Optimal Frequency Regulation in AC Mobile Power Grids Exploiting Bilinear Matrix Inequalities

Javanmardi, Hamidreza; Dehghani, Maryam; Mohammadi, Mohsen; Vafamand, Navid; Dragičević, Tomislav

doi:10.1109/tte.2021.3064864

Cited by 14 publications

(9 citation statements)

References 32 publications

(54 reference statements)

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“…In [20], authors suggested the LMI-based technique for LFC of a shipboard microgrid considering the effect of time delay in the communication links. In [21,22], new formulations are suggested for LFC in shipboard MGs in the form of BMIs. However, linear matrix inequality (LMI)-based methods are conservative in most applications, resulting in the problems' infeasibility.…”

Section: Literature Reviewmentioning

confidence: 99%

Load frequency fractional‐order controller design for shipboard microgrids using direct search alghorithm

Bahrampour

Dehghani

Asemani

et al. 2022

IET Renewable Power Gen

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Load frequency control (LFC) is one of the controversial topics in power systems, especially in shipboard microgrids (SMG). In such applications, renewable energies such as wind, solar, or wave energies provide the power supply. However, changes in the weather conditions or loads can disrupt the frequency. To have a constant frequency in the presence of such turbulence in SMG, a fractional‐order dynamic output feedback controller (FDOFC) is proposed. As a result, the closed‐loop system is extended to a non‐identical fractional‐order system in the state space model. First, the non‐identical fractional‐order system is transformed into an identical one using the least common multiple techniques to determine control parameters. Subsequently, using a direct search algorithm, a considered initial design space is divided into smaller totally stable (TS) sub‐spaces. Then, among all TS controller parameters, the H∞$H_{\infty }$ controller is designed to reduce the effects of disturbances. The study is carried out on a practical SMG system to show the practicality of the proposed FDOFC. Finally, to evaluate the proposed method's efficiency, the SMG results are compared with the results obtained with μ synthesis, H∞$H_{\infty }$, Bilinear Matrix Inequality (BMI)‐based, and fuzzy fractional optimization methods. Compared to the state‐of‐the‐art approaches, more promising results are obtained for H∞$H_{\infty }$‐norm of the closed‐loop system about ten times smaller, that is, false|false|normalΔffalse|false|∞=0.00026$||\Delta f||_\infty = 0.00026$ which is such a negligible norm that concludes perfect disturbance rejection. Moreover, in more scenarios, the robustness of the designed framework is evaluated under parameter variations and time delays in communication. The results show that the maximum frequency deviation is 2.5×10−3$2.5 \times 10^{-3}$, which is very small. Therefore, the controller also works impressively under deviations of SMG system parameters, and communication time delays.

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Section: Literature Reviewmentioning

confidence: 99%

Load frequency fractional‐order controller design for shipboard microgrids using direct search alghorithm

Bahrampour

Dehghani

Asemani

et al. 2022

IET Renewable Power Gen

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“…Since the fuel current v 1 = i h fc should track the reference v 1,d = I re f given in (11). Define the tracking error as z 1 = v 1 − v 1,d − q 1 with q 1 is evoluted by…”

Section: Backstepping Design Proceduresmentioning

confidence: 99%

“…In the last decades, a large number of shipbuilding companies have tried to develop the more-electric ships, by integrating renewable energy sources and energy storage devices to alleviate the expenditure of fossil fuel and air emissions [6]. In this regard, hybrid-electric power and propellant apparatus has a huge potential to minimize the destructive effects of environmental issues in modern high-speed ferries [7][8][9][10][11].…”

Section: Motivation and Backgroundmentioning

confidence: 99%

Robust NN‐based backstepping control of non‐affine ferry ship fuel cell‐based DC MGs under stochastic disturbance inputs

