Micro-grid Grid Outage Management Using Multi-agent Systems

Raju, Leo; Morais, Antony Amalraj; Rathnakumar, Ramyaa; Ponnivalavan, Soundaryaa; Thavam, L. D.

doi:10.1109/icrtccm.2017.21

Cited by 14 publications

(11 citation statements)

References 14 publications

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“…As we know, the microgrid is a system which has different levels of entities, and they could be some time seller or buyer. So, in this market scenario, the MAS technology assumes a significant job in power management [107][108], resource allocation, and scheduling [109], controls, and optimizing [110] the microgrid. Fig.17 illustrated a control strategy based on MAS technology.…”

Section: B4 Multi-agent Control Strategymentioning

confidence: 99%

“…Likewise, in other control strategies, this control scheme requires a communication system to establish interaction among agents and micro-terminals in the operating environment. The research works presented in the literature [107,112] adopted the MAS based control algorithms to increase the robustness of MGs against communication failures. In these researches, each ESS unit considered as an agent with the autonomy of balancing the SoC during charging and discharging.…”

Section: B4 Multi-agent Control Strategymentioning

confidence: 99%

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A Comprehensive Review on Power Converters Control and Control Strategies of AC/DC Microgrid

Ansari¹,

Chandel²,

Tariq

2021

IEEE Access

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Owing to the smart lifestyle, environmental consciousness, and dwindling fossil fuel supplies, there is a huge demand for clean and green energy. Microgrid (MG) is a crucial approach to renewable and clean energy. Because of the success of the AC utility grid and the growing demand for critical loads, it is very convenient to provide AC/DC MG that can easily satisfy both the alternating current (AC) MG and the direct current (DC) MG requirements. Due to uncertainty in load variations, main grid failures, intermittent power generations from renewable energy sources (RESs), the synchronization and interconnection of different power converters are the paramount issues in the control of AC/DC MG. This paper presents an overview-oriented state of the art in the recent advancement in control strategies of AC/DC MG and its associated power converters control. Based on recent research, this paper summarizes unobstructed views on different topologies, types of power converters, power converter controls, and control strategies of AC/DC MG. Finally, it identified some future challenges that need to be addressed in order to develop a sustainable and reliable control strategy for AC/DC MG. This paper will serve as a guide for researchers. INDEX TERMS Distributed generation, Microgrids, AC/DC Microgrid, Centralized control, Decentralized control I. INTRODUCTION MGs compromise different RESs, i.e., PV cells, windmills, energy-storing systems (ESS), diesel generator sets, and small hydropower plants, as discussed in the [1,2]. With the advancements in power semiconductor devices, the integration of RESs with leading utility or MG becomes so more accessible. Based on the adopted topology, there are three types of MGs, classified as DC MG, AC MG, and AC/DC MG or hybrid MG [3]. The DC MGs are preferred to supply critical loads like computers, operation theatres, and billing counters. Whereas the AC MGs are preferred in supplying all loads during off-grid or on-grid. The AC/DC MG possesses the characteristics of both DC MG and AC MG. Since begin, in these types of MGs, the power converters are connected in parallel with the MG bus-bar and belong to the parallel topology of MG. Recently a seriescascaded MG topology is being investigated. Inam Ullah Nutkani and et al. in [4] has presented a series-cascaded AC MG topology to integrate the non-dispatchable RESs to the MG and offered its advantages and disadvantages over the parallel topology. Fig.1 shows the different topological advances of MGs.

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Section: B4 Multi-agent Control Strategymentioning

confidence: 99%

Section: B4 Multi-agent Control Strategymentioning

confidence: 99%

A Comprehensive Review on Power Converters Control and Control Strategies of AC/DC Microgrid

Ansari¹,

Chandel²,

Tariq

2021

IEEE Access

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“…FIPA defines a model for an agent platform and a communication language for agents. All platforms to be compliant with FIPA should follow this pattern and understand the language, and JADE is no exception [24]. Compliance essentially requires four features, as shown in the Figure 3:  ACC "Agent Communication Channel" is a mechanism that allows agents (and the platform itself) to communicate with each other.…”

Section: Communications Implemented Through "Jade"mentioning

confidence: 99%

A simulation energy management system of a multi-source renewable energy based on multi agent system

Basma

Oukarfi

2021

IJ-AI

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<p>The intermittent nature of renewable energies sources makes their control difficult. One of the solutions to overcome this handicap is to promote hybridization (multi-source system). To ensure continuity of service, a storage system must be coupled to the system. To do so, artificial intelligence based models are developed to respond optimally to the dilemma of energy supply and demand. These models allow the management of the energy flow between the sources (photovoltaic, wind, battery, super capacitor, and generator) and the variable loads by controlling electronic switches according to the availability of the sources. The artificial intelligence algorithm used in this study is multi agent system (MAS). The simulation results and validation tests shows the effectivenes of the proposed approach.</p>

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“…The recent development of control of microgrid using MAS is given in [14,15]. 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].…”

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

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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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Micro-grid Grid Outage Management Using Multi-agent Systems

Cited by 14 publications

References 14 publications

A Comprehensive Review on Power Converters Control and Control Strategies of AC/DC Microgrid

A Comprehensive Review on Power Converters Control and Control Strategies of AC/DC Microgrid

A simulation energy management system of a multi-source renewable energy based on multi agent system

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

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