Optimal centralized control application on microgrids

Hajar, Khaled; Hably, Ahmad; Bacha, Seddik; Elrafhi, Ahmad; Obeid, Ziad

doi:10.1109/redec.2016.7577549

Cited by 10 publications

(11 citation statements)

References 11 publications

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“…The integration of all those strategies through an MGCC has not been reported by previous studies, to the best authors' knowledge. It is worth pointing out that most of previous studies for this kind of MG are theoretical, having been validated by simulation results [4,[28][29][30][31]34,35]. In this paper, the experimental validation of the MGCC centralized algorithm in a DC microgrid is shown.…”

Section: Introductionmentioning

confidence: 76%

“…However, that study is beyond the scope of this paper. Besides, some previous works [1,20] recommend centralized solutions for small scale microgrids.Up to the present different centralized control strategies of microgrids have been proposed in the literature [28][29][30]. In [28], a control strategy for a DC microgrid was proposed.…”

mentioning

confidence: 99%

“…The strategy was aimed at minimizing the daily total energy costs. In [29], an optimization algorithm was applied to a group of interconnected MGs with the main grid. The procedures under study were charging/discharging of the ESS, starting or stopping the DGs, and receiving/sending power from/to neighboring MGs.…”

mentioning

confidence: 99%

“…Up to the present different centralized control strategies of microgrids have been proposed in the literature [28][29][30]. In [28], a control strategy for a DC microgrid was proposed.…”

mentioning

confidence: 99%

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Experimental Study of a Centralized Control Strategy of a DC Microgrid Working in Grid Connected Mode

et al. 2017

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The results concerning the integration of a set of power management strategies and serial communications for the efficient coordination of the power converters composing an experimental DC microgrid is presented. The DC microgrid operates in grid connected mode by means of an interlinking converter. The overall control is carried out by means of a centralized microgrid controller implemented on a Texas Instruments TMS320F28335 DSP. The main objectives of the applied control strategies are to ensure the extract/inject power limits established by the grid operator as well as the renewable generation limits if it is required; to devise a realistic charging procedure of the energy storage batteries as a function of the microgrid status; to manage sudden changes of the available power from the photovoltaic energy sources, of the load power demand and of the power references established by the central controller; and to implement a load shedding functionality. The experimental results demonstrate that the proposed power management methodology allows the control of the power dispatch inside the DC microgrid properly.2 of 25 highly stable, even in the case of low quality distribution grids [8]. When the distribution grid fails, the microgrid must regulate the DC bus voltage without the ILC. Some control methods have been developed and proposed in the literature [9][10][11] for reaching this goal. The typical objectives of the DC microgrid in grid-connected mode are: to minimize the cost of the imported energy from the main grid, to optimize the power dispatch among the converters and the DC bus and to regulate the DC bus voltage [12]. For the optimization of the power dispatch, communications between the devices of the MG and the grid operator are necessary [13,14].Regarding the control system, one of the main challenges in MGs is how to maintain the generation and consumption energy balance [15]. Power imbalance is a common scenario in MGs, which is caused by the discontinuous power generation availability caused in turn by the intermittent nature of renewables and the variable power demand of the loads connected to the MG, among other factors. These imbalances should be managed fast, safely and effectively by the MG control in order to avoid electrical transients, which can damage or destabilize the system [6][7][8]. Therefore, proper power management control strategies have been developed. These strategies are aimed mainly at: (i) controlling the connected DGs and energy storage system, (ii) regulating the DC bus voltage, (iii) optimizing the power dispatch between DC/DC converters and the DC bus voltage to minimize the cost of imported energy from the main grid, (iv) managing and optimizing the ESS operation, and (v) managing current sharing between parallel converters [16,17]. At present, the major control strategies to maintain power balance in DC microgrids are the well-known droop control methods [14][15][16][17][18], which don't require any communication infrastructure, or other solutions using communications [2...

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Section: Introductionmentioning

confidence: 76%

mentioning

confidence: 99%

mentioning

confidence: 99%

“…Up to the present different centralized control strategies of microgrids have been proposed in the literature [28][29][30]. In [28], a control strategy for a DC microgrid was proposed.…”

mentioning

confidence: 99%

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Experimental Study of a Centralized Control Strategy of a DC Microgrid Working in Grid Connected Mode

et al. 2017

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“…The secondary control, which can be centralized [132][133][134][135][136] or decentralized [137][138][139][140][141], is used to eliminate the deviation of output voltage and frequency in the primary control. In case of an AC MG, the frequency and amplitude restoration controllers G ω and G E can be denoted as follows:…”

Section: A the Classical Hierarchical Control Strategies Formentioning

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.

367

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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Emerging technologies, opportunities and challenges for microgrid stability and control

Satapathy,

Mohanty,

Mohanty

et al. 2024

Energy Reports

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Optimal centralized control application on microgrids

Abstract: In this paper, an optimization algorithm has been applied on a group of interconnected microgrids with the main grid. The objective is to maximize the benefits for all the elements of the grid. Results have shown the performance of the proposed algorithm.

Cited by 10 publications

References 11 publications

Experimental Study of a Centralized Control Strategy of a DC Microgrid Working in Grid Connected Mode

Experimental Study of a Centralized Control Strategy of a DC Microgrid Working in Grid Connected Mode

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

Emerging technologies, opportunities and challenges for microgrid stability and control

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