Low-complexity model predictive control of a four-level active neutral point clamped inverter without weighting factors

The four-level active neutral point clamped(ANPC)inverter has become increasingly widely used in the renewable energy indus-try since it offers one more voltage level without increasing the total number of active switches compared to the three-level ANPC inverter.The model predictive current control(MPCC)is a promising control method for multi-level inverters.However,the conven-tional MPCC suffers from high computational complexity and tedious weighting factor tuning in multi-level inverter applications.A low-complexity MPCC without weighting factors for a four-level ANPC inverter is proposed in this paper.The computational burden and voltage vector candidate set are reduced according to the relationship between voltage vector and neutral point voltage balance.The proposed MPCC shows excellent steady-state and dynamics performances while ensuring the neutral point voltage balancing.The efficacy of the proposed MPCC is verified by simulation and experimental results.

Adaptive Neuro Fuzzy Inference System Based Decoupled Control for Neutral Point Clamped Multi Level Inverter Fed Induction Motor Dri

The presence of an integrator in a reference model of a rotor flux-based model reference adaptive system(RF-MRAS)and non-linearity of the inverter in the output voltage degrade the speed response of the sensorless operation of the electric drive system in terms of DC drift,initial value issues,and inaccurate voltage acquisition.To improve the speed response,a compensating voltage component is supplemented by an amending integrator.The compensating voltage is a coalition of drift and offset voltages,and reduces DC drift and initial value issues.During low-speed operation,inaccurate voltage acquisition distorts the stator voltage critically,and it becomes considerable when the stator voltage of the machine is low.Implementing a three-level neutral point clamped inverter in speed-sensorless decoupled control of an induction motor improves the performance of the drive with superior quality of inverter output voltage.Further,the performance of the induction motor drive is improved by replacing the proportional-integral(PI)controller in the adaption mechanism of RF-MRAS with an adaptive neuro-fuzzy inference system(ANFIS)controller.A prototype model of the three-level neutral point clamped inverter(3L-NPC)-fed induction motor drive is fabricated in a laboratory,and its performance for a RF-MRAS,modified RFMRAS,and modified RFMRAS using ANFIS are compared using different benchmark tests.

Improved VSVPWM Modulation Method for Three-level NPC Inverter in Rural Power Grid

With the acceleration of agricultural electrification,a lot of nonlinear and shock loads appear in the rural power grid,and the resulting harmonic and reactive currents pollute the rural power grid more and more seriously.To solve the above problem,three-level neutral point clamped(NPC)inverters have been widely used,but their development is greatly restricted by the defect of neutral point voltage imbalance.In this paper,an improved virtual space vector pulse width modulation(VSVPWM)was proposed.Firstly,the mathematical models of various space vectors were established,and the influence of various space vectors on neutral point voltage was analyzed.The sum of the vector current at the neutral point was zero and the voltage control at the neutral point was completed by.introducing the time offset into different switching times of the redundant small vector.This method was simple in design and avoided the redundant calculation of the traditional VSVPWM method and tedious switch sequence design.This balancing control strategy could greatly reduce the influence of virtual vectors on neutral point voltage and effectively control the low-frequency oscillation of neutral point voltage.The validity of the method was verified by establishing a matlab simulation model.

Unified power quality conditioner based on a three-level NPC inverter using fuzzy control techniques for all voltage disturbances compensation

This paper presents a novel and efficient control scheme for unified power quality conditioner （UPQC） based on three-level neutral point clamped （NPC） inverter using fuzzy logic techniques. The proposed UPQC is capable of mitigating source current harmonics and compensate all voltage disturbances such as voltage sags, swells, unbalances and harmonics. It is designed by the integration of series and shunt active filters （AFs） sharing a common DC bus capacitor. The DC voltage is maintained constant using proportional integral voltage controller. The synchronous reference frame （SRF） theory is used to get the reference signals for shunt active power filters （APFs） and the power reactive theory （p-q theory） for series APFs. The shunt and series APF reference signals derived from the control algorithm and sensed signals are injected in two controllers to generate switching signals. To improve the UPQC capability, fuzzy logic techniques are introduced to control the series APF. The performances of the proposed UPQC system are evaluated in terms of power factor correction, mitigation of voltage or current harmonics and all other voltage disturbances compensation using Matlab-Simulink software and SimPowerSystem toolbox. The simulation results illustrate the performance of the proposed UPQC at the common connection point of the nonlinear load to improve the power energy quality.