Publications

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Laboratory Directed Research and Design (LDRD) originating technologies are being developed to address challenges inherent to highly stochastic energy sources and loads, to conceivably satisfy the electrical energy needs of national/international power systems. The Enabling Secure, Scalable Microgrids with High Penetration Renewables Grand Challenge LDRD (FY11-FY13) aimed to develop a novel intelligent grid architecture, Secure Scalable Microgrid (SSM), based on closed loop controls and an agent-based architecture supporting intelligent power flow control. The approach was to enable self-healing, self-adapting, self-organizing architectures and allow a trade-off between storage in the grid versus information flow to control generation sources, power distribution, and where necessary, loads. L

To achieve high performance operation of micro-grids that contain stochastic sources and loads is a challenge that will impact cost and complexity. Developing alternative methods for controlling and analyzing these systems will provide insight into tradeoffs that can be made during the design phase. This paper presents a design methodology, based on Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) [1] for a hierarchical control scheme that regulates renewable energy sources and energy storage in a DC micro-grid. Recent literature has indicated that there exists a trade-off in information and power flow and that intelligent, coordinated control of power flow in a microgrid system can modify energy storage hardware requirements. Two scenarios are considered; i) simple two stochastic source with variable load renewable DC Microgrid example and ii) a three zone electric ship with DC Microgrid and varying pulse load profiles. © 2014 IEEE.

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In this paper, 1 the equations are formulated to model the dynamic behavior of a wind turbine coupled to the electric grid through a Unified Power Flow Controller (UPFC). This concept is demonstrated in order to treat wind plants more as a controllable energy source rather than a negative load, which is the current trend among renewable energy systems. The results of this research include the determination of the required performance of a proposed Flexible AC Transmission System (FACTS)/storage device, such as a UPFC, to enable the maximum power output of a wind turbine while meeting the constraints of the bulk electric system. The UPFC is required to operate as both a generator and load (energy storage) on the power system in this design. An illustrative example demonstrates this concept applied to a UPFC with a 1MW fixed speed wind turbine. The wind turbine is operated with multiple wind profiles for below-rated wind power conditions. The wind turbine is connected in series through a UPFC to the infinite bus. Numerical simulation cases are reviewed that best demonstrate the stability and performance of a UPFC as applied to a renewable energy system. © 2012 IEEE.

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In this paper, the swing equations for renewable generators are formulated as a natural Hamiltonian system with externally applied non-conservative forces. A two-step process referred to as Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) is used to analyze and design feedback controllers for the renewable generator system. The results of this research include the determination of the required performance of a proposed Flexible AC Transmission System (FACTS)/storage device, such as a Unified Power Flow Controller (UPFC), to enable the maximum power output of a wind turbine while meeting the power system constraints on frequency and phase. The UPFC is required to operate as both a generator and load (energy storage) on the power system in this design. Necessary and sufficient conditions for stability of renewable generator systems are determined based on the concepts of Hamiltonian systems, power flow, exergy (the maximum work that can be extracted from an energy flow) rate, and entropy rate. An illustrative example demonstrates this HSSPFC methodology. It includes a 600 kW wind turbine, variable speed variable pitch configuration. The wind turbine is operated with a turbulent wind profile for below-rated wind power conditions. The wind turbine is connected in series through a UPFC to the infinite bus. Numerical simulation cases are reviewed that best demonstrate the stability and performance of HSSPFC as applied to a renewable energy system. © 2011 IEEE.

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The swing equations for renewable generators connected to the grid are developed and a wind turbine is used as an example. The swing equations for the renewable generators are formulated as a natural Hamiltonian system with externally applied non-conservative forces. A two-step process referred to as Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) is used to analyze and design feedback controllers for the renewable generators system. This formulation extends previous results on the analytical verification of the Potential Energy Boundary Surface (PEBS) method to nonlinear control analysis and design and justifies the decomposition of the system into conservative and non-conservative systems to enable a two-step, serial analysis and design procedure. The first step is to analyze the system as a conservative natural Hamiltonian system with no externally applied non-conservative forces. The Hamiltonian surface of the swing equations is related to the Equal-Area Criterion and the PEBS method to formulate the nonlinear transient stability problem. This formulation demonstrates the effectiveness of proportional feedback control to expand the stability region. The second step is to analyze the system as natural Hamiltonian system with externally applied non-conservative forces. The time derivative of the Hamiltonian produces the work/rate (power flow) equations which is used to ensure balanced power flows from the renewable generators to the loads. The Second Law of Thermodynamics is applied to the power flow equations to determine the stability boundaries (limit cycles) of the renewable generators system and enable design of feedback controllers that meet stability requirements while maximizing the power generation and flow to the load. Necessary and sufficient conditions for stability of renewable generators systems are determined based on the concepts of Hamiltonian systems, power flow, exergy (the maximum work that can be extracted from an energy flow) rate, and entropy rate. © 2010 IEEE.

