基于改进生物地理学优化算法的SVC次同步阻尼控制器设计

发布时间：2018-01-14 12:07

本文关键词：基于改进生物地理学优化算法的SVC次同步阻尼控制器设计　出处：《电力系统自动化》2014年08期 　论文类型：期刊论文

【摘要】：针对常用的次同步振荡控制器不能较好地适应电力系统时变非线性的特点,提出了一种引入余弦迁移模型、早熟判断机制、变尺度混沌变异策略及排重操作的改进生物地理学优化算法。基于该算法结合静止无功补偿器(SVC)抑制次同步振荡的机理,对次同步阻尼控制器进行优化设计,并采用特征值分析和时域仿真验证了控制系统的有效性。锦界电厂算例分析表明:经改进生物地理学算法优化的SVC次同步阻尼控制器能较好地提高机组扭振的模态阻尼,可有效抑制次同步振荡,进而保证机组和电网的安全稳定运行;与传统的生物地理学优化算法、粒子群算法及遗传算法相比,改进生物地理学优化算法在搜索最优控制参数时具有较快的搜索速度和较高的搜索精度。
[Abstract]:In view of the fact that the subsynchronous oscillation controller can not adapt to the time-varying nonlinearity of power system, a cosine migration model is proposed, which is based on the precocious judgement mechanism. Variable scale chaos mutation strategy and improved biogeographic optimization algorithm for weight-removing operation. Based on the mechanism of the algorithm combined with SVC (static Var compensator) to suppress sub-synchronous oscillation. The sub-synchronous damping controller is optimized. The effectiveness of the control system is verified by eigenvalue analysis and time-domain simulation. The SVC sub-synchronous damping controller optimized by the improved biogeographic algorithm can improve the modal damping of the torsional vibration of the unit. It can restrain the sub-synchronous oscillation effectively, and then ensure the safe and stable operation of the unit and power grid. Compared with the traditional biogeographic optimization algorithm, particle swarm optimization algorithm and genetic algorithm, the improved biogeographic optimization algorithm has faster search speed and higher searching precision in searching optimal control parameters.
【作者单位】：武汉大学电气工程学院;中国电力科学研究院;
【基金】：国家自然科学基金资助项目(51207114)~~
【分类号】：TM761.12
【正文快照】： 0引言为了提高输电线路的输送能力,串联电容补偿(下文简称串补)技术被广泛应用,但采用该技术后可能会引发次同步振荡(SSO)问题。SSO是指电力系统中电气系统和汽轮发电机组以低于系统同步频率的某个或多个振荡频率交换显著能量的不正常运行状态,并且危及汽轮发电机轴系安全的动

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