科研之友
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摘要
Load-frequency control (LFC) strategy aims to extinguish oscillations of both the frequency and tie-line power deviations to restore the steady state of an electric grid after load change occurs. Classical controllers, e.g., Proportional-Integral (PI) regulators, have been initially applied to deal with the LFC. However, the main control performances, such as overshoots and settling times, should be further optimized to maintain the frequency within the desired tolerances. This paper investigates a novel approach using two-stage controllers based on neural network and fuzzy logic technique to improve efficiently the control performances. A six-control-area-interconnected power system model is also built as the typical case study. Subsequently, the proposed controllers will be applied to this model to solve the LFC issue in two cases: with and without using superconducting magnetic energy storage (SMES) devices. In principle, such SMES units can compensate efficiently load variations in a power system, thus they can be used in the LFC strategy to achieve the optimal performances. Finally, simulation results, which are obtained under various load conditions, demonstrate evidently the superiority of the proposed control strategy for the efficient solution of the LFC problem.