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In this paper, the swing equations for renewable generators are formulated as a natural Hamiltonian system with externally applied non-conservative forces. A two-step process referred to as Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) is used to analyze and design feedback controllers for the renewable generator system. This formulation extends previous results on the analytical verification of the Potential Energy Boundary Surface (PEBS) method to nonlinear control analysis and design and justifies the decomposition of the system into conservative and non-conservative systems to enable a two-step, serial analysis and design procedure. In particular, this approach extends the work done by developing a formulation which applies to a larger set of Hamiltonian Systems that has Nearly Hamiltonian Systems as a subset. The results of this research include the determination of the required performance of a proposed Flexible AC Transmission System (FACTS)/storage device to enable the maximum power output of a wind turbine while meeting the power system constraints on frequency and phase. The FACTS/storage device is required to operate as both a generator and load (energy storage) on the power system in this design. The Second Law of Thermodynamics is applied to the power flow equations to determine the stability boundaries (limit cycles) of the renewable generator system and enable design of feedback controllers that meet stability requirements while maximizing the power generation and flow to the load. Necessary and sufficient conditions for stability of renewable generators systems are determined based on the concepts of Hamiltonian systems, power flow, exergy (the maximum work that can be extracted from an energy flow) rate, and entropy rate.

Active aerodynamic load control of wind turbine blades has been heavily researched for years by the wind energy research community and shows great promise for reducing turbine fatigue damage. One way to benefit from this technology is to choose to utilize a larger rotor on a turbine tower and drive train to realize increased turbine energy capture while keeping the fatigue damage of critical turbine components at the original levels. To assess this rotor-increase potential, Sandia National Laboratories and FlexSys Inc. performed aero/structural simulations of a 1.5MW wind turbine at mean wind speeds spanning the entire operating range. Moment loads at several critical system locations were post-processed and evaluated for fatigue damage accumulation at each mean wind speed. Combining these fatigue damage estimates with a Rayleigh wind-speed distribution yielded estimates of the total fatigue damage accumulation for the turbine. This simulation procedure was performed for both the turbine baseline system and the turbine system incorporating a rotor equipped with FlexSys active aerodynamic load control devices. The simulation results were post-processed to evaluate the decrease in the blade root flap fatigue damage accumulation provided by the active aero technology. The blade length was increased until the blade root flap fatigue damage accumulation values matched those of the baseline rotor. With the new rotor size determined, the additional energy capture potential was calculated. These analyses resulted in an energy capture increase of 11% for a mean wind speed of 6.5m/s.

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This paper presents a new nonlinear control methodology for slewing spacecraft, which provides both necessary and sufficient conditions for stability by identifying the stability boundaries, rigid body modes, and limit cycles. Conservative Hamiltonian system concepts, which are equivalent to static stability of airplanes, are used to find and deal with the static stability boundaries: rigid body modes. The application of exergy and entropy thermodynamic concepts to the work-rate principle provides a natural partitioning through the second law of thermodynamics of power flows into exergy generator, dissipator, and storage for Hamiltonian systems that is employed to find the dynamic stability boundaries: limit cycles. This partitioning process enables the control system designer to directly evaluate and enhance the stability and performance of the system by balancing the power flowing into versus the power dissipated within the system subject to the Hamiltonian surface (power storage). Relationships are developed between exergy, power flow, static and dynamic stability, and Lyapunov analysis. The methodology is demonstrated with two illustrative examples: (1) a nonlinear oscillator with sinusoidal damping and (2) a multi-input-multioutput three-axis slewing spacecraft that employs proportional-integral-derivative tracking control with numerical simulation results.