Vafamand

Afsharinejad

Arefi

et al. 2022

IET Renewable Power Gen

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Fossil fuels play a significant role in the automobile industry, as well as marine vessel systems, with a lot of benefits like high-density and low-cost power supply, which is relatively easy to reserve, apply and carry. However, fossil fuel combustion produces several emissions such as CO 2 , which become greenhouse gas emissions and harmful to human health. One of the most favorable emission-free modern technologies is fuel cells, which can be applied to supply power to marine vessel propulsion systems. In such a most electrified ship, the whole of the shipboard grid can be regarded as a direct current (DC) stand-alone microgrid (MG) configuration with linear resistive and nonlinear constant power loads (CPLs). The main challenge in this new configuration of the shipboard MG is stabilizing the system's currents and voltages, subjected to stochastic disturbances arising from the effect of external winds and waves. Hence, the key objective of this research is to introduce a new modified robust adaptive stochastic backstepping controller, which is equipped with an artificial neural network, for stabilizing the current and voltage of the DC MG. The developed approach is robust against uncertainties and disturbances, has a systematic design procedure, and offers a low computational burden compared to the other complicated nonlinear controllers. In the end, a simulation is run for investigating the performance of the proposed controller over the state-of-the-art methods.

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“…Farsani et al [17] introduced the frequency control based on robust µand mixed µ-synthesis by considering system uncertainties and external disturbances for an alternating current (AC) shipboard microgrid. For the same system, Javanmardi et al [18] used bilinear matrix inequalities to design the H ∞ controller. In [19], a robust extended H ∞ control strategy based on the linear matrix inequality method was proposed for islanded microgrids.…”

Section: Literature Reviewmentioning

confidence: 99%

“…For the same system, Javanmardi et al. [18] used bilinear matrix inequalities to design the H ∞ controller. In [19], a robust extended H ∞ control strategy based on the linear matrix inequality method was proposed for islanded microgrids.…”

Section: Literature Reviewmentioning

confidence: 99%

Adaptive constrained population extremal optimisation‐based robust proportional‐integral‐derivation frequency control method for an islanded microgrid

Zeng

Zhou

2021

IET Cyber-Syst and Robotics

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The expected penetration of renewable sources is driving the islanded microgrid towards uncertainties, which have highly influence the reliability and complexities of frequency control. To alleviate the influence caused by load fluctuations and inherent variability of renewable sources, this article proposes an optimised robust proportional-integralderivation (PID) frequency control method by taking full advantage of a robust control strategy while simultaneously maintaining the basic characteristics of a PID controller. During the process of iterated optimisation, a weighted objective function is used to balance the tracking error performance, robust stability and disturbance attenuation performance. Then, the robust PID frequency (RPIDF) controller is determined by an adaptive constrained population extremal optimisation algorithm based on self-adaptive penalty constraint-handling technique. The proposed control method is examined on a typical islanded microgrid, and the control performance is evaluated under various disturbances and parametric uncertainties. Finally, the simulation results indicate that the fitness value of the proposed method is 1.7872, which is lower than 2.9585 and 3.0887 obtained by two other evolutionary algorithms-based RPIDF controllers. Moreover, the comprehensive simulation results fully demonstrate that the proposed method is superior to other comparison methods in terms of four performance indices on the most considered scenarios. K E Y W O R D S constrained evolutionary algorithm, frequency control, islanded microgrid, population extremal optimisation, robust PID controllerThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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Optimal Frequency Regulation in AC Mobile Power Grids Exploiting Bilinear Matrix Inequalities

Cited by 14 publications

References 32 publications

Load frequency fractional‐order controller design for shipboard microgrids using direct search alghorithm

Load frequency fractional‐order controller design for shipboard microgrids using direct search alghorithm

Robust NN‐based backstepping control of non‐affine ferry ship fuel cell‐based DC MGs under stochastic disturbance inputs

Adaptive constrained population extremal optimisation‐based robust proportional‐integral‐derivation frequency control method for an islanded microgrid

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