Search

Control of AC/DC pulse-width modulation (PWM) power electronic converter, referred to as "AC/DC PWM converter", is vital to the efficient regulation of power flow between AC and DC parts of a hybrid microgrid. Given the importance of such converters in AC/DC microgrids, this paper investigates the design of fault-tolerant control for AC/DC PWM converters in the presence of microgrid faults. In particular, two novel fault-tolerant schemes based on fuzzy logic and model predictive control are proposed and implemented in an advanced hybrid microgrid benchmark in MATLAB/Simulink environment. The considered hybrid microgrid consists of dynamic loads and distributed energy resources including solar photovoltaic arrays, wind turbines, and battery energy storage systems. The proposed schemes especially target the fault effects due to common power-loss malfunctions in solar photovoltaic arrays in the presence of microgrid uncertainties and disturbances. The effectiveness of proposed fault-tolerant control schemes is demonstrated and compared under realistic fault scenarios in the hybrid microgrid benchmark. [ABSTRACT FROM AUTHOR]

With focusing on solar photovoltaic (PV) systems operating at microgrid (MG) level, this study investigates the impacts of different physical faults and cyberattacks as well as designing an intelligent faults/attacks detection and diagnosis system. The ability to quickly identify and diagnose faults/attacks enables local controllers and energy management system to accommodate or mitigate the negative effects of physical faults or cyberattacks in a MG. This allows the MG to carry on operating without experiencing any significant interruptions. In this regard, the current paper investigates a hybrid AC/DC MG made up of different distributed energy resources (DER), including solar PV arrays, wind turbines, and battery energy storage systems. An intelligent hybrid diagnosis (IHD) scheme is introduced for online monitoring and diagnosing the data to reflect the real-time status of the PV system operating at the MG level. This hybrid system uses three parallel units, including a "fuzzy inference system (i.e., a rule-based unit)", a "power spectrum estimator (i.e., a signal-based unit)", and an "adaptive neuro-fuzzy inference system (i.e., a model-based unit)". A realistic MG benchmark model with a wide range of operating conditions and dynamic electrical loads in the presence of potential MG disturbances is used to demonstrate the high performance and resilience of the proposed IHD scheme under various types of faults/attacks scenarios. • The impacts of physical faults and cyberattacks on photovoltaic (PV) systems at microgrid (MG) level are investigated. • A faults/attacks detection and diagnosis scheme referred to as intelligent hybrid diagnosis (IHD) scheme is presented. • A hybrid AC/DC MG composed of several renewable distributed energy resources (DER) is considered. • Three parallel diagnosis units including rule-based, signal-based, and model-based units for IHD scheme are designed. • Simulations on realistic MG model with wide range of operating conditions in the presence of disturbances are performed. [ABSTRACT FROM AUTHOR]