Model Predictive Voltage Control Based on Finite Control Set With Computation Time Delay Compensation for PV Systems

Jin, Tao; Shen, Xueyu; Su, Taixin; Flesch, Rodolfo C.C.

doi:10.1109/tec.2018.2876619

Cited by 59 publications

(30 citation statements)

References 27 publications

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“…( 1) ( ) kk  + = + X Ψ X Θ U (10) where, Eq. (10) is the discrete mathematical model in d-q coordinate system, in (12), the TS is the sampling period of the system, in (13), the ꞷ is the phase angle detected by PLL. When APF is used to compensate harmonic and reactive power, it must be detected first, including FFT, FBD, PQ method, and so on.…”

Section: Discrete Mathematical Model Of Three-phase Apfmentioning

confidence: 99%

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A Novel Multi-vector Model Predictive Current Control of Three-Phase Active Power Filter

Li¹,

Liu²,

Qi³

et al. 2021

EJEE

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This paper proposes the application of a novel finite control set model predictive control (FCS-MPC) strategy in active power filter (APF). In the process of APF compensating harmonic and reactive power, the traditional single vector model predictive current control (MPCC) has low tracking accuracy to harmonic current, while the multi-vector MPCC has the problems of complex calculation and long calculation time, a new multi-vector MPCC control method has proposed in this paper. Firstly, the harmonic reference value is transformed into d-q coordinate system, according to the sector, the slope is calculated and the action time is obtained. Six new expected vectors are synthesized from six effective vectors and zero vectors. The value function is established to loop and calculate the optimal virtual vector, which is applied to APF. Compared with single vector control and traditional multi-vector control, it has a wider vector action area and faster calculation speed. The compensation results and dynamic performance are improved. The simulation results show that the total harmonic distortion (THD) is low.

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Section: Discrete Mathematical Model Of Three-phase Apfmentioning

confidence: 99%

“…For the problems existing in the control method of FCS-MPC, many scholars in related fields have proposed different improved control methods based on FCS-MPC [6,10,11,12]. Studies [13] have looked at a model predictive control method with time-delay compensation is proposed. The reference current is predicted by Lagrange interpolation.…”

Section: Introductionmentioning

confidence: 99%

A Novel Multi-vector Model Predictive Current Control of Three-Phase Active Power Filter

Li¹,

Liu²,

Qi³

et al. 2021

EJEE

View full text Add to dashboard Cite

show abstract

“…The sample period is the same as the switching period used in the PWM. Thus, a time delay of one sample was included in the model to compensate for the computation time delay [31].…”

Section: Simulation Case Studymentioning

confidence: 99%

“…The discretisation was done assuming a zero-order hold model for the inputs and the sample period was chosen as T s = 100 s. The sample period is the same as the switching period used in the PWM. Thus, a time delay of one sample was included in the model to compensate for the computation time delay [31].…”

Section: Simulation Case Studymentioning

confidence: 99%

Fast algorithms for constrained generalised predictive control with on‐line optimisation

Peccin

Lima

Flesch

et al. 2020

IET Control Theory & Appl

Self Cite

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This paper proposes fast algorithms for constrained generalised predictive control based on two first-order methods, namely accelerated dual gradient projection method and fast alternating minimisation algorithm. Theoretical bounds on the number of iterations, which play an important role in the context of real-time model predictive controllers, are provided for both algorithms. Also, some implementation issues in parallel architectures are discussed. The methods are firstly validated by simulation and their results are compared with the ones presented by commercial solvers. A three-phase grid-connected LCL-filtered inverter was used as a case study. The algorithms were evaluated in an FPGA with the quadratic program computed in microseconds.

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“…The model predictive control approach is an advanced high-performance design technique which is known to be a very efficient method of controlling complex [23]- [25], and non-minimum-phase systems [26], [27]. The simplicity, conceptual easiness and accurate tracking performance of MPC approach have led to widespread successful applications, such as energy and power systems [28]- [30], aero-space [31], [32], and automotive control [33], [34].…”

Section: Introductionmentioning

confidence: 99%

Gas Turbines Power Regulation Subject to Actuator Constraints, Disturbances and Measurement Noises

et al. 2021

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An accurate understanding of the output power functionality in gas turbines concerning the fuel, inlet valve status and other parameters can provide a general overview of the turbine's performance. In this study, the problem of practical power regulation in gas turbines is investigated in the simultaneous presence of actuator constraints, unknown disturbances, and measurement noises. To this aim, a model predictive controller-based approach is utilized because of its high flexibility combined with a twolayer filtering and anti-filtering procedure to efficiently cope with the measurement noises. Moreover, the proposed structure takes the effects of unknown disturbances into account and thereby it is shown that the proposed controller can efficiently achieve all design objectives while handling actuator constraints, disturbances and measurement noises.

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Model Predictive Voltage Control Based on Finite Control Set With Computation Time Delay Compensation for PV Systems

Cited by 59 publications

References 27 publications

A Novel Multi-vector Model Predictive Current Control of Three-Phase Active Power Filter

A Novel Multi-vector Model Predictive Current Control of Three-Phase Active Power Filter

Fast algorithms for constrained generalised predictive control with on‐line optimisation

Gas Turbines Power Regulation Subject to Actuator Constraints, Disturbances and Measurement Noises

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