Design of fractional order PID controller for automatic regulator voltage system based on multi-objective extremal optimization

Zeng, Guo‐Qiang; Chen, Jie; Dai, Yuxing; Li, Limin; Chen, Zheng; Chen, Min-Rong

doi:10.1016/j.neucom.2015.02.051

Cited by 273 publications

(117 citation statements)

References 56 publications

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“…However, from the theoretical perspective, the optimal design issue of the weighting vectors, prediction horizon and control horizon in the proposed MPC method is still challenging. From the perspective of engineering practice, the proposed method will be further studied in depth by tuning the weighting vectors, prediction horizon and control horizon based on evolutionary algorithms, such as multi-objective optimization algorithms [46][47][48]. On the other hand, the extension of MPC to more complex power systems by taking into account the robust control performance indices [45] and real-time predictive power of renewable energy systems [49] is another significant subject of future investigation.…”

Section: Discussionmentioning

confidence: 99%

An Adaptive Model Predictive Load Frequency Control Method for Multi-Area Interconnected Power Systems with Photovoltaic Generations

2017

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Abstract:As the penetration level of renewable distributed generations such as wind turbine generator and photovoltaic stations increases, the load frequency control issue of a multi-area interconnected power system becomes more challenging. This paper presents an adaptive model predictive load frequency control method for a multi-area interconnected power system with photovoltaic generation by considering some nonlinear features such as a dead band for governor and generation rate constraint for steam turbine. The dynamic characteristic of this system is formulated as a discrete-time state space model firstly. Then, the predictive dynamic model is obtained by introducing an expanded state vector, and rolling optimization of control signal is implemented based on a cost function by minimizing the weighted sum of square predicted errors and square future control values. The simulation results on a typical two-area power system consisting of photovoltaic and thermal generator have demonstrated the superiority of the proposed model predictive control method to these state-of-the-art control techniques such as firefly algorithm, genetic algorithm, and population extremal optimization-based proportional-integral control methods in cases of normal conditions, load disturbance and parameters uncertainty.

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Section: Discussionmentioning

confidence: 99%

An Adaptive Model Predictive Load Frequency Control Method for Multi-Area Interconnected Power Systems with Photovoltaic Generations

2017

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“…For more than two centuries, this subject was relevant only in pure mathematics, and Euler, Fourier, Abel, Liouville, Riemann, Hadamard, among others, have studied these new fractional operators, by presenting new definitions and studying their most important properties. However, in the past decades, this subject has proven its applicability in many and different natural situations, such as viscoelasticity [11,26], anomalous diffusion [14,19], stochastic processes [9,29], signal and image processing [31], fractional models and control [24,32], etc. This is a very rich field, and for it we find several definitions for fractional integrals and for fractional derivatives [16,25].…”

Section: Introductionmentioning

confidence: 99%

A Caputo fractional derivative of a function with respect to another function

Almeida

2017

Communications in Nonlinear Science and Numerical Simulation

875

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In this paper we consider a Caputo type fractional derivative with respect to another function. Some properties, like the semigroup law, a relationship between the fractional derivative and the fractional integral, Taylor's Theorem, Fermat's Theorem, etc, are studied. Also, a numerical method to deal with such operators, consisting in approximating the fractional derivative by a sum that depends on the first-order derivative, is presented. Relying on examples, we show the efficiency and applicability of the method. Finally, an application of the fractional derivative, by considering a Population Growth Model, and showing that we can model more accurately the process using different kernels for the fractional operator is provided.Mathematics Subject Classification 2010: 26A33, 34A08, 65L05, 34K60.

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“…Consequently, EO has attracted increasing attention recently for its wide applications in various benchmark and real-world engineering optimization problems [31,32]. However, there are only few multi-objective evolutionary algorithms based on the EO mechanism [33][34][35][36][37]. An individual elitist (1+λ) multi-objective extremal optimization algorithm [33] is based on a single solution and a hybrid mutation operator combining Gaussian mutation with Cauchy mutation to enhance the exploratory capabilities.…”

Section: Introductionmentioning

confidence: 99%

“…An individual elitist (1+λ) multi-objective extremal optimization algorithm [33] is based on a single solution and a hybrid mutation operator combining Gaussian mutation with Cauchy mutation to enhance the exploratory capabilities. In our recent research work, a modified multi-objective extremal optimization based on individual iterated optimization mechanisms has been presented to design FOPID controllers for automatic voltage regulator systems [37]. On the other hand, another version called multi-objective population-based extremal optimization (MOPEO) is proposed by combining population-based optimization mechanism and a popular mutation operator called non-uniform mutation [34].…”

Section: Introductionmentioning

confidence: 99%

Design of a Fractional Order Frequency PID Controller for an Islanded Microgrid: A Multi-Objective Extremal Optimization Method

et al. 2017

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Abstract:Fractional order proportional-integral-derivative(FOPID) controllers have attracted increasing attentions recently due to their better control performance than the traditional integer-order proportional-integral-derivative (PID) controllers. However, there are only few studies concerning the fractional order control of microgrids based on evolutionary algorithms. From the perspective of multi-objective optimization, this paper presents an effective FOPID based frequency controller design method called MOEO-FOPID for an islanded microgrid by using a Multi-objective extremal optimization (MOEO) algorithm to minimize frequency deviation and controller output signal simultaneously in order to improve finally the efficient operation of distributed generations and energy storage devices. Its superiority to nondominated sorting genetic algorithm-II (NSGA-II) based FOPID/PID controllers and other recently reported single-objective evolutionary algorithms such as Kriging-based surrogate modeling and real-coded population extremal optimization-based FOPID controllers is demonstrated by the simulation studies on a typical islanded microgrid in terms of the control performance including frequency deviation, deficit grid power, controller output signal and robustness.

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Design of fractional order PID controller for automatic regulator voltage system based on multi-objective extremal optimization

Cited by 273 publications

References 56 publications

An Adaptive Model Predictive Load Frequency Control Method for Multi-Area Interconnected Power Systems with Photovoltaic Generations

An Adaptive Model Predictive Load Frequency Control Method for Multi-Area Interconnected Power Systems with Photovoltaic Generations

A Caputo fractional derivative of a function with respect to another function

Design of a Fractional Order Frequency PID Controller for an Islanded Microgrid: A Multi-Objective Extremal Optimization Method

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