Optimal indirect model predictive control for single‑phase two‑level shunt active power filters

Roberto Morales-Caporal

Optimal indirect model predictive control for single‑phase two‑level shunt active power filters

Roberto Morales-Caporal

Vol. 22, No. 1, pp. 84-93, Jan. 2022

10.1007/s43236-021-00343-4

Active power filter

Digital signal controller

Model predictive control

Power inverter

Power quality

Abstract

In the conventional model predictive control (MPC) for single-phase two-level shunt active power filters (SP-2L-SAPFs), the voltage vector (VV) that is synthesized by the voltage source inverter (VSI) in the next control cycle is selected by the evaluation of a cost function. However, the application of a single VV, either an active VV (AVV) or a zero VV (ZVV), during the whole control cycle results in a grid current with a high ripple. To overcome this drawback, an optimized indirect MPC (IMPC) scheme that uses two VVs in each control cycle is proposed. The IMPC predicts the current slopes of all the VVs generated by the VSI. Then, it calculates the optimal on-time for each of the available AVVs. Two switching strategies are evaluated in this work to select the optimum ones for implementation. The final selection of a set of AVV and its on-time is carried out by evaluating the cost function as done in the MPC. To keep the voltage on the DC-link constant, a discrete-time fractional order PIλ controller is used. Simulation and experimental results obtained using a 10 kW SP-2L-SAPF prototype and a low-cost digital system verify the excellent performance of the proposed IMPC algorithm.

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Cite this article

[IEEE Style]

R. Morales-Caporal, "Optimal indirect model predictive control for single‑phase two‑level shunt active power filters," Journal of Power Electronics, vol. 22, no. 1, pp. 84-93, 2022. DOI: 10.1007/s43236-021-00343-4.

[ACM Style]

Roberto Morales-Caporal. 2022. Optimal indirect model predictive control for single‑phase two‑level shunt active power filters. Journal of Power Electronics, 22, 1, (2022), 84-93. DOI: 10.1007/s43236-021-00343-4.