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Improved Sliding Mode Design for Load Frequency Control of Power System Integrated an Adaptive Learning Strategy

机译:集成自适应学习策略的电力系统负载频率控制的改进滑模设计

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摘要

Randomness from the power load demand and renewable generations causes frequency oscillations among interconnected power systems. Due to the requirement of synchronism of the whole grid, load frequency control (LFC) has become one of the essential challenges for power system stability and security. In this paper, by modeling the disturbances and parameter uncertainties into the LFC model, we propose an adaptive supplementary control scheme for the power system frequency regulation. An improved sliding mode control (SMC) is employed as the basic controller, where a new sliding mode variable is specifically proposed for the LFC problem. The adaptive dynamic programming strategy is used to provide the supplementary control signal, which is beneficial to the frequency regulation by adapting to the real-time disturbances and uncertainties. The stability analysis is also provided to guarantee the reliability of the proposed control strategy. For comparison, a particle swarm optimization-based SMC scheme is developed as the optimal parameter controller for the frequency regulation problem. Simulation studies are performed on single-area and multiarea benchmark systems, and comparative results illustrate the favorable performance of the proposed adaptive approach for the frequency regulation under load disturbances and parameter uncertainties.
机译:电力负荷需求和可再生能源发电的随机性会导致互连的电力系统之间发生频率振荡。由于整个电网需要同步,因此负载频率控制(LFC)已成为电力系统稳定性和安全性的主要挑战之一。在本文中,通过将扰动和参数不确定性建模为LFC模型,我们提出了一种用于电力系统频率调节的自适应补充控制方案。改进的滑模控制(SMC)被用作基本控制器,其中针对LFC问题专门提出了新的滑模变量。自适应动态规划策略用于提供辅助控制信号,通过适应实时干扰和不确定性,有利于频率调节。还提供稳定性分析以保证所提出控制策略的可靠性。为了进行比较,开发了基于粒子群优化的SMC方案作为频率调节问题的最佳参数控制器。在单区域和多区域基准系统上进行了仿真研究,比较结果表明,在负载扰动和参数不确定性的情况下,所提出的自适应方法在频率调节方面具有良好的性能。

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