Intelligent voltage and frequency control of islanded micro-grids based on power fluctuations and communication system uncertainty

•Optimal management of active power between DGs and HESS.•Micro-grid frequency control based on DG uncertainties in primary and secondary.•Protection of HESS units and improve transient stability.•Improving the speed and accuracy of dynamic response system based on meta-heuristic algorithms. Control...

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Bibliographic Details
Published in:	International journal of electrical power & energy systems Vol. 143; p. 108383
Main Authors:	Ghasemi, Arvin, Sedighizadeh, Mostafa, Fakharian, Ahmad, Nasiri, Mohammad Reza
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01-12-2022
Subjects:	Hybrid energy storage systems Intelligent control Intelligent neural network Microgrid Particle swarm optimization and Fuzzy algorithm Particle swarm optimization and Fuzzy algorithm Microgrid Intelligent neural network Hybrid energy storage systems Intelligent control
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Summary:	•Optimal management of active power between DGs and HESS.•Micro-grid frequency control based on DG uncertainties in primary and secondary.•Protection of HESS units and improve transient stability.•Improving the speed and accuracy of dynamic response system based on meta-heuristic algorithms. Control of critical micro-grid factors such as voltage/frequency is complex and challenging in power distribution networks that include micro-grids. Therefore, providing an efficient and optimal control framework to maintain stability and control the critical factors of the network significantly affects the development of micro-grids goals. The present study proposed the intelligent voltage/frequency control scheme in primary and secondary micro-grids. Micro-grid voltage/frequency restoration was planned based on the PSO-Fuzzy control algorithm in the primary control. In addition to optimizing the members of the fuzzy controller, the PSO optimization algorithm was also used to calculate the voltage/ frequency deviation based on the voltage error factors and the violation of the deviation from the frequency reference. The PSO-Fuzzy structure was provided to optimize hybrid energy storage units' charge and discharge thresholds. Moreover, an intelligent artificial neural network algorithm was presented based on Lyapunov stability equations and a communication system platform to compensate for the voltage/frequency deviation in the secondary control. The proposed algorithm had optimal and efficient performance in different scenarios, such as the effect of load dynamic and its type, power fluctuations, and communication system delays.
ISSN:	0142-0615 1879-3517
DOI:	10.1016/j.ijepes.2022.108383