Autonomous Control Techniques for Grid-Connected Inverters
Author(s)
Miranbeigi, Mohammadreza
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Abstract
The traditional power grid dominated by synchronous machines is shifting toward a modern power-electronics-based system due to environmental concerns and a significant plunge in the price of solar modules and wind-energy systems. This radical evolution leads to more controllability, sustainability, and higher power conversion efficiency. At the same time, it creates new challenges for the stability and operation of the grid. Due to a high number of inverters being deployed at the transmission and distribution level, it is challenging to control all inverters in real-time by a central controller. In addition, dependence on large-scale real-time communication networks for centralized control is impractical, given the critical nature of power infrastructure. It is more feasible to push intelligence to the edge and make each inverter a smart agent that can work autonomously in real-time. In this case, the communication with the operator is only used for optimization and long-term planning. Autonomous operation requires inverters to be capable of working with poor system knowledge, managing the transients, and supporting the grid to keep it firm and stable. Moreover, to improve the resiliency of the grid, they should be capable of working in both grid-connected and grid-isolated modes and seamlessly switch between them. Since the grid will experience fast transients in the presence of inverters, inverters should be equipped with techniques that can measure parameters instantly and extract useful information in a fast and reliable manner. The existing control schemes cannot meet all these objectives, therefore novel and autonomous schemes are needed that enhance the performance of the grid-connected inverters and grant more autonomy to them.
The objective of the proposed research is to develop a universal method that meets some of these requirements and addresses some of the issues with the existing techniques by proposing a new universal control (UniCon) scheme. The UniCon consists of three elements that all work in harmony: adaptive inertia + damping, current-limiting phase-jump, and adaptive virtual impedance. The adaptive inertia + damping scheme enables inverters to support the grid while damping low-frequency power swing oscillations. The current-limiting phase-jump allows instant connection of an inverter to another source, hence the inverter can transition between grid-connected and grid-isolated modes in an ad hoc manner. The adaptive virtual impedance allows the inverter to stably ride through a fault and provide maximum current to support the grid voltage. These three elements together enable the UniCon to work in a wide range of conditions, including normal, abnormal, and fault. Lastly, a novel scheme is proposed based on deep neural networks that enables inverters to rapidly track grid variables, such as amplitude and phase, so that inverters can promptly take proper action. The UniCon elements have been tested in a simulation testbed and an experimental setup and have been compared with the state-of-the-art schemes.
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Date
2022-07-20
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Dissertation