Model predictive control scheme for coordinated voltage control of power systems at the presence of volatile wind power generation

Yassami, Hossein; Rabiee, Abbas; Jalilvand, Abolfazl; Bayat, F. Kemal

doi:10.1049/iet-gtd.2017.1422

Cited by 12 publications

(8 citation statements)

References 33 publications

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“…The performance indexes of the d ‐axis current and q ‐axis current are defined as follows

J_{cd} false(n false) = false[i_{d}^{normal*} false(n + 1 false) - {\hat{i}}_{d} false(n + 1 false) false]^{^{2}}

and

J_{cq} false(n false) = false[i_{q}^{normal*} false(n + 1 false) - {\hat{i}}_{q} false(n + 1 false) false]^{^{2}}

In this paper, the d ‐axis current reference is selected as zero, and the q ‐axis current command is selected by computing the difference between the speed command and the measured speed, and then executing the predictive speed control algorithm. Taking the partial differential of the

J_{cd} false(n false)

v_{d} false(n false)

and setting the result to zero, we can obtain the following equations [32–34]:

\begin{matrix} right leftthickmathspace.5em \\ \frac{\partial J_{normalcd} (n)}{\partial v_{d} (n)} & = - 2 b_{normalcd} \{[a_{normalcd} i_{d} (n) + b_{normalcd} (v_{d} (n) + L_{q} ω_{normalre} (n) i_{q} (n))] \\ - i_{d}^{*} (n + 1) ...\} \end{matrix}

…”

Section: Predictive Controller Designmentioning

confidence: 99%

Fault‐tolerant matrix‐converter‐controlled IPMSM‐drive system using a predictive controller and sliding‐mode estimator

Liu

Chang

2019

J. eng.

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“…The performance indexes of the d ‐axis current and q ‐axis current are defined as follows

J_{cd} false(n false) = false[i_{d}^{normal*} false(n + 1 false) - {\hat{i}}_{d} false(n + 1 false) false]^{^{2}}

and

J_{cq} false(n false) = false[i_{q}^{normal*} false(n + 1 false) - {\hat{i}}_{q} false(n + 1 false) false]^{^{2}}

J_{cd} false(n false)

v_{d} false(n false)

and setting the result to zero, we can obtain the following equations [32–34]:

\begin{matrix} right leftthickmathspace.5em \\ \frac{\partial J_{normalcd} (n)}{\partial v_{d} (n)} & = - 2 b_{normalcd} \{[a_{normalcd} i_{d} (n) + b_{normalcd} (v_{d} (n) + L_{q} ω_{normalre} (n) i_{q} (n))] \\ - i_{d}^{*} (n + 1) ...\} \end{matrix}

…”

Section: Predictive Controller Designmentioning

confidence: 99%

Fault‐tolerant matrix‐converter‐controlled IPMSM‐drive system using a predictive controller and sliding‐mode estimator

Liu

Chang

2019

J. eng.

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“…Model predictive control (MPC) is an advanced method that has been widely applied to the study of mid‐long term voltage stability control [6–8]. The main advantage of MPC is that it allows the system states at current timeslot to be optimised while keeping those at future timeslots into account.…”

Section: Introductionmentioning

confidence: 99%

Galerkin method‐based model predictive control for mid‐long term voltage stability enhancement

Xia

Shen

et al. 2020

IET gener. transm. distrib.

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“…Control theories are widely used in the wind turbines to increase energy production performance and achieving maximum power extraction goal. Thus, the control subsystems play a vital role in the performance of the wind turbines, and thereby the stability of power systems [1, 2]. In this regard, many approaches have been used to control the wind turbines working in either the partial or full load region.…”

Section: Introductionmentioning

confidence: 99%

Wind turbines robust fault reconstruction using adaptive sliding mode observer

Taherkhani

Bayat

2019

IET Generation, Transmission & Distribution

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Model predictive control scheme for coordinated voltage control of power systems at the presence of volatile wind power generation

Cited by 12 publications

References 33 publications

Fault‐tolerant matrix‐converter‐controlled IPMSM‐drive system using a predictive controller and sliding‐mode estimator

Fault‐tolerant matrix‐converter‐controlled IPMSM‐drive system using a predictive controller and sliding‐mode estimator

Galerkin method‐based model predictive control for mid‐long term voltage stability enhancement

Wind turbines robust fault reconstruction using adaptive sliding mode observer

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