Optimal Closed Loop Control of G2V/V2G Action Using Model Predictive Controller

This paper has developed a closed-loop control algorithm to operate the G2V/V2G action, tested under varying battery voltage conditions and load and source power differences. Under V2G action, to maintain total harmonic distortion under minimum level and grid frequency under the standard limit, a Model predictive controller (MPC) has been used to control the gate driver circuit of the inverter. The state space model of the plant has been created using the system identification toolbox, and the MPC Controller block has been designed using the Model Predictive Control Toolbox of MATLAB. The proposed methodology is tested using MATLAB/Simulink and OPAL-RT (OP4510) in a real-time environment. This methodology reduces %THD to less than 0.5%, improves waveform quality of grid voltage, inverter output voltage, grid current, and inverter output current to nearly 99%, and maintains the grid frequency in standard limit while in G2V/V2G action

Model-Free Predictive Current Control of a Voltage Source Inverter

Indexación: Scopus.Conventional model predictive control (MPC) of power converter has been widely applied to power inverters achieving high performance, fast dynamic response, and accurate transient control of power converter. However, the MPC strategy is highly reliant on the accuracy of the inverter model used for the controlled system. Consequently, a parameter or model mismatch between the plant and the controller leads to a sub-optimal performance of MPC. In this paper, a new strategy called model-free predictive control (MF-PC) is proposed to improve such problems. The presented approach is based on a recursive least squares algorithm to identify the parameters of an auto-regressive with exogenous input (ARX) model. The proposed method provides an accurate prediction of the controlled variables without requiring detailed knowledge of the physical system. This new approach and is realized by employing a novel state space identification algorithm into the predictive control structure. The performance of the proposed model-free predictive control method is compared with conventional MPC. The simulation and experimental results show that the proposed method is totally robust against parameters and model changes compared with the conventional model based solutions.https://ieeexplore.ieee.org/document/926284

Finite control set model predictive control for grid-tied quasi-Z-source based multilevel inverter

In this paper, a finite control set Model Predictive Control (MPC) for grid-tie quasi-Z-Source (qZS) based multilevel inverter is proposed. The proposed Power Conditioning System (PCS) consists of a single-phase 2-cell Cascaded H-Bridge (CHB) inverter where each module is fed by a qZS network. The aim of the proposed control technique is to achieve grid-tie current injection, low Total Harmonic Distortion (THD) current, unity power factor, while balancing DC-link voltage for all qZS-CHB inverter modules. The feasibility of this strategy is validated by simulation using Matlab/Simulink environment

Predictive current control with instantaneous reactive power minimization for a four-leg indirect matrix converter

This paper presents the experimental valida¬tion of a predictive current control strategy with minimiza¬tion of the instantaneous reactive input power for a Four-Leg Indirect Matrix Converter (4Leg-IMC). The topology includes an input matrix converter stage, which provides the dc voltage for a four-leg voltage source converter (VSC) output stage. The VSC’s fourth leg provides a path for the zero sequence load current. The control technique is based on a finite control set model predictive control (FCS-MPC) strategy, whereby the switching states for the input and out¬put converters are selected by evaluating a predictive cost function. This results in a simpler approach than that seen in other well-known modulation methods, such as three-dimensional space vector modulation (3D-SVM). Positive dc voltage, (a requirement for the safe operation of the IMC) and minimization of the instantaneous input reactive power are obtained, while maintaining good tracking of the load reference currents. Furthermore, soft switching is achieved by synchronizing the state changes in the input stage with the application of zero voltage space vectors in the inverter stage. The control strategy is experimentally verified using a laboratory prototype

Performance degradation of surface PMSMs with demagnetization defect under predictive current control

To control the current of a surface mounted permanent magnet synchronous machine fed by a two-level voltage source inverter, a large variety of control algorithms exists. Each of these controllers performs differently concerning dynamic performance and control- and voltage quality, but also concerning sensitivity to demagnetization faults. Therefore, this paper investigates the performance degradation of three advanced predictive controllers under a partial demagnetization fault. The three predictive controllers are: finite-set model based predictive control, deadbeat control, and a combination of both previous algorithms. To achieve this goal, the three predictive controllers are first compared under healthy conditions, and afterwards under a partial demagnetization fault. A PI controller is added to the comparison in order to provide a model-independent benchmark. Key performance indicators, obtained from both simulations and experimental results on a 4 kW axial flux permanent magnet synchronous machine with yokeless and segmented armature topology, are introduced to enable a quantification of the performance degradation of the controllers under a demagnetization fault. A general conclusion is that the deadbeat controller shows superior control quality, even under partial demagnetization

