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Journal ArticleDOI

Robust distributed MPC for load frequency control of uncertain power systems

TL;DR: In this paper, a robust distributed model predictive control (RDMPC) based on linear matrix inequalities is proposed to solve a series of local convex optimization problems to minimize an attractive range for a robust performance objective by using a time-varying statefeedback controller for each control area.
About: This article is published in Control Engineering Practice.The article was published on 2016-11-01. It has received 55 citations till now. The article focuses on the topics: Electric power system & Convex optimization.
Citations
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Journal ArticleDOI
TL;DR: The comprehensive experimental results fully demonstrate that the proposed control scheme in this paper performs better than other control strategies on the most considered scenarios under the conditions of load disturbance and parameters uncertainties in terms of system response and control performance indices.

131 citations

Journal ArticleDOI
TL;DR: The obtained results confirmed the accuracy and reliability of the proposed approach in designing LFC for multi-interconnected power systems.
Abstract: This paper proposes optimal load frequency control (LFC) designed by Adaptive Neuro Fuzzy Inference System (ANFIS) trained via antlion optimizer (ALO) for multi-interconnected system comprising renewable energy sources (RESs). Two systems are modeled and investigated; the first one has two plants of grid connected photovoltaic (PV) system with maximum power point tracker (MPPT) and thermal plant while the second comprises four plants of thermal, wind turbine and grid connected PV systems. ALO is employed to get the optimal gains of Proportional-Integral (PI) controller such that the integral time absolute error (ITAE) of frequency and tie line power deviations is minimized. The input and output of the optimized PI controller are used to train the ANFIS-LFC with Gaussian surface membership functions. Different load disturbances are studied and the results are compared with other reported approaches. The obtained results confirmed the accuracy and reliability of the proposed approach in designing LFC for multi-interconnected power systems.

91 citations

Journal ArticleDOI
TL;DR: A novel, unknown input functional observer based optimal load frequency control approach for real-world complex nonlinear power systems that is able to handle parametric and nonparametric uncertainties, control loop and sensor faults, unknown inputs, and cyber-attacks.
Abstract: This paper proposes a novel, unknown input functional observer based optimal load frequency control approach for real-world complex nonlinear power systems. In the proposed control approach, the control signal applied to each power plant is directly estimated via the well-designed functional observer. The proposed functional dynamic estimator is able to handle parametric and nonparametric uncertainties, control loop and sensor faults, unknown inputs, and cyber-attacks. The observer for each power plant is decoupled from the other plants resulting in a more feasible implementation, reducing the complexity of the estimator and improving the reliability of the proposed control system. The applicability of the proposed method is shown on IEEE 39 bus-system divided into three control areas. The effectiveness of the proposed control scheme is verified by comparing results with well-known control schemes. Tolerance of the proposed technique to unknown inputs, uncertainties, and possible cyber-attacks is verified by several simulation scenarios.

88 citations


Cites methods from "Robust distributed MPC for load fre..."

  • ...In the first group, methods such as model predictive control [3]–[5], optimal control [6], sliding mode control [7], intelligent control methods [8]–[10], and evolutionary computing based tuning load frequency controllers [11]–[15] are reported....

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Journal ArticleDOI
TL;DR: A novel cascade fuzzy-proportional integral derivative incorporating filter (PIDN)-fractional order PIDN (FPIDN-FOPIDN) controller is offered as an expert control strategy to deal effectively with AGC issue of IPS.

80 citations

Journal ArticleDOI
TL;DR: The work proposes a review of those called traditional and those who combined the traditional controller and artificial intelligence algorithms, and introduces the need of more controllers when taking into account the integration of renewable energy sources into the traditional power system.

80 citations

References
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Journal ArticleDOI
TL;DR: This paper presents a new approach for robust MPC synthesis that allows explicit incorporation of the description of plant uncertainty in the problem formulation, and shows that the feasible receding horizon state-feedback control design robustly stabilizes the set of uncertain plants.

2,329 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present a critical literature review and an up-to-date and exhaustive bibliography on the AGC of power systems, highlighting various control aspects concerning the AGG problem.
Abstract: An attempt is made in This work to present critical literature review and an up-to-date and exhaustive bibliography on the AGC of power systems. Various control aspects concerning the AGC problem have been highlighted. AGC schemes based on parameters, such as linear and nonlinear power system models, classical and optimal control, and centralized, decentralized, and multilevel control, are discussed. AGC strategies based on digital, self-tuning control, adaptive, VSS systems, and intelligent/soft computing control have been included. Finally, the investigations on AGC systems incorporating BES/SMES, wind turbines, FACTS devices, and PV systems have also been discussed.

836 citations

Journal ArticleDOI
TL;DR: A distributed model predictive control framework, suitable for controlling large-scale networked systems such as power systems, is presented and the distributed MPC algorithm is feasible and closed-loop stable under intermediate termination.
Abstract: A distributed model predictive control (MPC) framework, suitable for controlling large-scale networked systems such as power systems, is presented. The overall system is decomposed into subsystems, each with its own MPC controller. These subsystem-based MPCs work iteratively and cooperatively towards satisfying systemwide control objectives. If available computational time allows convergence, the proposed distributed MPC framework achieves performance equivalent to centralized MPC. Furthermore, the distributed MPC algorithm is feasible and closed-loop stable under intermediate termination. Automatic generation control (AGC) provides a practical example for illustrating the efficacy of the proposed distributed MPC framework.

774 citations