Reliability Analysis of Microgrids: Evaluation of Centralized and Decentralized Control Approaches

The transformation of traditional power systems into micro and smart grids has become necessary with recent advancements in technology. However, these new systems often have low inertia, which can lead to instability, decreased power quality, and potential blackouts. There are two methods for controlling microgrids: centralized and decentralized controllers. Each method provides different advantages and has some limitations. This paper focuses on the reliability of central and decentralized controlled microgrids. It reviews the reliability of microgrids using both centralized and decentralized controllers, and explains various methods and analysis that can be applied. Examples which analyses reliability assessment of microgrid central controller are given. Examples employed different methods such as the Monte Carlo simulation, the Markov Chain process, the fast decoupled load flow simulation method and hybrid methods. Then, centralized and decentralized microgrids reliability is analyzed and compared through an example with Markov Chain Modeling and reliability indices. It is understood that the microgrid central controller has to be survive all the time otherwise it is very likely to see the grid failure. Also, it is seen that decentralized architecture is crucial with regard to reliability because centrally controlled microgrids are prone to failures due to their single point of failure.