Advanced control schemes for wind power plants and renewable energy-based islanded microgrids

Shabbir, Md Nasmus Sakib Khan (2021) Advanced control schemes for wind power plants and renewable energy-based islanded microgrids. Doctoral (PhD) thesis, Memorial University of Newfoundland.

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Renewable energy sources are increasingly integrated in power grids, creating significant challenges for control and system operation. Among various renewable energy sources, wind power is one of the dominant forms, mainly generated from large-scale transmission-connected wind power plants (WPPs). The grid-connected WPPs are required to follow grid codes to maintain a predefined power factor range under normal operation and supply required reactive power under faulty conditions. To meet grid code requirements, a WPP control architecture is developed in this thesis. The control system consists of a central WPP controller and a local wind turbine generator (WTG) controller, both operate in the voltage control mode. Therefore, the controller can respond faster and is robust to communication failures. Under normal operating conditions, the proposed controller regulates the WPP’s operation within its steady-state reactive power capability and meets the power factor limits. Under faulty conditions, the controller forces the WPP to its maximum capability to contribute more reactive power support to the grid. Two mathematical models representing the steady-state and maximum reactive power capability of the WPP are developed through regression and analytic approaches, respectively. In the second part of the thesis, a model predictive control (MPC)-based distributed generation (DG) controller is proposed to regulate the voltage and frequency at the point of common coupling (PCC) in an islanded microgrid. A data-driven input-output Box-Jenkins polynomial predictive model for DG control is developed using the Gauss-Newton-based nonlinear least square method with the prediction optimization focus. The model inputs are direct- and quadrature-axis components of the control signal, and the model outputs are deviations of the voltage and frequency from their nominal values at the PCC. The proposed MPC controller operates using the PCC data and does not require the microgrid’s central controllers or DG-to-DG communication networks. It can effectively compensate voltage and frequency deviations at the PCC and ensure proportional reactive power sharing among DGs without a secondary controller and a virtual impedance loop. The integrated Kalman filter in the MPC structure enables a robust controller design when subjected to impedance variations and measurement noises.

Item Type: Thesis (Doctoral (PhD))
Item ID: 15243
Additional Information: Includes bibliographical references.
Keywords: renewable energy, wind power plant, maximum reactive power, voltage control, distributed generation, islanded microgrid, model predictive control
Department(s): Engineering and Applied Science, Faculty of
Date: June 2021
Date Type: Submission
Digital Object Identifier (DOI):
Library of Congress Subject Heading: Renewable energy sources; Wind power plants; Distributed generation of electric power; Microgrids (Smart power grids); Predictive control; Mathematical models.

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