Real-time grid parameter estimation methods using model based predictive control for grid-connected converters

Arif, Bilal (2016) Real-time grid parameter estimation methods using model based predictive control for grid-connected converters. PhD thesis, University of Nottingham.

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In recent years, renewable and distributed generation (DG) systems have contributed towards an efficient and an economic way of transporting electricity to end-users as the generation sources are in general located nearer the loads. DG and renewable energy systems are modifying the old concept of distribution network by instigating a bi-directional power flow into the grid, facilitated through the use of power electronic grid-connected converters.

A challenge associated with grid-connected converters arises when they are interacted with a grid that is not stiff, like weak micro grids. Small grid parameter variations in these systems can considerably affect the performance of the converter control and lead to higher values in current total harmonic distortion (THD) and loss of control and synchronization. Thus, the control of grid-connected power converters needs to be regularly updated with latest variation in grid parameters.

Model Predictive Direct Power Control (MP-DPC) has been chosen as the control strategy for the work presented in this thesis due to its advantages over traditional control techniques such as multivariable control, no need of phase-locked loops (PLLs) for grid synchronization and avoidance of cascaded control loops.

Two novel methods for estimating the grid impedance variation, and hence the grid voltage, are presented in this thesis along with a detailed literature review on control of grid-connected converters with special emphasis on impedance estimation techniques. The first proposed estimation method is based on the difference in grid voltage magnitudes at two consecutive sampling instants while the second method is based on a model-fitting algorithm similar to the concept of cost-function optimization in model predictive control. The proposed estimation methods in this thesis are integrated within the MP-DPC, therefore updating the MP-DPC in real-time with the latest variation in grid impedance. The proposed algorithms provide benefits such as: quick response to transient variations, operation under low values of short-circuit-ratio (SCR), robust MP-DPC control, good reference tracking to grid parameter variations and operation under unbalanced grid voltages. The thesis also presents the advantages and drawbacks of the proposed methods and areas where further improvement can be researched.

The work presented has been tested on a three phase two-level grid-connected converter prototype, which is connected to a low voltage substation highly dominated by inductive component of grid impedance. It can be adapted and modified to be used for general grid impedance estimation, medium or high voltage applications, in case of multilevel grid-connected converter topologies or photo-voltaic (PV) grid-connected applications.

Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Zanchetta, P.
Tarisciotti, L.
Clare, J.C.
Keywords: Electric current converters, Predictive control, Impedance (Electricity), Microgrids (Smart power grids)
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3001 Distribution or transmission of electric power
Faculties/Schools: UK Campuses > Faculty of Engineering
Item ID: 31963
Depositing User: Arif, Bilal
Date Deposited: 27 Jul 2016 09:38
Last Modified: 14 Oct 2017 18:25

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