The corrective control problem was decomposed into a nonlinear power flow and linear sensitivitycomputation sub-problem and a sensitivity-based linear programming optimization control sub-problem.
In the safety correcting computation, effective control variables are selected by sensitivity analysis and their adjusted values are found directly by the pseudo-inverse method.
在安全校正计算中,通过灵敏度分析选择出有效控制变量并由伪逆法直接求得其调整量。
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We analysis the affection that the transition matrix error of a Markov chain brings to the average reward of the system and discuss the computation of the system sensitivity.