Article, 2024

Adaptive generalized predictive voltage control of islanded ac microgrid in presence of symmetric and asymmetric faults

Electric Power Systems Research, ISSN 0378-7796, Volume 226, 10.1016/j.epsr.2023.109964

Contributors

Felegari B. 0000-0003-2411-6289 [1] Asvadi-Kermani O. 0000-0001-6257-1958 [1] Oshnoei A. 0000-0003-3178-6643 [2] Momeni H. 0000-0003-2855-2141 [1] Muyeen S.M. 0000-0003-4955-6889 (Corresponding author) [3]

Affiliations

  1. [1] Tarbiat Modares University
  2. [NORA names: Iran; Asia, Middle East];
  3. [2] Aalborg University
  4. [NORA names: AAU Aalborg University; University; Denmark; Europe, EU; Nordic; OECD];
  5. [3] Qatar University
  6. [NORA names: Qatar; Asia, Middle East]

Abstract

In islanded microgrids, efficiently controlling the output voltage and frequency of voltage source inverters while maintaining stability poses a significant challenge, particularly during grid fault conditions. This paper presents an online adaptive Kalman-based constrained generalized predictive voltage controller (AGPVC) that there are constraints on the inverter control signal and its changes to maintain microgrid s’ voltage and frequency are stayed within the specified limits and restore them to reference values after short circuit faults, after the system s’ dynamic changes. Notably, the proposed controller operates without requiring knowledge of the system's physical parameters, relying solely on local information to regulate the inverter output. The constrained and adaptive model estimation mechanisms increase the stability and scalability of the proposed method for implementation on the different systems. The transient and steady-steady state response of the output voltage in both normal and faulty conditions shows that for the 380 V reference maximum voltage drop during fault is 40 V less than the traditional method after the fault happens. The effectiveness of the proposed controller is verified through time-domain simulations conducted in MATLAB/Simulink.

Keywords

Adaptive control, Faults, Kalman filter estimation, Model Predictive Control

Funders

  • Qatar National Library

Data Provider: Elsevier