Meta-Stability of Pulsed Load Microgrids

Sandia National Labs

Statement of Work
NAVSEA/ Military microgrids
Using the HSSPFC (Hamiltonian Surface Shaping and Power Flow Control) derived MATLAB/Simulink
tools develop a Reduced Order Model (ROM) to support control designs for pulse load applications for i)
up to (3) key ship modes of a ship power system operation and ii) a stable and unstable modes of
switching operations as a part of a survivability scenario.
Deliverables Tasks:
1. Provide ROM of meta-stable ship system.
2. Analyses and control design (feedforward and feedback) of meta-stable system.
3. Analyses and control design for multi-pulse load systems.
4. Analyses of the effects and potential benefits of non-linear magnetics in meta-stable system.
5. Develop and perform hardware testing on metastable laboratory benchtop system.
6. Develop networked Microgrid model for KIER/LUXCO scenario

Investigator: Wayne Weaver

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.

Introduction
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.

Autonomous Microgrids: Theory, Control, Flexibility and Scalability

U.S. Dept of Defense Office of Naval Research

Project Description and Research Objectives:
From large scale electric power grids and microgrids down to small scale electronics, power networks are typically deployed using a fixed infrastructure architecture that cannot expand or contract without significant human intervention. Mobile, monolithic power systems exist but are also not readily scalable to exploit surrounding power sources and storage devices. However, if a power network is constructed from physically independent and autonomous building blocks, then it would be infinitely reconfigurable and adaptable to changing needs and environments. The aim of this project is to integrate vehicle robotics with intelligent power electronics to create self-organizing, ad-hoc, hybrid AC/DC microgrids. The main benefits of this system would be the establishment and operation of an electrical power networks independent of human interaction and can adapt to changing environments, resource and mission. In the context of U.S. Naval platforms, this autonomous electrical network could be used in land, air or sea systems.

The focus of this work will be on land based autonomous microgrid systems, but the fundamental theory developed may be applicable to air and sea based systems as well. Investigators at Michigan Technological University have developed initial hardware and testbeds to study this problem. However, a more detailed theoretical foundation is needed to be developed to apply autonomous microgrids to a wide variety of operational scenarios with various resources. It is also hypothesized that given the flexibility of this approach that it could be equally applied over a vast scale of energy assets. A microgrid that grows in situ from 10 s to 100 s to 1000 s of energy assets can be equally managed, controlled and optimized through the highly scalable approach proposed in this project.

These applications are examples of the critical need for autonomous mobile microgrid capable of operating in highly dynamic and potentially hazardous environments. Our overall goal is to create a scalable architecture to develop a system that accounts for uncertainty in predictions and disturbances, is redundant, requires minimal communication between agents, provides real-time guarantees on the performance of path planning, and reaches the targets while making electrical connections. Such architecture provide a coherent layout for the interconnection between different disciplines on this topic and minimizes the integration concerns for future developments.

Description of the Proposed Work:
• Microgrid Planning and Control
• Microgrid Topology and Optimization
• Electrical Components and Power Flow
• Game-Theoretic Control
• Physical Autonomous Positioning and Connections

Investigator: Wayne Weaver, Rush Robinett and Nina Mahmoudian

Umesh Korde


Biography
Umesh Korde has been active in the area of ocean wave energy utilization since 1982. He has worked on several aspects of the problem, though his research over the last three decades has primarily been concerned with the dynamics, control, and hydrodynamics of oscillating bodies and pressure distributions performing as the primary working element of a wave energy converter. Of particular interest in the last few years have been 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 his current research has been new techniques for modeling and control, including novel ways to utilize existing approaches.

Dr. Korde has also worked on the dynamics and control of flexible bodies including lightweight membranes, for space applications such as steering and shaping of laser beams, tunable passive damping of lightweight structures, and self-healing of structures using focused stress waves. Dr. Korde serves as an associate editor for the journal J Ocean Engineering and Marine Energy (Springer), and is a Fellow of the American Society of Mechanical Engineers.

Research Specialties

  • Dynamics and control: floating body hydrodynamics, hydrodynamic modeling of buoys, cables;
  • Modeling and control of flexible and smart structures;
  • Wave energy converters, near-optimal control in the time domain;
  • Adaptive and nonlinear control of floating bodies;
  • Low-dissipation actuator and mechanism development, development of new detection and sensing modalities;
  • Deterministic wave prediction;
  • Control of ship-board systems
  • Wave powered microgrids
  • 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.

