Emergency islanding of a microgrid (MG) can be vital in ensuring continuity of power supply to a local network during major contingencies in the main grid. However, such an event will inadvertently cause large voltage transients except in the trivial case where zero power is exchanged. The under/over voltages can result in the disconnection of the local distributed generators within the MG, increasing the risk of a local blackout. In this paper, we present a MG operational optimization strategy that includes dynamic voltage constraints aiming at enhancing MG resilience during emergency situations. A dynamic optimization technique, based on sequential constraint transcription, is used to formulate the dynamic voltage security constraints applied to the steady-state problem in a computationally efficient manner. An iterative approach ensures that the dynamic constraints are updated in relation to the optimized operating point of the MG. The performance of the proposed approach is investigated on a 30-bus medium-voltage MG by considering a potential disconnection at each hour of the day, subject to daily load and generation profiles.

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This paper presents a data-driven two-stage distributionally robust planning tool for sustainable microgrids under the uncertainty of load and power generation of renewable energy sources (RES) during the planning horizon. In the proposed two-stage planning tool, the first-stage investment variables are considered as here-and-now decisions and the second-stage operation variables are considered as wait-and-see decisions. In practice, it is hard to obtain the true probability distribution of the uncertain parameters. Therefore, a Wasserstein metricbased ambiguity set is presented in this paper to characterize the uncertainty of load and power generation of RES without any presumption on their true probability distributions. In the proposed data-driven ambiguity set, the empirical distributions of historical load and power generation of RES are considered as the center of the Wasserstein ball. Since the proposed distributionally robust planning tool is intractable and it cannot be solved directly, duality theory is used to come up with a tractable mixed-integer linear (MILP) counterpart. The proposed model is tested on a 33-bus distribution network and its effectiveness is showcased under different conditions.

Abstract--This paper presents a novel synchronization technique which can identify the grid voltage frequency and phase angle under unbalanced grid voltage conditions. The method combines the features of two different energy operator schemes: the basic one for estimating the frequency of the grid voltages and the cross-energy operator for phase tracking. Using a moving data window of five samples the algorithm can track the fundamental frequency and phase angle quickly and accurately. The paper discusses the fundamental principles of the method, highlights its features and filter requirements in implementation. An experimental implementation of this method is presented which validates its performance for practical operation. The ability of the proposed method to enable a STATCOM riding-through unbalanced grid voltage condition is verified by the results from a power network simulation study.

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