Robust distributed stochastic secondary control of microgrids with system and communication noises

• Published in: IET generation, transmission & distribution transmission & distribution, 2020-03, Vol.14 (6), p.1148-1158
• Main Authors: Dehkordi, Nima Mahdian, Nekoukar, Vahab
• Format: Article
• Language: English
• Subjects: Case Study; communication channels; communication noises; distributed control; distributed generations; distributed power generation; estimated signals; frequency restoration; graph theory; islanded microgrids; Kalman filters; Kalman‐filtering theory; limited band‐width constraints; low computational burden; mean‐square synchronisation; neighbour DGs; noise interferences; noise‐resilient distributed methods; noisy communication environment; noisy measurement; power distribution faults; power generation control; power sharing accuracy; robust control; robust stochastic distributed secondary control method; secondary control method; sparse communication network; stochastic secondary control; stochastic theory; synchronisation; system measurement
• ISSN: 1751-8687; 1751-8695; 1751-8695
• DOI: 10.1049/iet-gtd.2019.0694

This study proposes an advanced robust stochastic cooperative frequency/voltage restoration control considering the effects of both communication/system noises based on Kalman-filtering theory for secondary control of islanded microgrids. Compared with existing ideal and noise-resilient distributed methods, the proposed robust stochastic distributed secondary control method can achieve mean-square synchronisation for voltage and frequency restoration of distributed generations (DGs) along with the real power sharing accuracy through a sparse communication network, even though both the system measurement and communication channels are susceptible to noise interferences and limited band-width constraints. To this end, the graph theory, stochastic theory, and Kalman-filtering theory are employed to estimate the states of each DG based on the information of noisy measurement, and then the estimated signals are sent to the neighbour DGs via a noisy communication environment. The main advantages of the proposed method are its ability to provide the quality of the estimate, low complexity, low computational burden, and working even though both the system and communication channels are susceptible to noise interferences and limited band-width constraints. Finally, the simulation results in MATLAB/SimPowerSystems Toolbox show that the proposed method has better, robust, resilient, acceptable, and desirable performance compared with the recent and effective methods.