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Voltage control bandwidth comparison for a four-node system using communication delay and with increasing number of nodes.
Source publication
This study is dedicated to establishing a comparative analysis of the performance ofdifferent local controllers on the cooperative control of DC microgrids. One of the elementary andchallenging issues in DC microgrids is the assurance of fairness in proportional current sharingwhile accomplishing voltage regulation in parallelly connected distribut...
Contexts in source publication
Context 1
... control performance of the two existing techniques and the proposed technique was ensured in the four-node-based system. The voltage control bandwidth / comparison is shown in Table 2 with different communication delays and with increasing number of nodes. ...Context 2
... Table 2, it can be seen that as the communication delay increased from 0.40ms to 0.1ms, the bandwidth of the voltage control loop decreased. The performance of the proposed controller was better compared to the two existing techniques, with a higher voltage control bandwidth. ...Context 3
... performance of the proposed controller was better compared to the two existing techniques, with a higher voltage control bandwidth. The analysis presented in Table 2 was also extended for increasing number of nodes with the communication frequency of 20kHz. When the number of nodes increased in the system, the bandwidth started to decrease. ...Similar publications
In the direct current (DC) microgrid composed of multiple distributed generations, due to the different distances between various converters and the DC bus in the system, the difference of the line resistance will reduce the current sharing accuracy of the system. The droop control was widely used in the operation control of the DC microgrid. It wa...
Citations
... The primary control loop adjusts the frequency and amplitude of the voltage in each DG, while secondary control compensates for the deviations in voltage amplitude and frequency, and finally tertiary control coordinates the overall power flow in and out of the microgrid [11]. Consensus-based methods were used to implement the various control loops in microgrids [7,[14][15][16][17], where each DG is treated as a node in a network, and only relies on information from its neighbouring nodes, unlike in schemes requiring full state knowledge [5,18] or the centralised schemes in [3,19]. A consensus-based scheme for current sharing and voltage regulation was proposed in [7]; the reference voltage into each DG is however assumed to be constant, which may not be realistic given that he microgrid may be subject to fluctuations in demand, and that each DG generally operates under its own varying conditions [4,6]. ...
... • Two observer-based fault-tolerant secondary control schemes for a faulty microgrid are presented. Both schemes use a SMO to estimate faults affecting the microgrid (which were not considered in [4,6,[10][11][12][13][14][15][16][17]), and negate the effect of the faults on the microgrid. • ...
This paper proposes two sliding mode observer (SMO)-based fault-tolerant secondary control schemes for microgrids. The first scheme consists of a central SMO-based fault tolerant controller that uses outputs from the microgrid and estimates all states in the microgrid as well as the fault. The estimated fault is then used to reject the effect of faults on the microgrid. The second scheme is decentralised, where each distributed generator (DG) has its own SMO-based fault tolerant controller which would estimate faults affecting that DG alone, and compensate for faults in only that DG. By rejecting the effect of faults in each DG, the effect of faults on the entire microgrid can be negated. Finally, we simulate an example using both schemes, and its results verify the efficacy of the schemes for fault-tolerant secondary control of microgrids.
The development of cooperative control strategies for microgrids has become an area of increasing research interest in recent years, often a result of advances in other areas of control theory such as multi-agent systems and enabled by rapid advances in wireless communications technology and power electronics. Though the basic concept of cooperative action in microgrids is intuitively well-understood, a comprehensive survey of this approach with respect to its limitations and wide range of potential applications has not yet been provided. The objective of this paper is to provide a broad overview of cooperative control theory as applied to microgrids, introduce other possible applications not previously described, and discuss recent advances and open problems in this area of microgrid research.
To explore the influence of grid connected electric vehicle on microgrid and its collaborative control under the background of new energy power generation, in this study, the constraints of electric vehicle are established from two aspects of electric vehicle travel characteristics and battery charging and discharging characteristics. In view of the variety of controllable resources in microgrid, multi-agent microgrid coordination control architecture is used to control the multi-layer coordination of microgrid, and simulation is built to analyze four different scenes. The results show that in the microgrid load, it is found that the valley peak difference is the smallest when both the electric vehicle and the conventional load participate in the demand response (scene 4). In the change of SOC and charge discharge power of battery energy storage system, it is found that four scenes make the energy storage function of “low storage and high generation” play an effective role. In the economic and environmental benefits of microgrid daily operation, it is found that the daily operation cost and environmental benefits of scene 4 are significantly lower than that of scene 1. Therefore, in this study, the coordinated optimization method of integrating electric vehicle into microgrid based on multi-agent microgrid can effectively solve the coordinated optimization of multi controllable resources of microgrid, and provide experimental basis for the subsequent development and optimization of microgrid.
