科研之友
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摘要
The focus of this work is to design a novel hybrid load-frequency control (LFC) strategy for a multi-area large-scale electric power interconnection. The proposed methodology is based on two consecutive control phases, including an artificial neural network model and a PD-like fuzzy logic inference system. The new two-stage architecture enables this control strategy to utilize the advantage of each phase, and thus it is able to enhance the robustness of the LFC controller to quickly restore the steady state of the network after load variations. In addition, superconducting magnetic energy storage (SMES) devices, which can powerfully compensate for the loss of energy in an electric power grid, are investigated to support the LFC scheme. The integration of the novel hybrid LFC controller and the SMES devices in a large-scale network is completely capable of being a promising control solution for maintaining the system frequency against the load variations. The feasibility and superiority of the proposed control strategy over the conventional PI regulators as well as a number of previous studies will be demonstrated through numerical simulation processes with various load conditions implemented in a six-control-area electric power interconnection.
