Publications
Energy resilience: exercises for Marine Corps installations
February 1, 2022
Journal Article
Published in:
Marine Corps Gazette, Vol. 106, No. 2, February 2022, p. 20-24.
Summary
Microgrids are areas that are self-sufficient for power that can controllably disconnect from the incoming utility feed and control generation assets in conjunction with changing load requirements. They are increasingly being touted as a way to improve installations energy resilience because they allow installations to decouple from the larger electric grid if it fails and continue to provide power in the face of growing natural and man-made threats to Marine Corps installations. However, before commanders can put resources toward upgrading infrastructure, they need to identify and understand their vulnerabilities. A key way to do this is by holding exercises designed to simulate grid failures and outages either in a tabletop manner or in realtime. These exercises also help personnel train for disruptions, understand their impact on operations, and identify unknown interdependencies that can be just as important as investing in resilient technology and the physical electric grid. In order for the equipment to work, personnel have to know how to employ it and commands need to understand how outages will affect their installations. These types of exercises are as important as the physical infrastructure or ensuring the energy resilience of Marine Corps installations and the missions that depend on them in the future.
Summary
Microgrids are areas that are self-sufficient for power that can controllably disconnect from the incoming utility feed and control generation assets in conjunction with changing load requirements. They are increasingly being touted as a way to improve installations energy resilience because they allow installations to decouple from the larger electric...
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A hybrid algorithm for parameter estimation (HAPE) for dynamic constant power loads
November 1, 2021
Journal Article
Published in:
IEEE Trans. Ind. Electron., Vol. 68, No. 11, November 2021, pp. 10326-35.
Summary
Low-inertia microgrids may easily have a single load which can make up most of the total load, thereby greatly affecting stability and power quality. Instead of a static load model, a dynamic constant power load (DCPL) model is considered here. Next, a hybrid algorithm for parameter estimation (HAPE) is introduced. In order to verify the load model and the HAPE, two experiments are conducted with different DCPLs using a Power-Hardwarein-the-Loop (PHiL) testbed. The PHiL testbed consists of a real-time computer working with a programmable power amplifier in order to perturb the input voltage's amplitude and frequency. Each connected DCPL in two separate experiments serves as the device under test (DUT). Using the captured experimental data as a reference, the HAPE is then invoked. The resulting parameter estimates are used to define simulation models. Both resulting DCPL models are simulated to produce waveforms that closely resemble experimental waveforms. Finally, the HAPE's resulting parameter estimates are presented, and the performance of the HAPE is discussed.
Summary
Low-inertia microgrids may easily have a single load which can make up most of the total load, thereby greatly affecting stability and power quality. Instead of a static load model, a dynamic constant power load (DCPL) model is considered here. Next, a hybrid algorithm for parameter estimation (HAPE) is introduced...
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High quality of service in future electrical energy systems: a new time-domain approach
November 18, 2020
Journal Article
Published in:
IEEE Trans. on Sustainable Energy, vol. 12, no. 2, pp. 1196-1205, April 2021, doi: 10.1109/TSTE.2020.3038884.
Summary
In this paper we study dynamical distortion problems in future electrical energy systems with high renewable penetration. We introduce a new time-domain modeling of electrical energy systems comprising inverter-controlled distributed energy resources (DERs). This modeling is first used to quantify the relations between distortions and real/reactive power dynamics. Next, to ensure acceptable Quality of Service (QoS), a novel nonlinear distributed inverter control is introduced. Sufficient conditions are established for the guaranteed performance of the proposed control. These conditions further support the practical implementation of the derived controller. The effectiveness of this enhanced control is illustrated using simulations for the case of avoiding system instability during sudden grid reconfigurations. Simulations also show that distortions can be suppressed in systems with parallel-connected solar photovoltaics (PVs).
Summary
In this paper we study dynamical distortion problems in future electrical energy systems with high renewable penetration. We introduce a new time-domain modeling of electrical energy systems comprising inverter-controlled distributed energy resources (DERs). This modeling is first used to quantify the relations between distortions and real/reactive power dynamics. Next, to...
