Research on Mixed Logic Dynamic Modeling and Finite Control Set Model Predictive Control of Multi-Inverter Parallel System

Parallel connection of multiple inverters is an important means to solve the expansion,reserve and protection of distributed power generation,such as photovoltaics.In view of the shortcomings of traditional droop control methods such as weak anti-interference ability,low tracking accuracy of inverter output voltage and serious circulation phenomenon,a finite control set model predictive control(FCS-MPC)strategy of microgrid multiinverter parallel system based on Mixed Logical Dynamical(MLD)modeling is proposed.Firstly,the MLD modeling method is introduced logical variables,combining discrete events and continuous events to form an overall differential equation,which makes the modeling more accurate.Then a predictive controller is designed based on the model,and constraints are added to the objective function,which can not only solve the real-time changes of the control system by online optimization,but also effectively obtain a higher tracking accuracy of the inverter output voltage and lower total harmonic distortion rate(Total Harmonics Distortion,THD);and suppress the circulating current between the inverters,to obtain a good dynamic response.Finally,the simulation is carried out onMATLAB/Simulink to verify the correctness of the model and the rationality of the proposed strategy.This paper aims to provide guidance for the design and optimal control of multi-inverter parallel systems.

Research on AC Electronic Load with Energy Recovery Based on Finite Control Set Model Predictive Control

Nowadays,AC electronic loads with energy recovery are widely used in the testing of uninterruptible power supplies and power supply equipment.To tackle the problems of control difficulty,strategy complexity,and poor dynamic performance of AC electronic load with energy recovery of the conventional control strategy,a control strategy of AC electronic load with energy recovery based on Finite Control Set Model Predictive Control(FCSMPC)is developed.To further reduce the computation burden of the FCS-MPC,a simplified FCS-MPC with transforming the predicted variables and using sector to select expected state is proposed.Through simplified model and equivalent approximation analysis,the transfer function of the system is obtained,and the stability and robustness of the system are analyzed.The performance of the simplified FCS-MPC is compared with space vector control(SVPWM)and conventional FCS-MPC.The results show that the FCS-MPC method performs better dynamic response and this advantage is more obvious when simulating high power loads.The simplified FCS-MPC shows similar control performance to conventional FCS-MPC at less computation burden.The control performance of the system also shows better simulation results.

Finite-Control-Set Model Predictive Control of Permanent Magnet Synchronous Motor Drive Systems——An Overview

Permanent magnet synchronous motors(PMSMs)have been widely employed in the industry. Finite-control-set model predictive control(FCS-MPC), as an advanced control scheme, has been developed and applied to improve the performance and efficiency of the holistic PMSM drive systems. Based on the three elements of model predictive control, this paper provides an overview of the superiority of the FCS-MPC control scheme and its shortcomings in current applications. The problems of parameter mismatch, computational burden, and unfixed switching frequency are summarized. Moreover, other performance improvement schemes, such as the multi-vector application strategy, delay compensation scheme, and weight factor adjustment, are reviewed. Finally, future trends in this field is discussed, and several promising research topics are highlighted.

DC active power filter based on model predictive control for DC bus overvoltage suppression of accelerator grid power supply

The China Fusion Engineering Test Reactor plans to build a 200 k V/25 A acceleration grid power supply(AGPS)for the negative-ion-based neutral beam injector prototype system.The AGPS uses a rectifier-inverter-isolated step-up structure.There is a DC bus between the rectifier and the inverter.In order to limit DC bus voltage ripple and transient fluctuations,a large number of capacitors are used,which degrades the reliability of the power supply and occupies a large amount of space.This work finds that due to the difference in the turn-off time of the rectifier and the inverter,the capacitance mainly depends on the rectifier current when the inverter is turned off.On this basis,an active power filter(APF)scheme is proposed to absorb the current.To enhance the dynamic response ability of the APF,model predictive control is adopted.In this paper,the circuit structure of the APF is introduced,the prediction model is deduced,the corresponding control strategy and signal detection method are proposed,and the simulation and experimental results show that APF can track the transient current of the DC bus and reduce the voltage fluctuation significantly.

Model Predictive Control Strategy of Multi-Port Interline DC Power Flow Controller

There are issues with flexible DC transmission system such as a lack of control freedom over power flow.In order to tackle these issues,a DC power flow controller(DCPFC)is incorporated into a multi-terminal,flexible DC power grid.In recent years,a multi-port DC power flow controller based on a modular multi-level converter has become a focal point of research due to its simple structure and robust scalability.This work proposes a model predictive control(MPC)strategy for multi-port interline DC power flow controllers in order to improve their steady-state dynamic performance.Initially,the mathematical model of a multi-terminal DC power grid with a multi-port interline DC power flow controller is developed,and the relationship between each regulated variable and control variable is determined;The power flow controller is then discretized,and the cost function and weight factor are built with numerous control objectives.Sub module sorting method and nearest level approximation modulation regulate the power flow controller;Lastly,theMATLAB/Simulink simulation platformis used to verify the correctness of the establishedmathematicalmodel and the control performance of the suggestedMPC strategy.Finally,it is demonstrated that the control strategy possesses the benefits of robust dynamic performance,multiobjective control,and a simple structure.

