Abstract
Although the deployment and integration of isolated microgrids is gaining widespread support, regulation of microgrid frequency under high penetration levels of renewable sources is still being researched. Among the numerous studies on frequency stability, one key approach is based on integrating an additional loop with virtual inertia control, designed to mimic the behavior of traditional synchronous machines. In this survey, recent works related to virtual inertia control methods in islanded microgrids are reviewed. Based on a contextual analysis of recent papers from the last decade, we attempt to better understand why certain control methods are suitable for different scenarios, the currently open theoretical and numerical challenges, and which control strategies will predominate in the following years. Some of the reviewed methods are the coefficient diagram method, H-infinity-based methods, reinforcement-learning-based methods, practical-swarm-based methods, fuzzy-logic-based methods, and model-predictive controllers.
Highlights
IntroductionRenewable energy sources (RESs) are frequently deployed in modern power grids to promote a myriad of environmental and economical benefits
One approach for addressing this problem is to install fast-reacting storage systems with virtual inertia controllers alongside low-inertia power sources; such controllers have been extensively studied in recent years [5,6,7,8,9,10,11]
The contribution of photovoltaic (PV) power plants as virtual inertia was discussed and the damping factor evolution was analyzed. Contrary to these comprehensive reviews, which focused on virtual inertia topologies implementation [12], virtual inertia and frequency control for distributed energy sources [21], and inertia estimation evolution in power systems [22], we focused on the systematic comparison of virtual inertia control methods designed to solve the frequency regulation problem in islanded microgrids
Summary
Renewable energy sources (RESs) are frequently deployed in modern power grids to promote a myriad of environmental and economical benefits. Classical control paradigms are simple in general but are designed for specific scenarios, whereas data-driven algorithms are flexible and enable online learning. These algorithms are numerically complex and require adequate data to operate efficiently. Microgrids have received increasing attention as a means of integrating distributed generation into the electricity grid [18]. Microgrids comprise a variety of technologies: renewable sources, such as photovoltaic and wind generators, are operated alongside
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