Model Predictive Power Control Method Research Articles

High Precision Model Predictive Power Control Method for Battery Energy-Stored Quasi Z-Source Inverter

High Precision Model Predictive Power Control Method for Battery Energy-Stored Quasi Z-Source Inverter

Model Predictive Power Control of Grid-Connected Quasi Single-Stage Converters for High-Efficiency Low-Voltage ESS Integration

The grid-connected quasi-single-stage converter (QSSC) provides a direct power flow path from low-voltage (LV) energy storage systems (ESS) to ac–dc converters, resulting in reduced power conversion stage for high-efficiency ESS integration. However, due to the dc-link voltage ratio between the two ports varies with the ESS state of charge, the voltage vectors in the ac side are unevenly distributed in the QSSC. This nonlinearity brings some challenges in control and modulation design for the ac–dc part of QSSC. In this article, a virtual two-level converter model considering the two ports as a single dc source is proposed, and model predictive power control (MPPC) based on the virtual two-level model is proposed to enhance the grid current performance. The duty cycle of each phase is calculated based on the active and reactive power tracking error minimization in the two-level converter frame, and the duty cycle for each switching pair is obtained by minimizing the power processed by the dc–dc converter. In this way, the complicated implementation of MPPC for a three-level converter is avoided, and the controller design of the QSSC can be simplified. The effectiveness of the proposed virtual two-level converter model and MPPC method are verified with experimental results.

Model Predictive Power Control for Bidirectional Series-Resonant Isolated DC–DC Converters With Fast Dynamic Response in Locomotive Traction System

High-frequency bidirectional dual-bridge series-resonant dc–dc converters have been attracted more attention in power electronic transformer (PET) due to high power density and efficiency. In this article, a model predictive power control method with phase shift modulation is proposed, to improve the dynamic response and robustness of the converter without load current sensor. In addition, the proposed method is insensitive to the resonant parameters in the adopted converter and can keep excellent dynamic characteristics even if the resonant parameter deviates from the desired operating point, which indicates good robustness. Effectiveness of the proposed control is verified on a 400-W scale-down experimental prototype with resistance load and inverter load, respectively. Compared with traditional voltage loop control and model predictive voltage control schemes, the proposed scheme can achieve a faster dynamic response of the output voltage in load and input voltage step change.

Model predictive power control for a fault‐tolerant grid‐connected converter using reconstructed currents

The reliability and stability of a grid-connected converter is vital to the power conversion system. The faults of switching device and current sensor lead to operation failure for a grid-connected converter. An improved model predictive power control (MPPC) based on reconstructed currents is proposed for fault-tolerant operation of a grid-connected converter. Firstly, the three-phase currents are reconstructed using the sampled dc current and normal sensor information according to the relationship between the voltage vector and output currents. Secondly, the predictive power model is built based on fault-tolerant three-phase four-switch topology. Then the reconstructed current is used for the MPPC method. To keep the balance of dc capacitor voltages, the cost function is optimised and the switching vector, which minimises the cost function, is applied to the fault-tolerant converter. Finally, the experiment platform and simulation models are built to verify the proposed method. The results show that the proposed MPPC using reconstructed currents can keep the fault-tolerant operation of the grid-connected converter with sinusoidal currents and stable output power. The proposed method achieves the fault-tolerant operation under switching device and ac current sensor fault, which improve the reliability of the system.

A Model Predictive Power Control Method for PV and Energy Storage Systems With Voltage Support Capability

The cascaded control method with an outer voltage loop and an inner current loop has been traditionally employed for the voltage and power control of photovoltaic (PV) inverters. This method, however, has very limited power regulation capability. With the fast increasing penetration of PV power generation systems in the distribution network, the voltage rise/drop has become a serious problem impacting negatively on the power quality and grid stability. Therefore, flexible power regulation is highly desired for PV inverters to provide ancillary services. This paper proposes a novel model predictive power control (MPPC) scheme to control and coordinate the dc–dc converter and inverter for grid-connected PV systems with energy storage systems (ESS). By regulating the dc-bus voltage and controlling the active and reactive power flows, MPPC can support the power grid to maintain stable voltage and frequency and improve the power factor. Numerical simulation and controller hardware-in-the-loop (CHIL) testing have been conducted on a PV-ESS system to verify the capability and effectiveness of the proposed control strategy.