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.

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

Unstable and Pulse Load Control Designs for Naval Electrical Systems

Sandia National Labs

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.
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

Microgrid Modeling and Optimization for High Penetration Renewables Integration

Sandia National Laboratory

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

CPS: Breakthrough: Toward Revolutionary Algorithms for Cyber-Physical Systems Architecture Optimization

National Science Foundation

Design optimization of cyber-physical systems (CPS) includes optimizing the system architecture (topology) in addition to the system variables. Optimizing the system architecture renders the dimension of the design space variable (the number of design variables to be optimized is a variable.) This class of Variable-Size Design Space (VSDS) optimization problems arises in many CPS applications including (1) microgrid design, (2) automated construction, (2) optimal grouping, and (3) space mission design optimization.

Evolutionary Algorithms (EAs) present a paradigm for statistical inference that implements a simplified computational model of the mechanisms embedded in natural evolution, with potential to solve this problem. However, existing EAs cannot optimize among solutions of different architectures because of the inherent strategy for coding the variables in EAs. Existing EAs resembles natural evolution in which a given architecture can evolve by improving the state of its variables but cannot be revolutionized. Inspired by the concept of hidden genes in biology, this project investigates revolutionary optimization algorithms that can optimize among different solution architectures and autonomously develop new architectures that might not be known a priori, yet are more fit solution architectures. Efficacy of the new algorithms for CPS is evaluated in the context of space mission design optimization.

Intellectual Merit:
There is an increasing demand in the scientific community for autonomous design optimization tools that can revolutionize systems designs and capabilities. Most existing optimization algorithms can only search for optimal solutions in a fixed-size design space; and hence they cannot be used for solution architecture optimization. Few existing algorithms can search for optimal solutions in VSDS problems; however these are problem-specific algorithms and cannot be used as a general framework for VSDS optimization. This project investigates the novel concept of hidden genes in coding the variables in evolutionary algorithms so that the resulting algorithms can be used for optimizing VSDS problems. The key innovation in these new algorithms is the new coding strategies. In addition, in this project, the standard operations in EAs will be replaced by new operations that are defined to enable revolutionizing a current population of solution architectures using the new coding strategy. The Pl’s recent research results, in the context of space mission design optimization, demonstrate that the hidden genes optimization algorithms can search for optimal solutions among different solution architectures, revolutionize an initial population of solutions, and construct new solution architectures that are more fit than the initial population solutions.

Investigator: Ossama Abdelkhalik

Control and Optimization of Microgrids Research


Optimal Control Surface

Optimal Control Surface

Researchers are focused on the control of individual energy load, source, and storage energy points as building blocks in a microgrid. This technology enables operation of a stable and optimized system through an agent based approach of the power electronics energy conversion points, enabling a robust and re-configurable system that does not rely on central control or communication.

Active Research Projects


Research is ongoing to develop new modeling, simulation, control and optimization tools for rational decisions for the best use of microgids with high penetrations renewable and dispatchable loads:

  • Rapid deployment of survivable, flexible, reconfigurable, stable, smart microgrids for military forward operating bases and humanitarian missions.
  • Transformation of U.S. military installations to be net neutral with safe, reliable power generation.
  • Training engineers who can adapt to new interdisciplinary challenges associated with delivering secure energy for both civilian and military applications.
AIM Microgrid Strategy

AIM Microgrid Strategy

Control and Optimization

Control and Optimization