    “CRISP Type 2: Revolution through Evolution: A Controls Approach to Improve How Society Interacts with Electricity.”

    National Science Foundation

    This CRISP project addresses the challenges associated with the rapid evolution of the electricity grid to a highly distributed infrastructure. The keystone of this research is the transformation of power distribution feeders, from relatively passive channels for delivering electricity to customers, to distribution microgrids, entities that actively manage local production, storage and use of electricity, with participation from individual customers. Distribution microgrids combine the advantages of the traditional electricity grid with the advantages of emerging distributed technologies, including the ability to produce and use power locally in the event of grid outages. The project will result in a unified model that incorporates key aspects of power generation and delivery, information flow, market design and human behavior. The model predictions can be used by policymakers to guide a transition to clean energy via distribution microgrids. The expectation is to enable at least 50% of electric power to come from renewable resources. This cannot be done with either the traditional grid, due to its limited capacity to accommodate intermittent renewable power sources, or with fully decentralized approaches, which would not be affordable for most utility customers.

    This project addresses many socio-technological gaps necessary to translate from research discovery to commercial applications. To date, there is no theoretical framework to ensure system stability as renewable energy routed through power electronics replaces traditional rotating machinery. To achieve an optimal mix of storage performance and information bandwidth and to design nonlinear controllers, we will use Hamiltonian Surface Shaping Power Flow Control theory. We will study methods to detect malicious tampering with information flows. The complex interaction of intermittent resources, human behavior and market structures will be modeled in an agent-based simulation. System inputs will be provided by utility and meteorological data, and by behavioral models that incorporate information obtained by surveys, interviews and metering data. Emergent system dynamics will be abstracted and studied using dynamical complex network theory, to explore stability limits as a function of human behavior and market design. Finally, the effect of enhanced controllability of distribution systems on the robustness of large energy-information-social networks will be analyzed using interdependent Markov-chain models. Graduate students involved in this program will be exposed to a unique combination of skills from engineering, data analysis and social sciences; such cross-disciplinary training will prepare them for leadership roles in the emerging energy economy of tomorrow.

    Investigators: Laura Brown, Chee-Wooi Ten, Wayne Weaver

    Revolution through Evolution: A Controls Approach to Improve How Society Interacts with Electricity

    September 20, 2015

    Laura Brown (PI) received a $699,796 NSF grant. The title of the project is “CRISP Type 2: Revolution through Evolution: A Controls Approach to Improve How Society Interacts with Electricity.” The co-principal investigators of this project are Chee-Wooi Ten (ECE) and Wayne Weaver (ECE). This is a three-year collaborative project with four other institutions with a total budget of $2,499,801. The project addresses the rapid evolution of the electricity grid, from one based on few centralized generators providing power to millions of users to one where many distributed energy resources. The keystone of this research is the transformation of power distribution feeders, from relatively passive channels that deliver electricity from the transmission grid to customers, to distribution microgrids, highly intelligent entities that actively manage production, storage and use of electricity.

     

     

    Kuilin Zhang

    Zhang-pers

    Dr. Zhang received his Ph.D. degree in Transportation Systems Analysis and Planning from the Department of Civil and Environmental Engineering at Northwestern University in December 2009.  After working as a Postdoctoral Fellow in the Transportation Center at Northwestern, he joined the Energy Systems Division at Argonne National Laboratory as a Postdoctoral Appointee in November 2010. He is a member of Transportation Research Board (TRB) standing committees of Transportation Network Modeling (ADB30) and Freight Transportation Planning and Logistics (AT015). He is also a member of INFORMS.

    Research Interests

    • Vehicle Network Microgrids
    • Dynamic network equilibrium and optimization
    • Modeling and simulation of large-scale complex systems
    • Multimodal transportation systems analysis
    • Freight transportation and logistics systems
    • Data-driven travel behavior analysis
    • Impact of plug-in electric vehicles to smart grid and transportation network systems
    • Vehicle systems dynamics and fuel-efficient driving behavior

    Advanced Control and Energy Storage Architectures for Microgrids

    Sandia National Laboratory

    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.

    Investigators: Wayne Weaver, Ossama Abdelkhalik

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

    Argonne National Laboratory

    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 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