This article presents a systematic robust current control design approach for three-phase voltage-source converters. Robustness is guaranteed by combining intrinsic passive properties of the impedance uncertainty at the point of common coupling together with stability results from a passivity-based control theory. This approach ensures stability against typical uncertainty sources at mid and high frequencies, such as cable resonances or other converters interaction, with significant less conservative performances than the obtained with the traditional robust control theory. The approach uses multiobjective controller synthesis formulation that allows us to logically combine robustness requirements with performance objectives avoiding heuristic iteration over the control structure and parameters. The controller synthesis is performed by means of a nonsmooth $\mathcal {H}_{\infty }$ optimization technique that tunes all free parameters of a vector-based controller function, which constraints its structure. This results in a synthesized controller with lower order than those obtained with convex optimization definitions of the $\mathcal {H}_{\infty }$ control problem. The design methodology is validated in time and frequency domain by means of theoretical analysis and experimental results with three usual grid filters: L , LCL, and LLCL .

Energy storage systems play a key role in the rise of distributed power generation systems, hence there is great interest in extending their lifetimes, which are directly related to DC current ripple. One of the ripple sources is the low-frequency active power fluctuations under unbalanced and distorted grid voltage conditions. Therefore, this paper addresses a multifrequency control strategy where the harmonic reference currents are calculated to reduce harmonic active power oscillations. The stationary reference frame (StRF) approach taken here improves the precision and computational time of the current reference calculation method. Additionally, in order to ensure safe converter operation when a multifrequency reference current is provided, a computational efficient peak current saturator is applied while avoiding signal distortion every time step. If the injected current harmonic distortion is to be minimized, which is a feature included in this work, the peak current saturator is a necessary requirement. Active power ripple is reduced even with frequency variations in the grid voltage using a well-known frequency-adaptive scheme. The simulation and experimental results prove the optimized performance for the control objective: power ripple reduction with minimum current harmonic distortion.

This paper proposes a controller tuning methodology for voltage-current droop-based DC-DC converters in DC microgrids to reduce the output capacitance. This minimization is cost saving and implies lower fault currents. However, it leads to higher DC voltage variability during load transients, which requires an output impedance shaping by control means to reduce over or undershoot. The proposed control structure and problem definition simultaneously takes into account that the solution must achieve the impedance shaping, performance and stand-alone stability objectives. This comprises a multi-objective problem which is effectively formulated here and, then, solved by a non-smooth H∞ optimization technique that tunes all free parameters. For comparison purposes, this tuning methodology is applied to several droop proposals, and the proposed droop is able to reduce the output capacitance of bidirectional buck-type and boost-type half-bridge converters by 37.5% and 23.08%, respectively, with respect to previous proposals. The designs are validated in time and frequency domains by means of theoretical analysis and experimental results on DC microgrid prototypes with bidirectional buck-type or boost-type half-bridge converters.

This paper presents a new approach on robust current control of LCL-type grid-tied voltage source converters. This control method takes advantage of grid impedance nature to manage its unavoidable uncertainty at every point of common coupling. The Passivity-based Robust Control framework minimizes the converter impact over grid stability based on the passivity index of the impedance uncertainty, which leads to less conservative designs. System robustness is improved by means of a passivity constraint while keeping a performance goal. In order to overcome the non-convex behavior of the proposed multi-objective problem, we present a two-step approach design to find an acceptable solution. The methodology is initialized obtaining a controller via ${\mathcal{H}_\infty }$ synthesis procedure, which achieves the performance objective. Then, if the passivity constraint is not fulfilled, the non-smooth optimization technique will enforce it while taking care of the trade-off with the performance objective. Numerical and experimental results verify the achievement of the proposed objectives in time and frequency domain.

Grid side converters of renewable power plants have to be capable of dealing with severe grid disturbances, such as, grid faults and voltage sags. Model‐based predictive control provides outstanding performance to grid side converters: fast dynamic response, good tracking error and high‐quality currents. However, choosing the best set of vectors for the modulation requires assessing all the possible combinations of vectors using a cost function, which is very time consuming. Thus, the modulation is normally carried out with only 1 or 2 vectors per PWM period to save computing time, but this turns the modulation non‐linear. This lack of linearity makes it impossible to use symmetrical components in unbalanced grids. A linear multi‐vector model‐based predictive control that controls the power of both sequences using a sole cost function and analyses the effect of the transient response of several sequence decomposition systems on the model‐based predictive control predictions and dynamic response is proposed. Moreover, the proposed multi‐vector provides low THD currents while keeping the computing time low. In addition, the paper addresses the extrapolation of the proposed multi‐vector model‐based predictive control to N‐level converters. The good performance obtained is supported by the results obtained in simulations and the laboratory.