A Reduced-order Aggregated Model for Parallel Inverter Systems with Virtual Oscillator Control

被引:11
|
作者
Khan, M. M. S. [1 ]
Lin, Yashen [1 ]
Johnson, Brian [2 ]
Purba, Victor [3 ]
Sinha, Mohit [3 ]
Dhople, Sairaj [3 ]
机构
[1] Natl Renewable Energy Lab, Golden, CO 80401 USA
[2] Univ Washington, Dept Elect Engn, Seattle, WA 98195 USA
[3] Univ Minnesota, Dept Elect & Comp Engn, Minneapolis, MN 55455 USA
基金
美国国家科学基金会;
关键词
DYNAMIC EQUIVALENT;
D O I
10.1109/COMPEL.2018.8458494
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper introduces a reduced-order aggregated model for parallel-connected inverters controlled with virtual oscillator control (VOC). The premise of VOC is to modulate inverter dynamics to emulate those of nonlinear oscillators with the goal of realizing a stable ac microgrid in the absence of communication, synchronous generation, or a stiff grid. To obtain a reduced-order model for a system of parallel-connected inverters with VOC, we first formulate a set of scaling laws that describe how the controller and filter parameters of a given inverter depend on its voltage and power rating. Subsequently, we show that N parallel inverters which adhere to this scaling law can be modeled with the same structure and hence the same computational burden of the model of a single inverter. The proposed aggregate model is experimentally validated on a system of three parallel inverters with heterogeneous power ratings.
引用
收藏
页数:6
相关论文
共 50 条
  • [41] Reduced-order residential home modeling for model predictive control
    Cole, Wesley J.
    Powell, Kody M.
    Hale, Elaine T.
    Edgar, Thomas F.
    ENERGY AND BUILDINGS, 2014, 74 : 69 - 77
  • [42] Analysis and Comparison of Reduced-order Model and Modeling Method for Grid-connected Inverter
    Yu H.
    Su J.
    Wang Y.
    Wang H.
    Shi Y.
    Yu, Hongru (hr_y_0514@163.com), 1600, Automation of Electric Power Systems Press (44): : 155 - 165
  • [43] On Model-Free Reinforcement Learning of Reduced-order Optimal Control for Singularly Perturbed Systems
    Mukherjee, Sayak
    Bai, He
    Chakrabortty, Aranya
    2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC), 2018, : 5288 - 5293
  • [44] Reduced-order models for microelectromechanical systems
    Batra, R. C.
    Porfiri, M.
    Spinello, D.
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MECHANICAL ENGINEERING AND MECHANICS 2007, VOLS 1 AND 2, 2007, : 2 - 6
  • [45] Reduced-Order Model of a Half-Bridge Series Resonant Inverter for Power Control in Domestic Induction Heating Applications
    Dominguez, A.
    Barragan, L. A.
    Artigas, J. I.
    Otin, A.
    Urriza, I.
    Navarro, D.
    2015 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY (ICIT), 2015, : 2542 - 2547
  • [46] REDUCED-ORDER MODELING FOR HYPERTHERMIA CONTROL
    POTOCKI, JK
    THARP, HS
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 1992, 39 (12) : 1265 - 1273
  • [47] REDUCED-ORDER OUTPUT-FEEDBACK CONTROL OF A CLASS OF UNCERTAIN SYSTEMS
    BENEDE, JR
    LEITMANN, G
    RYAN, EP
    LECTURE NOTES IN CONTROL AND INFORMATION SCIENCES, 1992, 170 : 29 - 34
  • [48] Reachability analysis of hybrid control systems using reduced-order models
    Han, Z
    Krogh, B
    PROCEEDINGS OF THE 2004 AMERICAN CONTROL CONFERENCE, VOLS 1-6, 2004, : 1183 - 1189
  • [49] A Novel Reduced-Order Protocol for Consensus Control of Linear Multiagent Systems
    Li, Xianwei
    Soh, Yeng Chai
    Xie, Lihua
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2019, 64 (07) : 3005 - 3012
  • [50] On backstepping control for a class of multiple uncertain systems with reduced-order ESO
    Wu, Tao
    Shi, Shangyao
    Zhang, Dong
    Shao, Xingling
    INTERNATIONAL JOURNAL OF CONTROL, 2023, 96 (02) : 309 - 320