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Toward distributed control for reconfigurable robust microgrids
October 11, 2020
Conference Paper
Published in:
2020 IEEE Energy Conversion Congress and Exposition, ECCE, 11-15 October 2020.
Summary
Microgrids have been seen as a good solution to providing power to forward-deployed military forces. However, compatibility, robustness and stability of current solutions are often questionable. To overcome some of these problems, we first propose a theoretically-sound modeling method which defines common microgrid component interfaces using power and rate of change of power. Using this modeling approach, we propose a multi-layered distributed control: the higher control layer participates in dynamic power management that ensures acceptable voltage, while the lower layer stabilizes frequency by regulating the dynamics to the power determined by the higher layer. Numerical and hardware tests are conducted to evaluate the effectiveness of the proposed control.
Summary
Microgrids have been seen as a good solution to providing power to forward-deployed military forces. However, compatibility, robustness and stability of current solutions are often questionable. To overcome some of these problems, we first propose a theoretically-sound modeling method which defines common microgrid component interfaces using power and rate of...
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A workflow for non-linear load parameter estimation using a power-hardware-in-the-loop experimental testbed
March 15, 2020
Conference Paper
Published in:
2020 IEEE Applied Power Electronics Conf. and Expo., APEC, 15-19 March 2020.
Summary
Low-inertia microgrids may easily have a single load which can make up most of the total load, thereby greatly affecting stability and power quality. Instead of static load models, dynamic load models are presented here for constant current loads (CILs) and constant power loads (CPLs). Next, a flexible Power-Hardware-in-the-Loop (PHiL) testbed is employed for the experiments in this work. The PHiL testbed consists of a real-time computer working with a power amplifier in order to perturb its voltage and frequency. A connected load serves as the device under test (DUT). Using the captured experimental data as a reference, a parameter estimation algorithm is then implemented. The resulting parameter estimates are used to define simulation models. Both the CIL and CPL dynamic models are simulated to produce waveforms that closely resemble experimental waveforms. The algorithm, referred to as an enhanced monte carlo algorithm (EMCA), is explained in this work. Finally, the EMCA's resulting parameter estimates are presented.
Summary
Low-inertia microgrids may easily have a single load which can make up most of the total load, thereby greatly affecting stability and power quality. Instead of static load models, dynamic load models are presented here for constant current loads (CILs) and constant power loads (CPLs). Next, a flexible Power-Hardware-in-the-Loop (PHiL)...
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Unified value-based feedback, optimization and risk management in complex electric energy systems
February 22, 2020
Journal Article
Published in:
Optim Eng 21, 427–483 (2020)
Summary
The ideas in this paper are motivated by an increased need for systematic data-enabled resource management of large-scale electric energy systems. The basic control objective is to manage uncertain disturbances, power imbalances in particular, by optimizing available power resources. To that end, we start with a centralized optimal control problem formulation of system-level performance objective subject to complex interconnection constraints and constraints representing highly heterogeneous internal dynamics of system components. To manage spatial complexity, an inherent multi-layered structure is utilized by modeling interconnection constraints in terms of unifed power variables and their dynamics. Similarly, the internal dynamics of components and sub-systems (modules), including their primary automated feedback control, is modeled so that their input–output characterization is also expressed in terms of power variables. This representation is shown to be key to managing the multi-spatial complexity of the problem. In this unifying energy/ power state space, the system constraints are all fundamentally convex, resulting in the convex dynamic optimization problem, for typically utilized quadratic cost functions. Based on this, an interactive multi-layered modeling and control method is introduced. While the approach is fundamentally based on the primal–dual decomposition of the centralized problem, this is formulated for the frst time for the couple real-reactive power problem. It is also is proposed for the frst time to utilize sensitivity functions of distributed agents for solving the primal distributed problem. Iterative communication complexity typically required for convergence of pointwise information exchange is replaced by the embedded distributed optimization by the modules when creating these functions. A theoretical proof of the convergence claim is given. Notably, the inherent multi-temporal complexity is managed by performing model predictive control (MPC)-based decision making when solving distributed primal problems. The formulation enables distributed decision-makers to value uncertainties and related risks according to their preferences. Ultimately, the distributed decision making results in creating a bid function to be used at the coordinating market-clearing level. The optimization approach in this paper provides a theoretical foundation for next-generation Supervisory Control and Data Acquisition (SCADA) in support of a Dynamic Monitoring and Decision Systems (DyMonDS) for a multi-layered interactive market implementation in which the grid users follow their sub-objectives and the higher layers coordinate interconnected sub-systems and the high-level system objectives. This forms a theoretically sound basis for designing IT-enabled protocols for secure operations, planning, and markets.
