1,314 research outputs found
Microgrid optimization, modelling and control
2014 Fall.To view the abstract, please see the full text of the document
Robust Current Control of Doubly Fed Wind Turbine Generator under Unbalanced Grid Voltage Conditions
Comparison of different repetitive control architectures: synthesis and comparison. Application to VSI Converters
Repetitive control is one of the most used control approaches to deal with periodic references/disturbances. It owes its properties to the inclusion of an internal model in the controller that corresponds to a periodic signal generator. However, there exist many different ways to include this internal model. This work presents a description of the different schemes by means of which repetitive control can be implemented. A complete analytic analysis and comparison is performed together with controller synthesis guidance. The voltage source inverter controller experimental results are included to illustrative conceptual developmentsPeer ReviewedPostprint (published version
Generalized Multivariable Grid-Forming Control Design for Power Converters
The grid-forming converter is an important unit in the future power system
with more inverter-interfaced generators. However, improving its performance is
still a key challenge. This paper proposes a generalized architecture of the
grid-forming converter from the view of multivariable feedback control. As a
result, many of the existing popular control strategies, i.e., droop control,
power synchronization control, virtual synchronous generator control, matching
control, dispatchable virtual oscillator control, and their improved forms are
unified into a multivariable feedback control transfer matrix working on
several linear and nonlinear error signals. Meanwhile, unlike the traditional
assumptions of decoupling between AC and DC control, active power and reactive
power control, the proposed configuration simultaneously takes all of them into
consideration, which therefore can provide better performance. As an example, a
new multi-input-multi-output-based grid-forming (MIMO-GFM) control is proposed
based on the generalized configuration. To cope with the multivariable
feedback, an optimal and structured synthesis is used to design
the control parameters. At last, simulation and experimental results show
superior performance and robustness of the proposed configuration and control
Advanced control techniques for modern inertia based inverters
”In this research three artificial intelligent (AI)-based techniques are proposed to regulate the voltage and frequency of a grid-connected inverter. The increase in the penetration of renewable energy sources (RESs) into the power grid has led to the increase in the penetration of fast-responding inertia-less power converters. The increase in the penetration of these power electronics converters changes the nature of the conventional grid, in which the existing kinetic inertia in the rotating parts of the enormous generators plays a vital role. The concept of virtual inertia control scheme is proposed to make the behavior of grid connected inverters more similar to the synchronous generators, by mimicking the mechanical behavior of a synchronous generator. Conventional control techniques lack to perform optimally in nonlinear, uncertain, inaccurate power grids. Besides, the decoupled control assumption in conventional VSGs makes them nonoptimal in resistive grids.
The neural network predictive controller, the heuristic dynamic programming, and the dual heuristic dynamic programming techniques are presented in this research to overcome the draw backs of conventional VSGs. The nonlinear characteristics of neural networks, and the online training enable the proposed methods to perform as robust and optimal controllers. The simulation and the experimental laboratory prototype results are provided to demonstrate the effectiveness of the proposed techniques”--Abstract, page iv
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