Three-phase four-wire shunt hybrid active power filter model with model predictive control in imbalance distribution networks

This paper presents a harmonic reduction and load imbalance model in a three-phase four-wire distribution network. This model uses a hybrid active power filter, a passive inductor and capacitor filter, and an active power filter in the form of a three-phase, four-leg connected grid inverter. The switching of the voltage source converter on this filter uses finite control set model predictive control (FCS-MPC). Control of this hybrid active power filter uses model predictive control (MPC) with a cost function, comparing the reference current and prediction current with mathematical modelling of the circuit. The reference current is taken from the load current by extracting dq, and the predicted current is obtained from the iteration of the voltage source converter (VSC) switching pattern. Each combination is compared with the reference current in the cost function to get the smallest error used as a power switching signal. Modelling was validated by using MATLAB Simulink. The simulation results prove a decrease in harmonics at a balanced load from 22.16% to 4.2% and at an unbalanced load, reducing the average harmonics to 4.74%. The simulation also decreases the load current imbalance in the distribution network. Reducing the current in the neutral wire from 62.01%-0.42% and 11.29-0.3 A

Modelling and simulation of voltage source converter with different control technique for offshore windfarm application

The uses of Voltage Source Converter is not something new in wind farm power generation. Advance technologies in rebuilding VSC that can control the output of alternating current (AC) through several current control technique produces from the wind energy, sometime lead to distortion that can disturb another component whether in VSC itself or effecting another equipment. In wind farm power generation, power VSC commonly used in order to deal with large value of voltage and current produced from wind energy. Hence, more electronic device and components will be used to deal with this situation. This is to some extent will create disturbances to the system that will not be seen through human naked eye. Through this paper, a conventional current control method, that is linear PWM is present. This method is much more complicated compare to proposed method, that is predictive current control. The function of multi predictive control (MPC) in determining the future value for the feedback signal into inverter is explained in 4.3. The result of this two method is analyse in aspect of total harmonic distortion (THD) for both voltage and current during transient state and steady state. During transient state for current, both of the methods exceed the IEEE-519 standards. Hence it is recommend to install several equipments to protect the facility of windfarm itself. While for steady state, both of the methods succeed maintain the THD below 5% for voltage and current

Predictive control of a single phase current source-fed multilevel converter

In this work, a single-phase multilevel current source DC/AC converter with sinusoidal output is presented. The voltage waveform is achieved by using the stepped current waveform of the multilevel current inverter and a single capacitor at the output. The proposed controller is based on the Finite-Control Set Predictive Control approach and regulates the output voltage simultaneously with the DC current on the converter’s internal inductor. The synthesis of a multilevel current at the output of the converter jointly with a single capacitor allows one to obtain a high quality output voltage at steady state with fast transient response capability without resonances.Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señale

A predictive control with flying capacitor balancing of a multicell active power filter

Unlike traditional inverters, multicell inverters have the following advantages: lower switching frequency, high number of output levels, and less voltage constraints on the insulated-gate bipolar transistors. Significant performances are provided with this structure which is constituted with flying capacitors. This paper deals with a predictive and direct control applied to the multicell inverter for an original application of this converter: a three-phase active filter. To take advantage of the capabilities of the multicell converter in terms of redundant control states, a voltage control method of flying capacitor is added, based on the use of a switching table. Flying capacitor voltages are kept on a fixed interval, and precise voltage sensors are not necessary. The association of predictive control and voltage balancing increases considerably the bandwidth of the active filter

A Novel Reduced Components Model Predictive Controlled Multilevel Inverter for Grid-Tied Applications

This paper presents an improved single-phase Multilevel Inverter (MLI) which is conceptualized to reduce power switches along with separate DC voltage sources. Compared with recent modular topologies, the proposed MLI employs a reduced number of components. The proposed inverter consists of a combination of two circuits, i.e., the level generation and polarity generation parts. The level generation part is used to synthesize different output voltage levels, while the polarity inversion is performed by a~conventional H-bridge circuit. The performance of the proposed topology has been studied using s single-phase seven-level inverter, which utilizes seven power switches and three independent DC voltage sources. Model Predictive Control (MPC) is applied to inject a sinusoidal current into the utility grid which exhibits low Total Harmonic Distortion (THD). Tests, including a~change in grid current amplitude as well as operation under variation in Power Factor (PF), have been performed to validate the good performance obtained using MPC. The effectiveness of the proposed seven-level inverter has been verified theoretically using MATLAB Simulink. In addition, Real-Time (RT) validation using the dSPACE-CP1103 has been performed to confirm the system performance and system operation using digital platforms. Simulation and RT results show improved THD at 1.23% of injected current