Related papers: A Data-Driven Optimal Control Architecture for Gri…
We apply a novel data-enabled predictive control (DeePC) algorithm in grid-connected power converters to perform safe and optimal control. Rather than a model, the DeePC algorithm solely needs input/output data measured from the unknown…
Power electronic converters are becoming the main components of modern power systems due to the increasing integration of renewable energy sources. However, power converters may become unstable when interacting with the complex and…
Grid-connected power converters encounter significant stability challenges during weak grid faults, when conventional PI-based controllers exhibit an oscillatory response and poor fault-ride-through performance. This paper addresses this…
Grid-connected inverter control is challenging to implement due to the difficulty of obtaining and maintaining an accurate grid model. Direct Data-Driven Predictive Control provides a model-free alternative to traditional model-based…
The integration of power electronic converters (PECs) and distributed energy resources (DERs) in modern power systems has introduced dynamism and complexity. Accurate simulation becomes essential to comprehend the influence of converter…
Modern power grids are fast evolving with the increasing volatile renewable generation, distributed energy resources (DERs) and time-varying operating conditions. The DERs include rooftop photovoltaic (PV), small wind turbines, energy…
One of the most important challenges facing an electric grid is to incorporate renewables and distributed energy resources (DERs) to the grid. Because of the associated uncertainties in power generations and peak power demands,…
Data-driven control that circumvents the process of system identification by providing optimal control inputs directly from system data has attracted renewed attention in recent years. In this paper, we focus on understanding the effects of…
Resonant power converters offer improved levels of efficiency and power density. In order to implement such systems, advanced control techniques are required to take the most of the power converter. In this context, model predictive control…
Hybrid AC/DC transmission grids incorporate Modular Multilevel Converters functioning as Interconnecting Power Converters (IPCs). The control role assigned to each converter significantly influences grid dynamics. Traditionally, these…
The modern power system features high penetration of power converters due to the development of renewables, HVDC, etc. Currently, the controller design and parameter tuning of power converters heavily rely on rich engineering experience and…
A significant amount of converter-based generation is being integrated into the bulk electric power grid to fulfill the future electric demand through renewable energy sources, such as wind and photovoltaic. The dynamics of converter…
We employ a novel data-enabled predictive control (DeePC) algorithm in voltage source converter (VSC) based high-voltage DC (HVDC) stations to perform safe and optimal wide-area control for power system oscillation damping. Conventional…
The fundamental role of power converters is to efficiently manage and control the flow of electrical energy, ensuring compatibility between power sources and loads. All these applications of power converters need the design of an…
Converter-based generators and loads are growing in prevalence on power grids across the globe. The rise of these resources necessitates controllers that handle the power electronic devices' strict current limits without jeopardizing…
Mitigating the energy use in buildings, together with satisfaction of comfort requirements are the main objectives of efficient building control systems. Augmenting building energy systems with batteries can improve the energy use of a…
An islanded inverter-based microgrid is a collection of heterogeneous DC energy resources, e.g., photovoltaic arrays, fuel cells, and energy-storage devices, interfaced to an AC distribution network and operated independently from the bulk…
Given the advancements in data-driven modeling for complex engineering and scientific applications, this work utilizes a data-driven predictive control method, namely subspace predictive control, to coordinate hybrid power plant components…
Data-enabled predictive control (DeePC) is a data-driven control algorithm that utilizes data matrices to form a non-parametric representation of the underlying system, predicting future behaviors and generating optimal control actions.…
The existing decentralized control for cascaded inverters is based on the assumption that all modules have same capacities, and a local fixed-amplitude-varied-phase voltage control is adopted for each inverter module. However, available…