Towards Optimal Management in Microgrids: An Overview

Inclusion of intermittent natured renewable energy resources in microgrid to reduce global warming, especially in shipboard power system and due to highly fluctuating propulsion load, frequency control strategy of isolated shipboard hybrid microgrid (ISHMG) is major point of attraction. Hence, a power system of marine vessel with dish‐stirling solar thermal system (DSTS), wind‐driven generation (WDG), solid oxide fuel cell (SOFC), super‐conducting magnetic energy storage (SMES), two different AC‐loads, and propulsion loads are considered as an ISHMG. The main objective of this paper is reducing the mismatch between generation and demand with the help of fractional‐order proportional integral‐derivative (FOPID) controller. To improve the frequency control, the tuning of the controller coefficients plays a major role as the controller's performance fully dependent on the parameters. Accordingly, the recently developed butterfly optimization algorithm (BOA) has been used to optimize the FOPID controller's parameters. Comparative analysis of several techniques like FA, PSO, GOA, SSA, and BOA used for PID, PI, FOPID controllers' optimization, and sensitivity analysis under different parametric variation has been presented to prove the stability of the ISHMG model. Analyzing all the results, it is found that BOA‐based FOPID controller is performing the frequency control far better than other techniques.

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“…The TF of the AC‐load‐1 and AC‐load‐2 can be depicted as 37 :

G_{{AL}_{1}} (s) = \frac{K_{{AL}_{1}}}{1 + {italicsT}_{{AL}_{1}}}

G_{{AL}_{2}} (s) = \frac{K_{{AL}_{2}}}{1 + {italicsT}_{{AL}_{2}}}

…”

Section: Modeling Of a Proposed Shipboard Microgridmentioning

confidence: 99%

Frequency regulation of hybrid shipboard microgrid system using butterfly optimization algorithm synthesis fractional‐order controller

Mondal

Latif

Das

et al. 2022

Int J Numerical Modelling

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“…Brief Description [18] A multi-disciplinary portrait of MG drivers, real-world applications, challenges, and future prospects is provided [26] MG control objectives, in particular in islanded mode, are discussed [27] A review of experimental MGs and test systems around the world is conducted [28] A review of the most relevant research works on NMGs is conducted [29] Control strategies for DC MGs are discussed [30] An overview of solutions evaluated during the last years by the scientific community for MG optimal management is given [31] A review of optimization techniques for the management of isolated MGs with hybrid renewable sources is conducted [32] An analysis of decision making strategies and their solution methods for MG energy management systems is performned [33] An overview of primary and seconderay control approaches for DC MGs is provided [34] A review of EMS control strategies for MGs with DERs is conducted, with a focus on energy storage [35] A review of energy management in renewable energy based MGs is conducted [36] Smart approaches for power grid monitoring and control, in a context of prolific distributed generation, are discussed [37] The application of MPC to MGs and NMGs is reviewed, from the point of view of their main functionalities [38] A review of MPC applied toward the control of MGs and NMGs is conducted [39] Coordination strategies and protection schemes that have been proposed for MGs in the last few years are reviewed [40] A review of compensation methods against power quality issues in MGs is conducted [41] An overview of control approaches for inverter-based MGs operating in islanded mode is given [42] A review of droop control techniques to coordinate distributed generators in MGs is conducted [43] Voltage and frequency control strategies of hybrid AC/DC MGs are reviewed [44] A review of AC/DC MGs in connection with RES-based distributed generators, ESSs and loads is conducted [45] A survey of the latest analytical and approximation techniques to model the uncertainties in MGs is presented [46] A survey on hybrid renewable energy system is presented [47] A review of optimization objectives, constraints, tools and algorithms for energy management in MGs is conducted [48] Control objectives and development methodologies in MG supervisory controllers are summarized …”

Section: Papermentioning

confidence: 99%

“…Centralized, decentralized, distributed, and hierarchical control strategies are discussed in this review paper. In [30], Topa Gavilema et al give an overview of different solutions evaluated during the last few years by the scientific community to manage MGs. The review shows the variety of mature and tested solutions for managing MGs with different configurations.…”

Section: Papermentioning

confidence: 99%

A Survey of Recent Advances in the Smart Management of Microgrids and Networked Microgrids

2022

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Microgrids (MGs) and networked (interconnected) microgrids (NMGs) are emerging as an efficient way for integrating distributed energy resources (DERs) into power distribution systems. MGs and NMGs can disconnect from the main grid and operate autonomously, strengthen grid resilience, and help mitigate grid disturbances and maintain power quality. In addition, when supported by sophisticated and efficient management strategies, MGs and NMGs have the ability to enhance power supply reliability. However, their deployment comes with many challenges, in particular regarding the efficient management of DERs. That is why a survey of recent advances in the smart management—the term refers to a variety of planning and control tasks—of MGs and NMGs is presented in this paper. It aims at establishing a picture of strategies and identifying trends in methods. The reader is provided with an in-depth analysis of a variety of papers recently published in peer-reviewed journals: the way the methods are used and the common issues addressed by the scientific community are discussed. Following this analysis, one can especially observe that (1) model-based predictive control (MPC) is emerging as a competitive alternative to conventional methods, in particular in voltage and frequency regulation and DER management (2) due to their ability to handle complex tasks, data-driven strategies are getting more and more attention from the scientific community (3) game theory (GT) is a very good candidate for efficient management of complex systems as NMGs (4) MPC and artificial intelligence are increasingly being used for proper MG islanded operation or to manage electric vehicles (EVs) efficiently.

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“…The state of the art clearly shows that the droop control was the most used control method for sharing the loads demand in a DC microgrid [23][24][25][26][27]. This control method, when the output current increases, linearly reduce the DC output voltage.…”

Section: The Dbs Logicmentioning

confidence: 99%

A Renewable Energy Community of DC Nanogrids for Providing Balancing Services

et al. 2021

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The massive expansion of Distributed Energy Resources and schedulable loads have forced a variation of generation, transmission, and final usage of electricity towards the paradigm of Smart Communities microgrids and of Renewable Energy Communities. In the paper, the use of multiple DC microgrids for residential applications, i.e., the nanogrids, in order to compose and create a renewable energy community, is hypothesized. The DC Bus Signaling distributed control strategy for the power management of each individual nanogrid is applied to satisfy the power flow requests sent from an aggregator. It is important to underline that this is an adaptive control strategy, i.e., it is used when the nanogrid provides a service to the aggregator and when not. In addition, the value of the DC bus voltage of each nanogrid is communicated to the aggregator. In this way, the aggregator is aware of the regulation capacity that each nanogrid can provide and which flexible resources are used to provide this capacity. The effectiveness of the proposed control strategy is demonstrated via numerical experiments. The energy community considered in the paper consists of five nanogrids, interfaced to a common ML-LV substation. The nanogrids, equipped with a photovoltaic plant and a set of lithium-ion batteries, participate in the balancing service depending on its local generation and storage capacity.

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Towards Optimal Management in Microgrids: An Overview

Cited by 22 publications

References 139 publications

Frequency regulation of hybrid shipboard microgrid system using butterfly optimization algorithm synthesis fractional‐order controller

Frequency regulation of hybrid shipboard microgrid system using butterfly optimization algorithm synthesis fractional‐order controller

A Survey of Recent Advances in the Smart Management of Microgrids and Networked Microgrids

A Renewable Energy Community of DC Nanogrids for Providing Balancing Services

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