Designing Structure-Dependent MPC-Based AGC Schemes Considering Network Topology

Jang, Young-Sik; Park, JoonHyung; Yoon, Yong Tae

doi:10.3390/en8053437

Cited by 5 publications

(3 citation statements)

References 9 publications

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“…In order to validate the performances of the previous controller, Jiang et al [24] made further efforts to introduce explicit MPC for the isolated industrial system. Jang et al [25] presented an MPC-based approach considering the topology of power grid for AGC so as to improve the dynamic performance of AGC. Taking into account the size of the grid and regional characteristics, Mohamed et al [26] studied a decentralized model-predictive-based load frequency control method in an interconnected power system.…”

Section: Introductionmentioning

confidence: 99%

A Distributed AGC Method considering Two-Channel Random Delays and Their Difference between Interconnected Power Systems

Zhao

Lin

et al. 2019

Journal of Electrical and Computer Engineering

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With the emergence of the concept of smart grid, the networked automatic generation control (AGC) method has been more and more important for secondary frequency control due to its characteristics such as openness and flexibility. However, the networked AGC system also presents some defects such as time delays and packet dropouts. The existence of time delays makes the traditional AGC strategies more challenging. A novel AGC method is proposed in this paper to mitigate the negative effects of time delays. Firstly, a multiarea power system model is built under the consideration of two-channel time delays: from controller to actuator and from sensor to controller. More practically, the difference of delays between areas is also exhibited in the model. Thus, from the predictive characteristics of model predictive control (MPC), a method of selection with optimization is presented to obtain the appropriate control variable when delays exist. Furthermore, three cases, (a) no processing for delay, (b) control sequence selection, (c) control sequence selection with optimization, are analyzed. The frequency and area control error (ACE) performance are evaluated with step load perturbation and random load perturbation. The simulation results indicate that the system controlled by the proposed method has desired dynamic performances. Consequently, the feasibility and effectiveness of the proposed method are verified.

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Section: Introductionmentioning

confidence: 99%

A Distributed AGC Method considering Two-Channel Random Delays and Their Difference between Interconnected Power Systems

Zhao

Lin

et al. 2019

Journal of Electrical and Computer Engineering

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“…If the sampling information is not received by the controller in time, the lost information can be estimated by the predictive value of previous sampling instant. Additionally, MPC is also an effective method for AGC due to its favorable characteristics [23][24][25]. Therefore, a MPC based distributed AGC method is discussed in this paper for multiarea interconnected power systems with random time delay existing between different regions, together with high penetration of photovoltaic system.…”

Section: Introductionmentioning

confidence: 99%

A System Compensation Based Model Predictive AGC Method for Multiarea Interconnected Power Systems with High Penetration of PV System and Random Time Delay between Different Areas

Zhao

et al. 2018

Mathematical Problems in Engineering

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In order to mitigate the negative influence of geographical dispersity of modern power system and the penetration of renewable energy, a system compensation based model predictive AGC method is proposed in this paper. A compensation unit is introduced in AGC system to reduce the influence of PV power output fluctuation. Furthermore, because the distributed power system is geographically dispersed, which leads to some defects such as time delay and packet dropouts, a selection and optimization algorithm is presented to obtain the appropriate variable when delays exist. Finally, a two-area interconnected power grid with PV systems is shown as an example to testify the feasibility and effectiveness of the proposed method. The simulation results indicate that the system controlled by the proposed method has the expected dynamic performance.

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“…Conventionally, automatic generation control (AGC) has been developed to compensate for the steady-state error that is caused by the primary frequency control. However, the conventional scheme of AGC might be difficult for obtaining a desirable performance due to the low inertia time constant of the MG system and the high penetration of wind generation [6,7]. The energy storage systems (ESSs) with the function of secondary frequency control, which might be a battery energy storage system (BESS), flywheel energy storage system (FESS), or superconducting magnetic energy storage (SMES), have been used in the stand-alone MG system to improve the performance of frequency regulation [8,9].…”

Section: Introductionmentioning

confidence: 99%

Analyzing the Impacts of System Parameters on MPC-Based Frequency Control for a Stand-Alone Microgrid

2017

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Model predictive control (MPC) has been widely studied for regulating frequency in stand-alone microgrids (MGs), owing to the advantages of MPC such as fast response and robustness against the parameter uncertainties. Understanding the impacts of system parameters on the control performance of MPC could be useful for the designing process of the controller to achieve better performance. This study analyzes the impact of system parameters on the control performance of MPC for frequency regulation in a stand-alone MG. The typical stand-alone MG, which consists of a diesel engine generator, an energy storage system (ESS), a wind turbine generator, and a load, is considered in this study. The diesel engine generator is in charge of primary frequency control whereas the ESS is responsible for secondary frequency control. The stand-alone MG is linearized to obtain the dynamic model that is used for designing MPC-based secondary frequency control. The robustness of MPC against the variation of system parameters is also analyzed in this study. A comparison study of MPC and proportional-integral (PI) control is presented. Simulation results show that MPC has a faster response time and lower overshoot compared to PI control. In addition, the robustness of MPC against the system uncertainties is stronger than conventional PI control.

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Designing Structure-Dependent MPC-Based AGC Schemes Considering Network Topology

Cited by 5 publications

References 9 publications

A Distributed AGC Method considering Two-Channel Random Delays and Their Difference between Interconnected Power Systems

A Distributed AGC Method considering Two-Channel Random Delays and Their Difference between Interconnected Power Systems

A System Compensation Based Model Predictive AGC Method for Multiarea Interconnected Power Systems with High Penetration of PV System and Random Time Delay between Different Areas

Analyzing the Impacts of System Parameters on MPC-Based Frequency Control for a Stand-Alone Microgrid

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