Automation of Electric Power SystemsVol. 40, Issue 3, Pages: 21-26(2016)
作者机构:
新能源电力系统国家重点实验室, 华北电力大学,北京市,102206
作者简介:
基金信息:
DOI:
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Published:2016
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MA Jing. [J]. Automation of electric power systems, 2016, 40(3): 21-26.
DOI:
MA Jing. [J]. Automation of electric power systems, 2016, 40(3): 21-26.DOI:
基于连续马尔可夫模型的时变电力系统自适应控制策略
摘要
针对风电机组出力波动等时变因素导致电力系统运行工况变化较大的问题
提出了一种基于连续马尔可夫(Markov)模型的时变电力系统自适应控制策略。首先
构建含连续Markov时变电力系统模型的Lyapunov泛函
利用Dynkin引理
推导出具有H∞范数界γ的鲁棒随机稳定性定理。在此基础上
利用Schur补引理
考虑系统各子工况下稳态方差约束
推导出满足干扰衰减度γ和最小方差约束的鲁棒随机稳定线性矩阵不等式(LMI)
并将该LMI转化为线性目标函数的最小化问题求解各子控制器。然后
利用随机梯度法辨识系统工况
确定各子控制器加权系数
构造自适应控制策略。时域仿真表明
该控制策略有效避免了固定故障集无法与当前工况合理匹配的问题。
Abstract
An adaptive control strategy based on continuous Markov model for time-varying power system is proposed to deal with the large variation in operating condition of power system caused by the wind generator output fluctuation. First
Lyapunov functional containing a continuous Markov model of time-varying power system is developed and Dynkin lemma is used to deduce the robust stochastic stabilization theorem with H∞ norm bound γ. On this basis
Schur complement lemma is used to deduce robust stochastic stabilization linear matrix inequalities(LMI)meeting decay rate γ and minimum variance constraints considering steady-state variance constraints of various operating conditions. Then it is turned into a minimization problem of linear objective function to obtain the sub-controllers. The operating condition is identified online with the stochastic gradient method and the weighted coefficient of each condition is determined to construct the adaptive control strategy. Time-domain simulation results show that the strategy has efficiently solved the problem that fixed fault sets cannot be matched with current operating condition reasonably. This work is supported by National Natural Science Foundation of China(No. 50907021
No. 51277193)
National Basic Research Program of China(973 Program)(No. 2012CB215200)
and Fundamental Research Funds for the Central Universities(No. 2014ZZD02).
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