Finite Control Set Model Predictive Current Control of a Five-Phase PMSM with Virtual Voltage Vectors and Adaptive Control Set

This paper presents an improved finite control set model predictive current control(FCS-MPCC)of a five-phase permanent magnet synchronous motor(PMSM).First,to avoid including all the 32 voltage vectors provided by a two-level five-phase inverter into the control set,virtual voltage vectors are adopted.As the third current harmonics can be much reduced by virtual voltage vectors automatically,the harmonic items in the cost function of conventional FCS-MPCC are not considered.Furthermore,an adaptive control set is proposed based on voltage prediction.Best control set with proper voltage vector amplitude corresponding to different rotor speed can be achieved by this method.Consequently,current ripples can be largely reduced and the system performs much better.At last,simulations are established to verify the steady and transient performance of the proposed FCS-MPCC,and experiments based on a 2 kW five-phase motor are carried out.The results have validated the performance improvement of the proposed control strategy.

Distributed Model Predictive Load Frequency Control of Multi-area Power System with DFIGs

Reliable load frequency control LFC is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-Area interconnected power system with wind turbines, this paper presents a distributed model predictive control DMPC based on coordination scheme. The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The generation rate constraints GRCs, load disturbance changes, and the wind speed constraints are considered. Furthermore, the DMPC algorithm may reduce the impact of the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and without the participation of the wind turbines is carried out. Analysis and simulation results show possible improvements on closed-loop performance, and computational burden with the physical constraints. © 2014 Chinese Association of Automation.

Model-predictive control of power supply for particle accelerators

In this paper, model-predictive control(MPC) is proposed for controlling power source of accelerators. The system state equation is employed as the predictive model. With MPC, the difference between possible output and the ideal output is forecasted and decreased, so that the system can trace the ideal trail as closely and quickly as possible. The results of simulations and experiments show that this method can reduce influence of low frequency noise.

Finite control set model predictive control of three-port converter for interfacing a PV-battery energy storage system to a three-phase stand-alone AC system

This paper proposes a multiport bidirectional non-isolated converter topology that provides advantages in terms of simultaneous multiple operations,single-stage conversion,high power density and reduced power losses due to the lower number of switches.The proposed multiport converter uses a centralized non-linear controller known as a finite control set model predictive controller to manage the flow of power between different ports.It deals with the parallel operation of photovoltaic and battery energy storage systems for stand-alone alternating current(AC)systems.The converter connects the lower voltage battery to the photovoltaic port using a bidirectional buck/boost converter and the photovoltaic port is linked to the stand-alone AC load through a three-phase full-bridge inverter.Each leg of the three-phase converter will act as a bidirectional direct current(DC)/DC converter as well as an inverter simultaneously.Only six switches manage the power transfer between all the connected ports of photovoltaic-battery energy storage system linked to the stand-alone AC load.The proposed multiport converter is mathematically modelled and controlled by a finite control set model predictive controller.The system is validated in simulation(1-kW rating)and experimental environment(200-W rating).The hardware prototype is developed in the laboratory and the controller is implemented on the field-programmable gate array board.Two independent case studies are carried out to validate the efficacy of the system.The first scenario is for a change in solar irradiance,while the second scenario is for a change in the output load.

Development and Application of a Power Law Constitutive Model for Eddy Current Dampers

Eddy current dampers (ECDs) have emerged as highly desirable solutions for vibration control due to theirexceptional damping performance and durability. However, the existing constitutive models present challenges tothe widespread implementation of ECD technology, and there is limited availability of finite element analysis (FEA)software capable of accurately modeling the behavior of ECDs. This study addresses these issues by developing anewconstitutivemodel that is both easily understandable and user-friendly for FEAsoftware. By utilizing numericalresults obtained from electromagnetic FEA, a novel power law constitutive model is proposed to capture thenonlinear behavior of ECDs. The effectiveness of the power law constitutive model is validated throughmechanicalproperty tests and numerical seismic analysis. Furthermore, a detailed description of the application process ofthe power law constitutive model in ANSYS FEA software is provided. To facilitate the preliminary design ofECDs, an analytical derivation of energy dissipation and parameter optimization for ECDs under harmonicmotionis performed. The results demonstrate that the power law constitutive model serves as a viable alternative forconducting dynamic analysis using FEA and optimizing parameters for ECDs.

