Central Damping Controller for Microgrid Voltage and Frequency Dynamic Stability Using Adaptive Artificial Neural Network

Autor: Seyyed Hamid Hosseini, Soheil Ranjbar, Masoud Radmehr
Rok vydání: 2021
Předmět:
Zdroj: Journal of Control, Automation and Electrical Systems. 32:1024-1040
ISSN: 2195-3899
2195-3880
DOI: 10.1007/s40313-021-00726-9
Popis: This paper presents an online non-model-based scheme to voltage and frequency control of microgrids in the presence of inverter-based distributed energy resources (DERs). For developing proposed controller, considering adaptive control concept, a central controller is designed through aggregation distribution procedure which optimized using artificial adaptive neural network (AANN). In this case, based on the system dynamic variables, the DERs dynamical models are provided which following Lyapunov-based theory, the corresponding central controller is designed. In this way, the proposed Lyapunov theory is responsible to limit AANN weighted boundaries which following an optimization procedure, it is resulted in controller accuracy. By developing central controller, the intelligent AANN is provided which considering a set of offline training procedure, online values of dynamic variables are estimated through real-time working mode. By this way, it is not required to receive any initial information related to DER variables which based on the developing non-model-based dynamical model, the central damping controller (CDC) is extended. The effectiveness of proposed CDC scheme is verified on a typical microgrid test system consisting of several DERs which considering different fault event scenarios, CDC damping performances are evaluated. Simulation results prove the voltage and frequency damping performances of proposed controller in the presence of low-inertia suppliers.
Databáze: OpenAIRE
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