Distributed Multi-Agent System-Based Load Frequency Control for Multi-Area Power System in Smart Grid

Singh, Vijay Pratap; Kishor, Nand; Samuel, Paulson

doi:10.1109/tie.2017.2668983

Cited by 146 publications

(64 citation statements)

References 24 publications

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“…A distributed MAS with frequency control scheme is presented in [158], each agent only communicates with the neighboring agents, by adopting the optimal average consensus strategy, all the information can be shared by the distributed control method. In [159], the MAS has been applied to the power management of the islanded MG. Fig. 4(a) shows the framework of the MAS-based MG.…”

Section: B Mas-based Distributed Coordination Control Of the Microgrmentioning

confidence: 99%

MAS-Based Distributed Coordinated Control and Optimization in Microgrid and Microgrid Clusters: A Comprehensive Overview

Han

Zhang

et al. 2018

IEEE Trans. Power Electron.

348

182

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Abstract-The increasing integration of the distributed renewable energy sources highlights the requirement to design various control strategies for microgrids (MGs) and microgrid clusters (MGCs). The multi-agent system (MAS)-based distributed coordinated control strategies shows the benefits to balance the power and energy, stabilize voltage and frequency, achieve economic and coordinated operation among the MGs and MGCs. However, the complex and diverse combinations of distributed generations in multi-agent system increase the complexity of system control and operation. In order to design the optimized configuration and control strategy using MAS, the topology models and mathematic models such as the graph topology model, non-cooperative game model, the genetic algorithm and particle swarm optimization algorithm are summarized. The merits and drawbacks of these control methods are compared. Moreover, since the consensus is a vital problem in the complex dynamical systems, the distributed MAS-based consensus protocols are systematically reviewed. NOMENCLATURE

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Section: B Mas-based Distributed Coordination Control Of the Microgrmentioning

confidence: 99%

MAS-Based Distributed Coordinated Control and Optimization in Microgrid and Microgrid Clusters: A Comprehensive Overview

Han

Zhang

et al. 2018

IEEE Trans. Power Electron.

348

182

View full text Add to dashboard Cite

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“…An SFR model block diagram of a non-reheated power system is shown in Figure 1. Generally, the model is commonly used in load frequency control (LFC) [37,38]. The dynamics of area i considering a multi-area power system is described by the differential Equations (4)- (8).…”

Section: Power System Dynamic Modellingmentioning

confidence: 99%

WAMS-Based Online Disturbance Estimation in Interconnected Power Systems Using Disturbance Observer

et al. 2019

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In the event of a generator loss or disturbance, the power system frequency declines quickly and overall system stability is at risk. During these scenarios, under frequency load shedding is triggered to restore the power system frequency. The main stage of modern adaptive under frequency load shedding techniques is disturbance estimation. However, the swing equation is widely used in disturbance estimation but has some critical estimation errors. In this paper, instead of using the swing equation we proposed the use of a disturbance observer to estimate the curtailed power. By making use of wide area measurements, a system frequency response model, which is a representative of the whole power system, can be realized in real time. Using different power system states of the developed model, a disturbance observer can be designed as well. The main advantage of the disturbance observer is that it can accurately estimate the disturbance magnitude and its location in a very short time. Further investigations show that by using the disturbance observer disturbances, which occur at the same time or at different times in different areas regardless of the magnitude or size, accurate estimations can be made. To ascertain the efficiency of the proposed scheme, simulations are done for a four-area power system using Matlab/Simulink.

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“…Existen varias configuraciones de topologías de conversión de pequeña y mediana potencia, incluyendo su control. Por ejemplo, la configuración de la turbina eólica y su respectivo operación a través de sistemas Multiagente (MAS), cuya función específica resulta en realizar un control inteligente para variables con persistentes cambios en la frecuencia de la carga (Singh, et al, 2017).…”

Section: Controlunclassified

Visión General, Características y Funcionalidades de la Red Eléctrica Inteligente (Smart Grid)

2018

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Este artículo presenta una visión general de la red eléctrica inteligente (Smart Grid) con sus características y funcionalidades y se identifica las actividades de investigación, tendencias, problemas y desafíos de la Smart Grid, Para ello se realizó una revisión de la literatura donde se visualiza como la integración de los recursos energéticos distribuidos (generación distribuida y almacenamiento energético), así como los avances de las tecnologías de la información y las comunicaciones, han desarrollado el concepto de la moderna red eléctrica. En esta área, la implementación de políticas y la rápida integración de sistemas de gestión, están teniendo como resultado una gran revolución en la generación, la trasmisión, la distribución, la operación y el consumo energético.

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Distributed Multi-Agent System-Based Load Frequency Control for Multi-Area Power System in Smart Grid

Cited by 146 publications

References 24 publications

MAS-Based Distributed Coordinated Control and Optimization in Microgrid and Microgrid Clusters: A Comprehensive Overview

MAS-Based Distributed Coordinated Control and Optimization in Microgrid and Microgrid Clusters: A Comprehensive Overview

WAMS-Based Online Disturbance Estimation in Interconnected Power Systems Using Disturbance Observer

Visión General, Características y Funcionalidades de la Red Eléctrica Inteligente (Smart Grid)

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