Advanced Energy Management of a Micro-grid Using Arduino and Multi-agent System

Raju, Leo; Morais, Antony Amalraj; Milton, Robert

doi:10.1007/978-981-10-4852-4_6

Cited by 9 publications

(7 citation statements)

References 9 publications

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“…e myopic strategy, as it was demonstrated earlier in this paper, is an example strategy of this type of approaches. Papers using this method [8,10,11,15,21,24,[35][36][37] proved the effectiveness of such strategies through simulations. More advanced techniques can be incorporated with rule-based approaches for higher efficiency.…”

Section: Algorithmsmentioning

confidence: 97%

“…e authors in [24] used it in their control strategy to keep the voltage network under a stable state. In [33,35], loads were divided into critical and noncritical (i.e., ordinary) loads. In an event of overloads, the system starts dropping the noncritical loads starting with the least priority ones.…”

Section: Journal Of Electrical and Computer Engineeringmentioning

confidence: 99%

“…More advanced techniques can be incorporated with rule-based approaches for higher efficiency. We cite as examples artificial neural networks (ANN) [33], fuzzy logic [34], and the adoption of multiagent systems (MAS) [35][36][37]44]. e use of the latter technique has garnered much interest lately.…”

Section: Algorithmsmentioning

confidence: 99%

“…Pymo is a python-based optimization tool for LP, nonlinear programming, and mixed integer LP (MILP). JADE (java agent development environment) is also used for the modelling of MAS systems [35,44].…”

Section: Toolsmentioning

confidence: 99%

See 3 more Smart Citations

Energy Management Strategies for Smart Green MicroGrid Systems: A Systematic Literature Review

Essayeh

Fenni

Dahmouni

et al. 2021

Journal of Electrical and Computer Engineering

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Having neither precise definition nor a commonly accepted scope, the term “MicroGrid” tends to be used differently across researchers and practitioners alike. The management of energy usage within a microgrid is one of the topics that was handled from numerous perspectives. This study presents systematic literature review (SLR) of research on architectures and energy management techniques for microgrids, providing an aggregated up-to-date catalogue of solutions suggested by the scientific community. The SLR incorporated 45 papers selected according to inclusion/exclusion criteria and defined a priori. The selection process was based on an automated search and covered three known digital libraries. The extraction process covers three main questions. (i) The architectures of microgrids including their components, their bus configuration, and the adopted utility grid policy. (ii) The employed methods to ensure an optimal usage of energy under uncertainty. (iii) The confronted challenges and constraints of the suggested strategies. The findings of this SLR indicate a great diversity of methods and a rich background. Finally, the SLR suggests that future research should take into account the uncertainty aspect relating to energy management rather than the direct use of historical data as it is commonly done in most research papers. A sensitivity analysis should be provided in the latter case.

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Section: Algorithmsmentioning

confidence: 97%

Section: Journal Of Electrical and Computer Engineeringmentioning

confidence: 99%

Section: Algorithmsmentioning

confidence: 99%

Section: Toolsmentioning

confidence: 99%

See 2 more Smart Citations

Energy Management Strategies for Smart Green MicroGrid Systems: A Systematic Literature Review

Essayeh

Fenni

Dahmouni

et al. 2021

Journal of Electrical and Computer Engineering

View full text Add to dashboard Cite

show abstract

“…Multiagent systems for grid outage management are discussed in [16]. Advanced energy management of microgrid using Arduino and multiagent system is discussed in detail in [17]. Here, only two microgrids are considered and transactive energy management is not adequately addressed.…”

Section: Multiagent Systems In Microgridmentioning

confidence: 99%

Multi-Agent Systems Based Advanced Energy Management of Smart Micro-grid

Raju¹,

Morais²

2020

Multi Agent Systems - Strategies and Applications

Self Cite

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Microgrids play a major role in enabling the widespread adoption of renewable distributed energy resources. However, as the power generated from renewable resources is intermittent in nature, it impacts the dynamics and stability of the microgrid, and hence their integration needs new approaches to coordination and control. The existing systems lack run-time adaptive behavior. To face these constraints, the electric energy system must adapt by integrating Information and Communication Technologies (ICT). Multiagent system (MAS) is emerging as an integrated solution approach to distributed computing, communication, and data integration needs for smart grid application. Distributed and heterogeneous information can be efficiently processed locally, but utilized globally to coordinate distributed knowledge networks, resulting in reduction of information processing time and network bandwidth. Parallel operations, asynchronous communication, and autonomous actions of agents enable MAS to adapt to dynamic changes of the environment, thereby improving the reliability, responsiveness, fault tolerance, and stability of the microgrid. In this chapter, MAS is implemented with Java Agent DEvelopment (JADE) framework for advanced energy management of a microgrid. Also, MAS is linked with Arduino microcontroller for practical verification of agent operations. Three microgrids are interconnected to form a microgrid testbed, and smart grid features such as demand side management and plug and play are implemented, making it into a smart microgrid.

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