Summary
The ideas in this paper are motivated by an increased need for systematic data-enabled resource management of large-scale electric energy systems. The basic control objective is to manage uncertain disturbances, power imbalances in particular, by optimizing available power resources. To that end, we start with a centralized optimal control problem...
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Modeling and distributed control of microgrids: a negative feedback approach
December 11, 2019
Conference Paper
Published in:
2019 IEEE 58th Conf. on Decision and Control, CDC, 11-13 December 2019.
Summary
In this paper, we first show how general microgrid can be modeled as a negative feedback configuration comprising two subsystems. The first subsystem is the interconnected microgrid grid which is affected through negative feedback by the second subsystem consisting of all single-port components. This is modeled by transforming physical state variables into energy state variables and by systematically defining input and output of system components in this transformed state space. We next draw on the fact that for this basic feedback configuration there exist several types of conditions regarding subsystem properties which ensure overall system properties. In particular, we utilize dissipativity theory to propose a subsystem nonlinear control design for heterogeneous resource components comprising microgrids so that they jointly result in a closed-loop feasible and stable dynamical system for given ranges of system disturbances.
Summary
In this paper, we first show how general microgrid can be modeled as a negative feedback configuration comprising two subsystems. The first subsystem is the interconnected microgrid grid which is affected through negative feedback by the second subsystem consisting of all single-port components. This is modeled by transforming physical state...
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Toward technically feasible and economically efficient integration of distributed energy resources
September 24, 2019
Conference Paper
Published in:
57th Annual Allerton Conf. on Communication, Control, and Computing, 24-27 September 2019.
Summary
This paper formulates the efficient and feasible participation of distributed energy resources (DERs) in complex electricity services as a centralized nonlinear optimization problem first. This problem is then re-stated using the novel energy/power transformed state space. It is shown that the DER dynamics in closed-loop can be made linear in this new state space. The decision making by the DERs then becomes a distributed model predictive control problem and it forms the basis for deriving physically implementable convex market bids. A multi-layered interactive optimization for clearing the distributed bids by higher layer decision makers, such as market aggregators, is posed and shown to lead to near-optimal system-level performance at the slower market clearing rates. A proof-of-concept example is illustrated involving close to one hundred heterogeneous controllable DERs with real consumption data of a distribution feeder in Texas, contributing to automatic generation control (AGC).
Summary
This paper formulates the efficient and feasible participation of distributed energy resources (DERs) in complex electricity services as a centralized nonlinear optimization problem first. This problem is then re-stated using the novel energy/power transformed state space. It is shown that the DER dynamics in closed-loop can be made linear in...
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Introducing DyMonDS-as-a-Service (DyMaaS) for Internet of Things
September 24, 2019
Conference Paper
Published in:
2019 IEEE High Performance Computing Conf., HPEC, 24-26 September 2019.
Summary
With recent trends in computation and communication architecture, it is becoming possible to simulate complex networked dynamical systems by employing high-fidelity models. The inherent spatial and temporal complexity of these systems, however, still acts as a roadblock. It is thus desirable to have adaptive platform design facilitating zooming-in and out of the models to emulate time-evolution of processes at a desired spatial and temporal granularity. In this paper, we propose new computing and networking abstractions, that can embrace physical dynamics and computations in a unified manner, by taking advantage of the inherent structure. We further design multi-rate numerical methods that can be implemented by computing architectures to facilitate adaptive zooming-in and out of the models spanning multiple spatial and temporal layers. These methods are all embedded in a platform called Dynamic Monitoring and Decision Systems (DyMonDS). We introduce a new service model of cloud computing called DyMonDS-as-a-Service (DyMaas), for use by operators at various spatial granularities to efficiently emulate the interconnection of IoT devices. The usage of this platform is described in the context of an electric microgrid system emulation.
Summary
With recent trends in computation and communication architecture, it is becoming possible to simulate complex networked dynamical systems by employing high-fidelity models. The inherent spatial and temporal complexity of these systems, however, still acts as a roadblock. It is thus desirable to have adaptive platform design facilitating zooming-in and out...
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New software helps users build resilient, cost-effective energy architectures
July 2, 2019
Journal Article
Published in:
Lincoln Laboratory News
Summary
The Energy Resilience Analysis tool lets mission owners and energy managers balance the needs of critical missions on military installations with affordability when they design energy resilience solutions.
Summary
The Energy Resilience Analysis tool lets mission owners and energy managers balance the needs of critical missions on military installations with affordability when they design energy resilience solutions.
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