期刊
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
卷 45, 期 5, 页码 7933-7960出版社
WILEY
DOI: 10.1002/er.6376
关键词
AGC; deregulated power system; energy storage; fuzzy logic control; genetic algorithms; TCPS; Ultrabattery
This article proposes a method for AGC control in a deregulated power system using Ultrabattery in coordination with TCPS. Simulation studies demonstrate the effectiveness of the scheme in mitigating low magnitude oscillations and improving system performance index.
This article studies automatic generation control (AGC) problem of a realistic, multi-source deregulated power system with thyristor controlled phase shifter (TCPS) in the tie-line for damping the inter-area power oscillations. In this direction, an intelligent integration of a commercially available, relatively low rating efficient energy storage system in the form of Ultrabattery for AGC enhancement is proposed. Herein, a two-level supervisory cascade control scheme is designed. The supervisory controller comprises of a genetically tuned fuzzy logic controller which ensures the operation of Ultrabattery within its regime of operation while supervising a conventional main controller in the inner loop. The exchange of desired power between the power system and Ultrabattery is governed by the main controller whose parameters are tuned offline using optimization toolbox in MATLAB. To make the power system model realistic, effects of generation rate constraint, governor dead band, boiler dynamics, and communication time delay have been incorporated. Extensive simulation studies conducted on a well-known benchmark two-area power system under various market scenarios demonstrate the effectiveness of the proposed scheme. The results obtained illustrate a substantial mitigation of low magnitude oscillations with TCPS in the tie-line. Following the introduction of an Ultrabattery rated at just 1% of the area capacity in coordination with TCPS, an improvement of at least 87% in the system performance index is achieved. Finally, a sensitivity analysis validates the robustness of the proposed scheme under varying system parameters and market scenarios.
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