Model Predictive Control-Based Direct Torque Control for Matrix Converter-Fed Induction Motor with Reduced Torque Ripple

To reduce the torque ripple in motors resulting from the use of conventional direct torque control(DTC),a model predictive control(MPC)-based DTC strategy for a direct matrix converter-fed induction motor is proposed in this paper.Two new look-up tables are proposed,these are derived on the basis of the control of the electromagnetic torque and stator flux using all the feasible voltage vectors and their associated switching states.Finite control set model predictive control(FCS-MPC)has then been adopted to select the optimal switching state that minimizes the cost function related to the electromagnetic torque.Finally,the experimental results are shown to verify the reduced torque ripple performance of the proposed MPC-based DTC method.

DISOPE distributed model predictive control of cascade systems with network communication

A novel distributed model predictive control scheme based on dynamic integrated system optimization and parameter estimation （DISOPE） was proposed for nonlinear cascade systems under network environment. Under the distributed control structure, online optimization of the cascade system was composed of several cascaded agents that can cooperate and exchange information via network communication. By iterating on modified distributed linear optimal control problems on the basis of estimating parameters at every iteration the correct optimal control action of the nonlinear model predictive control problem of the cascade system could be obtained, assuming that the algorithm was convergent. This approach avoids solving the complex nonlinear optimization problem and significantly reduces the computational burden. The simulation results of the fossil fuel power unit are illustrated to verify the effectiveness and practicability of the proposed algorithm.

Model Predictive Current Control for Low-Cost Shunt Active Power Filter

Performance of a three-phase shunt active power filter(SAPF)relies on the capability of the controller to track the reference current.Therefore,designing an accurate current controller is crucial to guarantee satisfactory SAPF operation.This paper presents a model predictive current controller(MPCC)for a low-cost,four-switch,shunt active power filter for power quality improvement.A four-switch,B4,converter topology is adopted as an SAPF,hence offering a simple,robust,and low-cost solution.In addition,to further reduce overall cost,only two interfacing filter inductors,instead of three,are used to eliminate switching current ripple.The proposed SAPF model MPCC is detailed for implementation,where simulation and experimental results validate effectiveness of the proposed control algorithm showing a 20%improvement in total harmonic distortion compared with a conventional hysteresis band current controller.

Nonlinear Model Predictive Controller for Compensations of Single Line-to-ground Fault in Resonant Grounded Power Distribution Networks

An nonlinear model predictive controller(NMPC)is proposed in this paper for compensations of single line-to-ground(SLG)faults in resonant grounded power distribution networks(RGPDNs),which reduces the likelihood of power line bushfire due to electric faults.Residual current compensation(RCC)inverters with arc suppression coils(ASCs)in RGPDNs are controlled using the proposed NMPC to provide appropriate compensations during SLG faults.The proposed NMPC is incorporated with the estimation of ASC inductance,where the estimation is carried out based on voltage and current measurements from the neutral point of the power distribution network.The compensation scheme is developed in the discrete time using the equivalent circuit of RGPDNs.The proposed NMPC for RCC inverters ensures that the desired current is injected into the neutral point during SLG faults,which is verified through both simulations and control hardware-in-the-loop(CHIL)validations.Comparative results are also presented against an integral sliding mode controller(ISMC)by demon-strating the capability of power line bushfire mitigation.

Fuzzy disturbance rejection predictive control of ultra-supercritical once-through boiler-turbine unit

In order to overcome the wide-range load tracking and unknown disturbance issues of an ultra-supercritical boiler- turbine unit, a fuzzy disturbance rejection predictive control approach is proposed using the techniques of fuzzy scheduling, model predictive control and extended state observer. Local state-space models are established on the basis of nonlinearity analysis and subspace identification. To eiJiance thedisturbance rejection capability of the controller, a extended state observer is employed to estimate unnown disturbances and model mismatches. The disturbance estimation ennaced local predictive controllers ae subsequently devised based on the local models, the performance of which is further strengthened by incorporating the fuzzy scheduling technique. The simulation results verify the merits of the proposed strategy in achieving satisfactory wide-range load tracking ad disturbance rejection performance.

