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This paper reveals that the existing techniques have some deficiencies in the proper estimation of voltage stability margin (VSM) when applied to a power system with different load change scenarios. The problem gets worse when credible contingencies occur. This paper proposes a real-time wide-area approach to estimate VSM of power systems with different possible load change scenarios under normal and contingency operating conditions. The new method is based on an artificial neural network (ANN) whose inputs are bus voltage phasors captured by phasor measurement units (PMUs) and rates of change of active power loads. A new input feature is also accommodated to overcome the inability of trained ANN in prediction of VSM under N−1 and N−2 contingencies. With a new algorithm, the number of contingencies is reduced for the effective training of ANN. Robustness of the proposed technique is assured through adding a random noise to input variables. To deal with systems with a limited number of PMUs, a search algorithm is accomplished to identify the optimal placement of PMUs. The proposed method is examined on the IEEE 6-bus and the New England 39-bus test system. Results show that the VSM could be predicted with less than 1% error.

This paper proposes a stabilizer to suppress the large transients subsequent to disconnection/reconnection of microgrids (MGs) that are controlled in a unified mode. In the unified control mode, the control system requires to operate in grid-connected mode, islanded mode, and mode transition transients with a unique control configuration. The MG is assumed to contain heterogeneous types of distributed generators (DGs) that include electronically interfaced DGs (EI-DGs) and synchronous generators (SGs). The simultaneous operation of the EI-DGs and SGs due to their different voltage and frequency control strategies makes the design of the stabilizer more challenging. A general Lyapunov function is defined considering the response delay of the primary resources. The deteriorating effects of the primary resource response delays on the mode transition transients are evaluated analytically. Furthermore, the asymptotic stability in the frequency and voltage loops are guaranteed by the proposed stabilizer that solely utilizes local information. The proposed stabilizer is designed and implemented for both EI-DGs and SGs. Finally, the effectiveness of the proposed control strategy is demonstrated using time-domain simulations on a multiresource MG. The performance of the proposed method is also compared with that of an existing method.