An effective robust fuzzy model predictive control (RFMPC) method for secondary voltage control in islanded microgrids (mu Gs) is presented here. In contrast to the existing techniques, which require a detailed model ...
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An effective robust fuzzy model predictive control (RFMPC) method for secondary voltage control in islanded microgrids (mu Gs) is presented here. In contrast to the existing techniques, which require a detailed model of mu G and an ideal communication network between mu G central controller and primary local controllers, RFMPC is synthesized for a non-linear model of the mu G with various time delays, uncertainties, and bounded disturbances. The famous Takagi-Sugeno fuzzy approach is adopted to approximate the inherently non-linear model of mu G by locally linear dynamics. The Lyapunov-Razumikhin functional method is exploited to deal with time delays. In this regard, sufficient conditions are provided in the form of linear matrix inequalities (LMIs). Then, a sequence of control laws corresponding to a set of terminal constraints is computed offline. Doing so, the online stage is reduced to solving a convex problem with LMI constraints considering the sequence of constraint sets obtained in the offline stage, thereby reducing the computational burden significantly. Robust positive invariance and input-to-state stability property concerning communication network deficiency are then speculated. The effectiveness of the proposed RFMPC is verified via a comprehensive suite of simulations in the matlab/simpowersystemsenvironment.
This study presents an automatic network balancing technique to limit the capacitive unbalance in resonant grounded power distribution systems (RGPDSs). The aim of this capacitive balancing technique is to minimise th...
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This study presents an automatic network balancing technique to limit the capacitive unbalance in resonant grounded power distribution systems (RGPDSs). The aim of this capacitive balancing technique is to minimise the unbalance current through the line to ground (which is the current through the neutral of the system) in order to automatically limit the neutral voltage. The proposed technique is designed by combining the weighted-sum technique and genetic algorithm (GA), where distributed switched capacitor banks (SCBs) are used for balancing RGPDSs. The proposed technique is employed to optimise available SCBs for limiting the network unbalance at the substation under a pre-defined threshold considering all possible network configurations. The unbalances at different locations of the network are also minimised to limit the system unbalance within the threshold due to minor changes in network parameters. Since the lifetime of capacitor banks relies on the switching, the proposed technique is designed in such a way that the system balance is achieved with the minimum switching. The performance of the proposed technique is evaluated through simulation studies in matlab/simpowersystemsenvironment. Simulation results show that the proposed technique works well and capable to maintain the capacitive balance of the system with changes in network configurations.
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