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

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

Distributed and Decentralized Control of Aircraft Energy Systems

U.S. Dept of Defense, Air Force Research Lab -InfoSciTex Corp (AFRL)

Aircraft energy system components, including sources, loads and distribution, have multiple commitments and responsibilities. Often much of the system is comprised of power electronic converters for sources, loads, and energy storage (chemical, mechanical and thermal). For example, a point of load power converter has the commitment to serve the energy needs of the end load. However, if the power system collapses, the needs of the load cannot be met. Therefore, it is also in the interest of the conve1ter to contribute to the global stability of the power system by reducing nonlinear dynamics and incremental negative impedance. One method to mitigate the destabilizing effects of constant power loads is the power buffer concept. A power buffer is a device that mitigates a destabilizing event by presenting controlled impedance to the supply during the transient while local energy is used to maintain constant power to the load until the system can recover. A power buffer may include additional hardware, or may merely be a modification of the controls of an existing active front end power converter. However to date the use of a load as an energy asset in a power buffer has been limited to traditional chemical (capacitor and battery) storage devices in the electrical network. Next generation aircraft may have a broad range of potential assets in the form of loads, including inertial spinning devices and thermal systems, which could be utilized in the overall energy strategy.

Research with AFRL researchers to investigate distributed and decentralized control of aircraft energy systems. This effort will include using models and simulations to formulate decentralized control and study the effects. Specifically,
• Develop and document a mathematical model of the aircraft energy systems including thermal and inertial loads.
• Formulate a decentralized power buffer control including inertial and thermal loads as energy storage assets.
• Develop and document nume1ic simulation models in MATLAB/Simulink and/or
• Modelica. The models will include aircraft system and controls.
• Validate theoretic results through simulation under stressing scenarios.

Investigator: Wayne Weaver

Unstable and Pulse Load Control Designs for Naval Electrical Systems

Sandia National Labs

NAVSEA
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.

ElectroMagnetic (EM) Coupling-Penetration Measurement Standard
Testing and simulation facilities have various methods for test readiness activities and post-test instrumentation and sensors performance verification. Such a canonical standard has been developed but has not been used or re-verified in recent years. Using the mathematical model of the canonical measurement standard previously documented in an EM Sand report, verify both analytical and computational analyses and propose experimental validation with analytical model.

Investigator: Wayne Weaver

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

Agent Based Control with Application to Microgrids with High Penetration Renewables

Sandia National Laboratory

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.

Investigators: Gordon Parker, Wayne Weaver, Steven Goldsmith

Microgrid Modeling and Optimization for High Penetration Renewables Integration

Sandia National Laboratory

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.

Investigators: Gordon Parker, Wayne Weaver

Wayne Weaver

image25785-persWayne W. Weaver received a BS in Electrical Engineering and a BS in Mechanical Engineering from GMI Engineering & Management Institute in 1997, and an MS and PhD in Electrical Engineering from the University of Illinois at Urbana–Champaign. Weaver was a research and design engineer at Caterpillar Inc., in Peoria, Illinois, from 1997 to 2003. From 2006 to 2008, he also worked as a researcher at the US Army Corp of Engineers, Engineering Research and Development Center (ERDC), Construction Engineering Research Lab (CERL), in Champaign, Illinois, on distributed and renewable-energy technology research. Weaver is a registered professional engineer in Illinois. His research interests include power electronics, electric machine drives, electric and hybrid-electric vehicles, and non-linear and optimal control.

Areas of Interest

  • Power electronics systems
  • Microgrids
  • Non-linear and game theoretic controls
  • Distributed energy resources
  • Electric drives and machinery

Interconnected and Agile Microgrids Research

Overview

Interconnected MicrogridA microgrid may consist of many interconnected energy assets to improve reliability efficiency. Two or more microgrids can also interconnect to share resources to further improve reliability and efficiency. The scalable microgrid project is aimed at creating a hardware test-bench capable of developing and testing technologies for control and optimization in large numbers of interconnected microgrids. It is also aimed at studying how these technologies can scale up to high and higher numbers of interconnected microgrids. Development of power conversion nodes that adapt and connect to an expanding interconnected microgrid structure to create a large, decentralized power distribution network that can adapt to changing resources and demands.

Active Research Projects

Applications

  • Communication protocols
  • High penetration renewable
  • Agile grid controls
  • Control of interconnected microgrids
  • Scale model explorations

Interconnected Flowchart

Agile DC Microgrid Testbed Architecture

Agile DC Microgrid Testbed Architecture

MTU - Scalable Interconnected Microgrid Testbed

MTU – Scalable Interconnected Microgrid Testbed
The light-weight agile DC microgrid testbed will be expanded to dozens of interconnected microgrids.

Interconnected Applications