Reset Control for DC–DC Converters: An Experimental Application

Nair, Unnikrishnan Raveendran; Costa‐Castelló, Ramon; Baños, Alfonso

doi:10.1109/access.2019.2940140

Cited by 9 publications

(2 citation statements)

References 32 publications

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“…Similarly, the set D, called the jump set, describes the points in the space where the system can jump according to the recursion (5b) [23], [42]. This type of model has been used in the context of power systems and MG control in [235], [240], [241], [242], and [243].…”

Section: C: Event-triggered Sampled-data and Hybrid Control In Vppsmentioning

confidence: 99%

Control Systems for Low-Inertia Power Grids: A Survey on Virtual Power Plants

et al. 2023

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Virtual Power Plants (VPPs) have emerged as a modern real-time energy management architecture that seeks to synergistically coordinate an aggregation of renewable and non-renewable generation systems to overcome some of the fundamental limitations of traditional power grids dominated by synchronous machines. In this survey paper, we review the different existing and emerging feedback control mechanisms and architectures used for the real-time operation of VPPs. In contrast to other works that have mostly focused on the optimal dispatch and economical aspects of VPPs in the hourly and daily time scales, in this paper we focus on the dynamic nature of the system during the faster sub-hourly time scales. The virtual (i.e., software-based) component of a VPP, combined with the power plant (i.e., physics-based) components of the power grid, make VPPs prominent examples of cyber-physical systems, where both continuous-time and discrete-time dynamics play critical roles in the stability and transient properties of the system. We elaborate on this interpretation of VPPs as hybrid dynamical systems, and we further discuss open research problems and potential research directions in feedback control systems that could contribute to the safe development and deployment of autonomous VPPs.INDEX TERMS Smart grids, renewable energy, virtual power plant, feedback control, multi-agent hybrid dynamical systems.

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Section: C: Event-triggered Sampled-data and Hybrid Control In Vppsmentioning

confidence: 99%

Control Systems for Low-Inertia Power Grids: A Survey on Virtual Power Plants

et al. 2023

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“…On the contrary, digital ACMCs present less performance variation over time than their analog counterparts. Digital predictive deadbeat (PDB) [15, 16], proportional‐integral‐derivative (PID) [17, 18], PI with Clegg integrators (PI+CI) [19], and state‐space‐based [20] ACMC strategies have been proposed. The PDB‐based strategies calculate the optimal duty cycle of the switch for the next switching period to minimise the error between the input current reference and measured average values.…”

Section: Introductionmentioning

confidence: 99%

Generalised predictive current‐mode control of passive front‐end boost‐type converters

Judewicz

González

Fischer

et al. 2021

IET Power Electronics

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In this work, an average current‐mode control strategy based on a generalised predictive control formulation for passive front‐end three‐phase boost‐type converters is proposed. A novel design procedure for the generalised predictive control strategy is introduced which considers both the cost function and disturbance model as design parameters to set the controller's dynamic response and robustness against component variations. A maximum robustness criterion was used for achieving stability up to a 70% inductance reduction with maximum possible bandwidth. The proposed strategy was compared against both a PI and a predictive deadbeat average current‐mode control using both simulations and experimental results on a 2-kW converter. The generalised predictive control presented less performance variations between different operating points than the PI controller. Also, the proposed strategy is more robust than the predictive deadbeat strategy, showing a better transient response with a 50% inductance reduction and remained stable for a 71% inductance reduction, while the predictive deadbeat could not. Finally, the proposed strategy achieved a 1.4% output voltage load transient response for a 595W load power step, and a 2.8% output voltage line transient response for a 100V input voltage step, outperforming existing state‐of‐the‐art strategies.

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