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Moreover, the impact of key primary frequency control parameters on the dynamic response characteristics of the AP1000 NPP and the control effect of system frequency was also studied, and the recommended values of the frequency deadband and bias coefficient have been given for the world's first AP1000 NPP under construction in Sanmen, Zhejiang province of China.
For model 3 in Table 2, the first-order difference method is utilized to estimate that the bias coefficient of interaction is 0.012 and 0.031 for outward interactions.
While the bias coefficient of internal interaction is −0.005, an insignificant negative number, that of outward interaction, is 0.051, which is very significant compared with a statistical level of 0.001.
In other words, the bias coefficient of internal interaction variation fails the significance test during single-period analysis for first and present job stages; otherwise, the coefficient in the difference model is significant.
It turns out that the bias coefficient of internal interaction is still insignificant, as it is only 0.010, although this is significant for outward interaction (0.057) which is also based on a statistical level of 0.01.
We run the Monte Carlo simulations with importance sampling with the bias coefficient a = 0.9.
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Finally, the genetic algorithm is adopted to optimize the bias coefficients to achieve better control performance.
Firstly, for the combustion control system with the varying variable bias and bi-double crossing limit, the ranges of bias coefficients are analyzed gradually.
In the difference model (model 3), bias coefficients for internal and outward interaction changes are 0.008 and 0.016, respectively.
Comparatively, variations of outward interaction are all significant in the three models, and their bias coefficients are positive.
In the presence of bias, bias coefficients will be significantly different than zero and the regression line will have a slope.
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