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A hybrid chemical reaction-particle swarm optimisation technique for automatic generation control

机译:用于自动发电控制的混合化学反应-粒子群优化技术

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摘要

In this paper, a novel hybrid chemical reaction optimisation and particle swarm optimisation (HCROPSO) optimised PI controller has been proposed for automatic generation control (AGC) problem. A two area reheat thermal-hydro system with non-linearities such as governor dead band (GDB), generation rate constraints (GRC) and boiler dynamics is considered. The parameters of PI controller are optimised employing HCRO-PSO technique. The superiority of the proposed approach is shown by comparing the results with PSO, CRO and fuzzy logic control (FLC). Improvement in system performance is obtained in terms of reduced settling time, overshoot and undershoot of frequency deviation and tie line power deviation with proposed controller. Investigation is performed with variation in inter rate and inertia weight parameters. Sensitivity analysis is performed by varying the system parameters and generation rate constraints from their nominal values. Analysis reveals that HCRO-PSO optimized PI gains obtained at nominal are quite robust and need not be reset for wide changes in system parameters.
机译:针对自动发电控制(AGC)问题,提出了一种新型的混合化学反应优化和粒子群优化(HCROPSO)优化的PI控制器。考虑具有非线性的两区域再热热水系统,例如调速器死区(GDB),发电率约束(GRC)和锅炉动力学。 PI控制器的参数使用HCRO-PSO技术进行了优化。通过将结果与PSO,CRO和模糊逻辑控制(FLC)进行比较,表明了该方法的优越性。通过减少建立时间,频率偏差的过冲和下冲以及所提出的控制器的线路功率偏差,可以提高系统性能。进行调查时会出现中间速率和惯性权重参数的变化。通过从其标称值改变系统参数和发电速率约束来执行灵敏度分析。分析表明,标称值获得的HCRO-PSO优化PI增益非常可靠,无需为系统参数的广泛变化而进行重置。

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