Hamiltonian methods of modeling and control of AC microgrids with spinning machines and inverters

Matthews, Ronald C.; Weaver, Wayne W.; Robinett, Rush D.; Wilson, David G.

doi:10.1016/j.ijepes.2017.11.041

Cited by 11 publications

(6 citation statements)

References 11 publications

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“…An inner feedback control loop was designed to ensure the tracking of the DGUs current references set by the droop controller. This control loop was implemented as a proportional-integral (PI) controller designed based on the Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) design technique [22,23,31]. Figure 7 shows the schematic of the Simulink model of the droop controller and the PI control loop.…”

Section: Hardware-in-the-loop Experimental Resultsmentioning

confidence: 99%

Droop Control in DQ Coordinates for Fixed Frequency Inverter-Based AC Microgrids

et al. 2019

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This paper presents a proof-of-concept for a novel dq droop control technique that applies DC droop control methods to fixed frequency inverter-based AC microgrids using the dq0 transformation. Microgrids are usually composed of distributed generation units (DGUs) that are electronically coupled to each other through power converters. An inherent property of inverter-based microgrids is that, unlike microgrids with spinning machines, the frequency of the parallel-connected DGUs is a global variable independent from the output power since the inverters can control the output waveform frequency with a high level of precision. Therefore, conventional droop control methods that distort the system frequency are not suitable for microgrids operating at a fixed frequency. It is shown that the proposed distributed droop control allows accurate sharing of the active and reactive power without altering the microgrid frequency. The simulation and hardware-in-the-loop (HIL) results are presented to demonstrate the efficacy of the proposed droop control. Indeed, following a load change, the dq droop controller was able to share both active and reactive power between the DGUs, whereas maintaining the microgrid frequency deviation at 0% and the bus voltage deviations below 6% of their respective nominal values.

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Section: Hardware-in-the-loop Experimental Resultsmentioning

confidence: 99%

Droop Control in DQ Coordinates for Fixed Frequency Inverter-Based AC Microgrids

et al. 2019

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“…The update rate can be on the order of milliseconds and uses both network communication and hardwired feedback loops. HSSPFC has been developed for microgrid systems in general and currently includes; i) a single DC Microgrid, ii) networked DC microgrids (Weaver, 2015a(Weaver, , 2015b, iii) AC single/networked inverter-based microgrids (Wilson 2016b), iv) AC inverter/synchronous generator microgrids, vi) hybrid AC/DC individual/networked microgrids , and vii) multi-spinning machines on an AC bus (Matthews, 2018). Several conditions are investigated; i) ESS optimization for controller set-points, ii) baseline ESS requirements for a single mission load under steady-state conditions, and iii) nonlinear metastable boundaries with no ESS.…”

Section: Hsspfc Energy Storage Controllermentioning

confidence: 99%

Nonlinear Power Flow Control Design Methodology for Navy Electric Ship Microgrid Energy Storage Requirements

Wilson

Weaver

Robinett

et al. 2018

Proceedings of the International Naval Engineering Conference and Exhibition (INEC)

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As part of the U.S. Navy’s continued commitment to protecting U.S. interests at home and abroad, the Navy is investing in the development of new technologies that broaden U.S. warship capabilities and maintain U.S. naval superiority. NAVSEA is developing power systems technologies for the Navy to realize an all-electric warship. New nonlinear power system controls approaches are being developed to improve system performance in light of new electrically powered weaponry that behave as pulsed-loads. Advancements include the identification of pulsed-load profiles that identify Energy Storage System (ESS) requirements. A dynamic optimization engine has been developed and serves as the feedforward receding horizon control portion of the Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) feedback controls for ESS networked microgrid system. A Coalition Warfare Program (CWP) test scenario was selected. The CWP is defined with a Reduced Order Model (ROM) that includes; generation, ESS, and mission pulsed-loads. Several numerical simulation studies were conducted. The CWP scenario is bounded by a baseline mission load local ESS contrasted with no ESS full nonlinear metastable boundaries. The main goal is to minimize ESS size and weight while maintaining power system performance. This paper focuses on the control and optimization of ESS as an integral part of supporting critical mission loads and real-time control algorithm development to improve future energy efficiency for multi-mission activities.

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“…The first step towards achieving a satisfactory performance in a microgrid is to model its dynamic behaviour [8][9][10]. The suitable modelling framework may be different when special types of control objectives are of interest [11,12]. It is becoming popular to use a hierarchical control structure for microgrids which is composed of local controllers at a primary level, a control system at the secondary level for coordination of the local controllers, and probably a tertiary level which coordinates several microgrids with the main grid [4,13].…”

Section: Introductionmentioning

confidence: 99%

Communication system effects on the secondary control performance in microgrids

Tavassoli

Fereidunian

Savaghebi

2020

IET Renewable Power Generation

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In the most common hierarchical control structure for microgrids, the secondary control layer relies on communication technologies for receiving feedback data and sending control commands. The imperfections of communication such as the delays can cause oscillations during the voltage and frequency restoration which degrade the power quality. This work aims at studying this effect in the case of a typical AC microgrid in the islanded mode. For this purpose, stochastic delay models for industrial communication protocols are combined with a simulation model of the microgrid together with its control system up to the secondary level. The results illustrate how the choice of communication technology can affect the transient response. Additionally, compensation of the control performance for the effects of communication is considered. A simple method is used to improve the control performance only by retuning the controller coefficients, without altering the standard control structure. It is shown that appropriate retuning of the secondary controller can prevent from oscillations caused by the delays and improve the power quality to some extent. The presented framework can be used for designing and verifying the combination of communication and control subsystems in microgrids.

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Hamiltonian methods of modeling and control of AC microgrids with spinning machines and inverters

Cited by 11 publications

References 11 publications

Droop Control in DQ Coordinates for Fixed Frequency Inverter-Based AC Microgrids

Droop Control in DQ Coordinates for Fixed Frequency Inverter-Based AC Microgrids

Nonlinear Power Flow Control Design Methodology for Navy Electric Ship Microgrid Energy Storage Requirements

Communication system effects on the secondary control performance in microgrids

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