Model predictive direct power control of three-level T-type inverter-fed doubly-fed induction generator for wind energy system

The paper proposes a simplified direct power control strategy of a doubly-fed induction generator fed by a three-level T-type inverter based on finite control set model predictive control. A mathematical model based on grid voltage orientation was employed to determine the predictive values of the stator flux, rotor current, and capacitor voltages for all feasible rotor-side inverter output voltages. The active and reactive powers were calculated by using the grid voltage and the rotor current. A cost function was applied to track the active and reactive powers, maintain the balance of capacitor voltages, and reduce the common-mode voltage. The best switching control input was chosen by minimizing the cost function and implemented to the inverter. Different operating conditions of wind turbine systems were studied with Matlab/Simulink environment. The simulation results validate the improved performance of the proposed method compared with the classical control in terms of transient response and steady-state conditions

Enhanced Deadbeat Control Approach for Grid-Tied Multilevel Flying Capacitors Inverter

This paper proposes an enhanced Deadbeat Controller (DBC) for a grid-tied Flying Capacitors Inverter (FCI). The proposed DBC guarantees the balancing of the capacitors' voltages while injecting current to the grid with lower Total Harmonics Distortion (THD). The proposed controller has the following advantages: 1) Improved current tracking quality even at zero crossing instants by using a weighted state-space model, 2) Superior steady-state performance (lower current THD) compared to other prediction-based control techniques such as Finite-Control-Set Model Predictive Control, 3) The generated duty cycles are normalized to the common base when the desired state is out of reach within the sampling time, 4) Voltage Ride-Through (VRT) capability, and 5) Robustness to parameters variation. Theoretical analysis, simulation, and experimental results are presented to show the effectiveness of the proposed control technique in ensuring uninterruptible and smooth transfer of energy to the grid during normal/abnormal operating conditions (severe voltage sags, parameters variation, etc.)

Mathematical models of vapor-compression systems for multivariable control of the refrigerant dynamics and indoor air conditions

Thesis (PhD (Electronic Engineering))--University of Pretoria, 2023.Detailed steady and transient state models of vapor compression (VC) systems have been suggested in this work so that the governing parameters of the refrigerant dynamics such as pressure, enthalpy and temperature could be predicted at different operating conditions. The steady and transient state models were validated with experimental data collected during startup and steady state operations. The experimental setup was equipped with a thermostatic expansion valve, a reciprocal compressor and plate heat exchangers for the condenser and evaporator. Recirculated water was adopted as secondary fluid for heat transfer with R-134a refrigerant. The steady state model was developed from first principles with the refrigerant conditions being determined at each junction between the components of the VC system. A steady state matrix was built to determine the model outputs and it could be adopted for similar problems such as steady state modelling of single-condenser-and-multi-evaporators systems. The refrigerant pressures through the evaporator and condenser were in agreement with experiments. Other refrigerant conditions such as enthalpy and temperature through the components were also validated with experiments. The evaporator and condenser modelling in transient state required special attention and Navier-Stokes equations were adopted for this purpose along with a finite volume scheme for discretization of the condenser and evaporator into 3 and n-control volumes. A transient state matrix was also built for outputs’ prediction in transient operating conditions such as startup and shutdown. The refrigerant conditions namely pressure and enthalpy through the evaporator and condenser were validated with experiments. The transient state model was then improved and converted into a control-oriented model with 12 state variables. The control-oriented model considered phase change in the condenser and evaporator namely, superheat, two-phase and subcooling. Model predictive control (MPC) was implemented on the control-oriented model after a model linearization around a steady state point carefully selected from the steady state experiments performed for validation of the steady state modelling. MPC implementation enabled to control superheat and evaporating pressure simultaneously with consideration of the coupling effect between superheat and capacity regulation. MPC was integrated in Simulink with satisfactory performances regarding disturbance rejection and reference tracking. Building up on satisfactory MPC performance for multivariable control of the refrigerant dynamics, a proportional integral derivative (PID)-MPC controller was implemented on a Chiller-Fan coil unit (FCU) to control simultaneously, indoor temperature, humidity and CO2 level with the coupling effect between humidity and temperature taken into consideration. PID was implemented on a sub layer control loop located at the first heat exchanger and fresh air temperature was maintained within settings to level-out with room temperature to prevent from imbalanced loads. Disturbance rejection and set point tracking were satisfactory without necessarily increasing the supply fan and compressor speeds. MPC was implemented on an upper layer control loop located at a secondary heat exchanger to regulate simultaneously indoor humidity, temperature and CO2 level. The coupling effect between humidity and temperature was well taken care of by the MPC loop and CO2 level regulation was performed without additional load as fresh air intake was carefully pre-cooled using the primary heat exchanger controlled with a PID loop. The performance of the sub layer PID was satisfactory with regards to stability, maximum overshoot and settling time whilst reference tracking and disturbance rejection were satisfactory with the upper layer MPC.Electrical, Electronic and Computer EngineeringPhD (Electronic Engineering)Unrestricte

An improved two-vector model predictive torque control based on RMS duty ratio optimization for pmsm

This paper proposes an improved two-vector model-predictive torque control (MPTC) strategy to reduce the average torque ripple and improve the flux tracking performance. When determining the duty ratio of vector combination, this method aims at restricting the root mean square (RMS) error of both torque and flux during the whole control period. Every vector combination and corresponding time duration are evaluated in the cost function, which leads to global restriction of torque ripple and flux ripple. In order to avoid increasing switching frequency and computational burden, a restriction is added on the second vector. The three candidates of the second vector are the two adjacent vectors of the first one and zero vector. Simulation results are provided to show the effectiveness of the proposed strategy

Adaptive reference model predictive control for power electronics

An adaptive reference model predictive control (ARMPC) approach is proposed as an alternative means of controlling power converters in response to the issue of steady-state residual errors presented in power converters under the conventional model predictive control (MPC). Differing from other methods of eliminating steady-state errors of MPC based control, such as MPC with integrator, the proposed ARMPC is designed to track the so-called virtual references instead of the actual references. Subsequently, additional tuning is not required for different operating conditions. In this paper, ARMPC is applied to a single-phase full-bridge voltage source inverter (VSI). It is experimentally validated that ARMPC exhibits strength in substantially eliminating the residual errors in environment of model mismatch, load change, and input voltage change, which would otherwise be present under MPC control. Moreover, it is experimentally demonstrated that the proposed ARMPC shows a consistent erasion of steady-state errors, while the MPC with integrator performs inconsistently for different cases of model mismatch after a fixed tuning of the weighting factor

Fast model predictive control for hydrogen outflow regulation in ethanol steam reformers

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In the recent years, the presence of alternative power sources, such as solar panels, wind farms, hydropumps and hydrogen-based devices, has significantly increased. The reasons of this trend are clear: contributing to a reduction of gas emissions and dependency on fossil fuels. Hydrogen-based devices are of particular interest due to their significant efficiency and reliability. Reforming technologies are among the most economic and efficient ways of producing hydrogen. In this paper we consider the regulation of hydrogen outflow in an ethanol steam reformer (ESR). In particular, a fast model predictive control approach based on a finite step response model of the process is proposed. Simulations performed using a more realistic non-linear model show the effectiveness of the proposed approach in driving the ESR to different operating conditions while fulfilling input and output constraints.Peer ReviewedPostprint (author's final draft