考虑离散马尔可夫模型的多工况电力系统自适应控制策略

发布时间：2019-01-21 20:28

【摘要】：针对连锁故障导致电力系统运行工况变化较大的问题,提出一种考虑离散马尔可夫模型(Markov)的多工况电力系统自适应控制策略。首先,建立考虑电力系统多工况因素的离散Markov系统模型,构造含该模型的Lyapunov泛函,并利用迭代法推导满足干扰衰减度的鲁棒随机稳定判据。在此基础上,利用Schur补引理,获取满足H?范数界的线性矩阵不等式(linear matrix inequality,LMI),并结合系统各子工况最小方差约束,设计满足最小方差约束的鲁棒随机稳定控制器。然后,利用线性目标函数的最小化问题求解各子工况匹配控制器,利用随机梯度在线辨识方法确定子工况对应加权系数,实现自适应加权控制。时域仿真结果表明该策略具有良好的控制效果,有效解决了固定故障集无法与当前工况合理匹配的难题。
[Abstract]:In order to solve the problem that cascading faults lead to great variation of power system operating conditions, an adaptive control strategy for multi-condition power system considering discrete Markov model (Markov) is proposed. Firstly, a discrete Markov system model considering multiple operating conditions is established, and a Lyapunov functional with this model is constructed, and a robust stochastic stability criterion satisfying the disturbance attenuation degree is derived by iterative method. On this basis, Schur complementary Lemma is used to obtain the satisfying H? The norm bound linear matrix inequality (linear matrix inequality,LMI) is used to design a robust stochastic stability controller which satisfies the minimum variance constraint. Then, the linear objective function minimization problem is used to solve the sub-condition matching controller, and the stochastic gradient on-line identification method is used to determine the corresponding weighting coefficients of the sub-conditions, and the adaptive weighting control is realized. The simulation results in time domain show that the strategy has a good control effect and effectively solves the problem that the fixed fault set can not match properly with the current working condition.
【作者单位】：新能源电力系统国家重点实验室(华北电力大学);国网冀北电力有限公司廊坊供电公司;
【基金】：国家自然科学基金项目(51277193) 中央高校基本科研业务费专项资金项目(2014ZZD02)~~
【分类号】：TM921.5

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