energy field with a specific interest in wave energy conversion power optimization using optimization techniques; such as dynamic programming, pseudo-spectral, novel shape optimization, and others. His specialized optimization skill-set and expertise will be critical in developing feedforward algorithms for design and real-time implementation. Ossama's publication record shows his depth in numerous trajectory optimization research projects in spacecraft navigation, guidance and control.

Overview

The existing communication layer for Vehicle to Grid (V2G) operations has sufficient throughput and capabilities for basic connectivity, but may not have enough for tasks such as operating military vehicle systems remotely. They cyber security approach to V2G operations has had some development in industry; however military vehicles demand more scrutiny from a cyber security perspective.

Vehicle-to-Vehicle (V2V) resource sharing would enable a greatly expanded flexibility for utilization of assets for forward operating bases (FOB). Consider a FOB with a variety of vehicle assets, each with different levels of functionality. The ability to daisy-chain the vehicle assets together (including partially disabled vehicles), have the vehicles automatically determine their net capability and then share resources to accomplish a common goal (force protection for example), would enable a level of capability not currently available.

Specific Tasks: Vehicle-to-Grid Simulation, Connection Protocol Assessment, Connection Protocol Development, Throughput Assessment, and Simulation Studies.

Background:

The purpose of this research is to be able to predict the natural frequencies associated with the cavity modes of tires mounted oil wheels. Ford has experienced difficulties in the past when these natural frequencies have aligned themselves with the natural frequencies of other vehicle components and hence caused an objectionable noise in the vehicle. The goal of this project is to provide the tools to Ford to allow them to make decisions in advance of mounting tire/wheel combinations on vehicles by estimating what these tire cavity natural frequencies will be. It is anticipated that to fully understand the frequencies of the tire cavity modes will require a combination of modeling and experimental testing.

Approach:

To meet these objectives start with a finite element model of the cavity of a tire mounted on a wheel. The initial model includes effectively a rigid tire and wheel. This model is not a coupled vibro-acoustic model but instead just an estimate the natural frequencies of the tire cavity itself with zero velocity boundary conditions. This model will be modified to simulate the change in the tire cavity shape when the wheel is loaded in a static configuration. The results of the loaded and unloaded models are compared to help to understand the effects of changing the tire cavity's shape. If the results of this model show promise, simpler modeling methods will be explored.

The next step in the modeling process includes a flexible tire and wheel and be a fully coupled vibro-acoustic model. In this model, the wheel will have actual material properties assigned while the tire will be modeled as an isotropic material with estimated material properties that will be iterated to achieve natural frequencies of the coupled system similar to those measured in the laboratory of a stationary tire. This model will then be modified to a statically loaded condition and the model re-run to observe the effects of loading the tire on the natural frequencies.

Models will be validated experimentally by testing a tire/wheel assembly in the laboratory at MTU. Testing will be done in the both the unloaded and the statically loaded case by exciting both the wheel and the tire patch in separate tests. Natural frequencies will be estimated from all tests and used to validate the models. Models and testing will be performed on several different tire/wheel combinations to assess the ability to estimate the natural frequencies of different configurations. Based on the results of the modeling and testing the final deliverable from this project will be the simplest approach that can be determined for estimating the natural frequencies of a tire cavity based on a minimum set of information or data.

Introduction

Calibration is an important step in creating a physical model that can be used for predictive control system design. IMECO has a MATLAB/Simulink model of their Steering Gear Actuation System (SGAS). It contains parameters that can be classified as known (e.g. control system gains), known with uncertainty (e.g. mass properties) and unknown (e.g. damping coefficients). IMECO has also obtained experimental data that can be used to run the model and compare model outputs to sensor measurements. An optimization-based method for identifying the model parameters is needed to help automate the calibration process.

Statement of Work

Using the model and experimental data supplied by IMECO, calibrate the model using advanced numerical optimization strategies. Separate calibration parameters for several data sets will be developed in addition to a single calibration across multiple data sets. While the calibration is of primary importance, development of a methodology for automating the process will also be developed.

Introduction

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 model-based 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.

Abstract

Future microgrids are envisioned having a large renewable energy penetration. While this feature is attractive it also produces design and control challenges that are currently unsolved. To help solve this dilemma, development of analysis methods for design and control of microgrids with high renewable penetration is the general focus of this activity. The specific foci are (1) reduced order microgrid modeling and (2) optimization strategies to facilitate improved design and control. This will be investigated over a multi-year process that will include simplified microgrid modeling and control, single microgrid modeling and control, collective microgrid modeling and control, and microgrid (single and collective) testing and validation.

Microgrid Reduced Order Modeling (ROM)

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 model-based control implementation must be real-time while having sufficient accuracy so that feedforward information can be maximized to achieve specified requirements. The expected outcomes of this study are (1) quantification of model uncertainty as a function of the assumptions with particular interest given to reduced order models (2) determination of appropriate time scales for reduced order modeling and (3) a MATLAB / Simulink reduced order model library of microgrid components. Contrasting different microgrid reduced order modeling approaches and simulation results that demonstrate the reduced order microgrid simulation.

Microgrid Optimization

Demonstrating microgrids with robust and high renewable penetration requires system-level extremization. This includes both its physical and control system designs. The expected outcomes of this study are (1) energy-optimal design methods suitable for microgrid design and control and (2) integration of these strategies with the microgrid reduced order model environment described above. How energy-optimal design can be exploited for microgrid design and control.

Overview

This project plan (APP) describes the second year of the four year program for distributed agent-based management of agile microgrids. In year 1, the team has evaluated modeling and forecasting techniques for renewable energy sources as well as developed relevant case studies. In year 2 the team will further develop the models and forecasting techniques as well as begin implementation of simulations and hardware test cases.

Topic area 1: Core electrical power networks and control technology research with the focus on modeling of networks and control methods, conceptual hardware evaluation and analysis and identification of Army modes of operation.

Topic Area 2: Modeling and optimization of tactical energy networks control systems with a focus on short term load forecasting and simulation.

Topic area 3: Research focused on machine learning, long-term prediction and forecasting of loads. Research into optimization and distributed control of power distribution systems.

Abstract

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.

Objective

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.

Scope

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.

Overview

Consult on advanced control and energy storage architectures for microgrids.

Tasks:

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.

Tasks:

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.