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Abstract
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Transient stability preventive control (TSPC), a method to efficiently withstand the severe contingencies in a power system, is mathematically a transient stability constrained optimal power flow (TSC-OPF) issue, attempting to maintain the economical and secure dispatch of power system via generation rescheduling. The traditional TSC-OPF issue incorporated with differential-algebraic equations (DAE) is time-consuming and difficult to solve. Therefore, a new TSPC method driven by a naturally inspired optimization algorithm integrated with transient stability assessment is proposed in this paper. To avoid solving complex DAE, stacking ensemble multilayer perceptron (SEMLP) is used as a transient stability assessment (TSA) model in this research. Simultaneously, sensitivity analysis based on this TSA model determines the adjustment direction of the controllable generators set and improves the efficiency of the subsequent optimization. In addition, a naturally inspired algorithm, Aptenodytes Forsteri Optimization (AFO), is introduced to find the best operating point with a near-optimal operational cost while ensuring power system stability. The accuracy and effectiveness of the method are verified on the IEEE 39-bus system and the IEEE 300-bus system.
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