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Section 2 presents the linear model with exponential power errors and the associated likelihood function.
We have developed Bayesian reference analysis for linear models with exponential power errors.
We can see that both Student-t and exponential power errors fits are robust against outliers.
The real and reactive power errors are eliminated by directly calculating the rotor control voltages through DSMC.
The inputs for the proposed control scheme are the DC voltage and reactive power errors at the converter station and the active and reactive power errors at the inverter station of the voltage-source converter-based high voltage direct current transmission (VSC-HVDC) link.
While the Gaussian model fit is clearly and strongly influenced by the outlier, the use of exponential power errors (with the four priors considered here) automatically makes the analysis robust against outliers.
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The controller includes a neuro-fuzzy system with power error and its derivative as inputs.
1) Distributed control using power error of single wind plants as reference input.
2) Integrated control using power error of a wind farm group as reference input.
(a, d) Angle error difference er EIAA angle - er IAA angle ; (b, e) power error difference er EIAA power - er IAA power ; (c, f) RTR of EIAA and IAA.
The decoupling control of d/q-axis voltage reference and active-reactive power error are realized effectively under dq synchronous rotating coordinate.
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