Neighbor-prediction-based networked hierarchical control in islanded microgrids

Abstract For the droop-controlled distributed generation units (DGs) in microgrids (MGs), the power sharing error associated with voltage difference of DGs can be attributed to the mismatched line impedance. To improve the power sharing accuracy in islanded MGs, a neighbor-prediction based hierarchical control strategy is proposed. In secondary control, a consensus protocol is used to regulate the DGs voltages interacted by communication network to the state of tracking synchronization. Thus, the error-free power sharing is obtained. Network data-loss and delay problems are considered. To stabilize the DGs’ inner-loop control in which there is a delayed input, the H∞ robustness criteria of a dynamic model of DGs is derived. If the DGi’s voltage in network transmission loses, the prediction system of a neighbor will be activated to forecast the lost voltage for secondary consensus control by extreme learning machine (ELM). Thus, the voltages regulation will be back to normalization. Simulations in MATLAB confirm the effectiveness of proposed control in MGs.

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