基于双矢量的并网逆变器无模型预测电流控制策略

doi:10.19595/j.cnki.1000-6753.tces.221461

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Abstract Grid-connected inverters are crucial interfaces in renewable energy systems, such as photo- voltaic power generation systems, wind power generation systems, and energy storage systems. In order to improve the system performance, it is important to regulate the output current of an inverter with a small ripple and low total harmonic distortion (THD) to meet grid connection requirements. Model predictive current control (MPCC) schemes have been well developed in grid-connected inverters due to many advantages, such as high-speed response, straightforward constraint handling, multi-objective control capability, and simple implementation. However, their performances are affected by the accuracy of system parameters. Recently, a model-free predictive current control (MFPCC) scheme based on look-up tables (LUTs) has been reported for permanent magnet synchronous motors, where sixteen current gradients generated by eight basic voltage vectors are stored and updated for current predictions. Compared to the MPCC schemes, MFPCC schemes do not require system models and can be easily implemented. This conventional scheme only updates the current gradient of the applied voltage vector in each control period which causes long stagnation and large current ripple and THD. This paper proposes a double-vector MFPCC (DV-MFPCC) scheme to deal with the issues arising from conventional MFPCC schemes.
Firstly, the proposed scheme can reduce current ripple and THD due to the utilization of two voltage vectors. The duration of two voltage vectors is calculated based on the principle that they are inversely proportional to the cost function. Furthermore, an advanced and simplified current gradient updating method is proposed to eliminate the stagnation effect and reduce the calculation burden. The current gradients of the two voltage vectors are calculated based on the durations of the two. Other current gradients of the remaining six voltage vectors are updated by establishing a relationship of current gradients.
Simulation results on the current gradient updating show that when the proposed DV-MFPCC scheme is applied, the stagnation effect is eliminated because the current gradients for all the vectors are updated in each control period. There are five curves under α-axis and three curves under β-axis since Δi_2α=Δi_6α, Δi_3α=Δi_5α, Δi_0α=Δi_7α, Δi_2β=Δi_3β, Δi_5β=Δi_6β and Δi_0β=Δi_7β=Δi_4β=Δi_1β. Experimental results on the proper model parameters show that the THD of the output current is reduced from 9.73 % to 4.74 % for the SV-MFPCC, the THD of the output current is reduced from 5.83 % to 2.87 % for the DV-MPCC, and the THD is reduced from 6.10 % to 3.03 % for the proposed scheme. As a result, the performance is verified similarly to the DV-MPCC and better than the SVV-MFPCC. Experimental results on the inaccurate model parameters show that when the controller parameter mismatches the actual parameter, the proposed DV-MFPCC produces a smaller THD than the DV-MPCC. Hence, the parameter robustness of the proposed scheme can be verified. Experimental results on the different updating methods show that the proposed updating method can improve current performance effectively.
The following conclusions can be drawn from the simulation and experimental analysis: (1) Two voltage vectors are utilized in each control period to reduce the ripple and THD of the output current. (2) It is independent of model parameters and avoids the influence of parameter mismatches, achieving similar control performance to DV-MPCC with accurate model parameters. (3) An advanced current gradient updating method with simple calculation is applied to eliminate the stagnation effect.
In future work, it is necessary to achieve the fixed switching frequency control, further reduce current ripples based on some advanced algorithms, and apply the proposed MFPCC in the higher-order system and multi-level inverter system.

Key words： Grid-connected inverter model-free predictive current control double-vector current gradient updating

Received: 28 July 2022

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	Rui Tao
	Yin Zheng
	Wang Fengxiang
	Lu Geye
	Li Zhen

Cite this article:

Rui Tao,Yin Zheng,Wang Fengxiang等. Model-Free Predictive Current Control Strategy of Grid-Connected Inverter Based on Double-Vector[J]. Transactions of China Electrotechnical Society, 2023, 38(14): 3759-3768.

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