Tube Model Predictive Control Based Cyber-attack-resilient Optimal Voltage Control Strategy in Wind Farms

Optimal voltage controls have been widely applied in wind farms to maintain voltage stability of power grids.In order to achieve optimal voltage operation,authentic grid information is widely needed in the sensing and actuating processes.However,this may induce system vulnerable to malicious cyber-attacks.To this end,a tube model predictive control-based cyber-attack-resilient optimal voltage control method is proposed to achieve voltage stability against malicious cyber-attacks.The proposed method consists of two cascaded model predictive controllers(MPC),which outperform other peer control methods in effective alleviation of adverse effects from cyber-attacks on actuators and sensors of the system.Finally,efficiency of the proposed method is evaluated in sensor and actuator cyber-attack cases based on a modified IEEE 14 buses system and IEEE 118 buses system.Index Terms-Attack-resilient control,optimal voltage control,tube-based model predictive control,wind farm-connected power system.

Multi-timescale optimization scheduling of interconnected data centers based on model predictive control

With the promotion of“dual carbon”strategy,data center(DC)access to high-penetration renewable energy sources(RESs)has become a trend in the industry.However,the uncertainty of RES poses challenges to the safe and stable operation of DCs and power grids.In this paper,a multi-timescale optimal scheduling model is established for interconnected data centers(IDCs)based on model predictive control(MPC),including day-ahead optimization,intraday rolling optimization,and intraday real-time correction.The day-ahead optimization stage aims at the lowest operating cost,the rolling optimization stage aims at the lowest intraday economic cost,and the real-time correction aims at the lowest power fluctuation,eliminating the impact of prediction errors through coordinated multi-timescale optimization.The simulation results show that the economic loss is reduced by 19.6%,and the power fluctuation is decreased by 15.23%.

Hierarchical Cluster Coordination Control Strategy for Large-scale Wind Power Based on Model Predictive Control and Improved Multi-time-scale Active Power Dispatching

The grid-connection of large-scale and high-penetration wind power poses challenges to the friendly dispatching control of the power system.To coordinate the complicated optimal dispatching and rapid real-time control,this paper proposes a hierarchical cluster coordination control(HCCC)strategy based on model predictive control(MPC)technique.Considering the time-varying characteristics of wind power generation,the proposed HCCC strategy constructs an improved multitime-scale active power dispatching model,which consists of five parts:formulation of cluster dispatching plan,rolling modification of intra-cluster plan,optimization allocation of wind farm(WF),grouping coordinated control of wind turbine group(WTG),and real-time adjustment of single-machine power.The time resolutions are sequentially given as 1 hour,30 min,15 min,5 min,and 1 min.In addition,a combined predictive model based on complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN),wavelet thresholding(WT),and least squares support vector machine(LSSVM)is established.The fast predictive feature of this model cooperates with the HCCC strategy that effectively improves the predictive control precision.Simulation results show that the proposed HCCC strategy enables rapid response to active power control(APC),and significantly improves dispatching control accuracy and wind power accommodation capabilities.

Wind Farm Coordinated Control for Power Optimization

以降低风电场尾流损失、优化风场出力为目标,设计基于Laguerre函数非线性预测控制（nonlinear modelpredictive control,NLMPC）方案的风场集群控制器。该控制器应用风场动态尾流模型,通过NLMPC统一调整风场内各机组转速以提升风场功率。在控制器设计中,使用有效风速预测误差校正对预测模型失配及超短期风速预测误差进行补偿,引入Laguerre函数降低滚动时域优化计算负担并分析了控制器对风速预测误差的鲁棒性能。仿真研究表明,集群控制器能够在不同风速条件下提升风场功率、降低优化计算负担,且对风速预测模型失配与风场自然风速预测误差具有鲁棒性。

PI-MPC Frequency Control of Power System in the Presence of DFIG Wind Turbines

For the recent expansion of renewable energy applications, Wind Energy System (WES) is receiving much interest all over the world. However, area load change and abnormal conditions lead to mismatches in frequency and scheduled power interchanges between areas. These mismatches have to be corrected by the LFC system. This paper, therefore, proposes a new robust frequency control technique involving the combination of conventional Proportional-Integral (PI) and Model Predictive Control (MPC) controllers in the presence of wind turbines (WT). The PI-MPC technique has been designed such that the effect of the uncertainty due to governor and turbine parameters variation and load disturbance is reduced. A frequency response dynamic model of a single-area power system with an aggregated generator unit is introduced, and physical constraints of the governors and turbines are considered. The proposed technique is tested on the single-area power system, for enhancement of the network frequency quality. The validity of the proposed method is evaluated by computer simulation analyses using Matlab Simulink. The results show that, with the proposed PI-MPC combination technique, the overall closed loop system performance demonstrated robustness regardless of the presence of uncertainties due to variations of the parameters of governors and turbines, and loads disturbances. A performance comparison between the proposed control scheme, the classical PI control scheme and the MPC is carried out confirming the superiority of the proposed technique in presence of doubly fed induction generator (DFIG) WT.