IEC61850 Based Operation, Control and Management of Utility Connected Microgrid Using Wireless Technology

Islam, Mojaharul; Lee, Hong‐Hee

doi:10.1007/978-3-642-31576-3_34

Cited by 8 publications

(8 citation statements)

References 12 publications

(12 reference statements)

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“…[16][17]; propose conceptual architectures for the implementation of data transmission networks capable of meeting the restrictions of the Smart Grid applications, e.g. [16,[18][19]; develop algorithms and methodologies to ensure compliance of new protocols, like IPv6, with the QoS requirements for these different classes of applications, e.g. [11].…”

mentioning

confidence: 99%

QoS management in smart grids: a Markovian approach

Silva

Francês

Costa

et al. 2014

J. Microw. Optoelectron. Electromagn. Appl.

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In Smart Grids, a variety of new applications are available to users of the electrical system (from consumers to the electric system operators and market operators). Some applications such as the SCADA systems, which control generators or substations, have consequences, for example, with a communication delay. The result of a failure to deliver a control message due to noncompliance of the time constraint can be catastrophic. On the other hand, applications such as smart metering of consumption have fewer restrictions. Since each type of application has different quality of service requirements (importance, delay, and amount of data to transmit) to transmit its messages, the policy to control and share the resources of the data communication network must consider them. In this paper Markov Decision Process Theory is employed to determine optimal policies to explore as much as possible the availability of throughput in order to transmit all kinds of messages, considering the quality of service requirements defined to each kind of message. First a non-preemptive model is formulated and after that a preemptive model is derived. Numerical results are used to compare FIFO, non-preemptive and preemptive policies.

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mentioning

confidence: 99%

QoS management in smart grids: a Markovian approach

Silva

Francês

Costa

et al. 2014

J. Microw. Optoelectron. Electromagn. Appl.

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“…The function of each agent is defined using a set of behaviour. Each agent performs different autonomous behaviour on the basis of their goal [77]. The autonomous behaviour of agents makes integrating MAS into the energy optimisation of NMGs feasible and even easy.…”

Section: Optimisation Of Energy In Nmgsmentioning

confidence: 99%

Control and optimisation of networked microgrids: A review

Islam

Yang

Ամին

2021

IET Renewable Power Gen

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Microgrids (MGs) have become an integral part of smart grid initiatives for future power system networks. Networked microgrids consist of several neighbouring microgrids connected in a low/medium distribution network. The primary objective of a network is to share surplus/shortage power with neighbouring microgrids to achieve mutual cost‐effective operation, utilising green energy from renewable energy resources in the network and increasing the reliability of customer service. This article classifies networked microgrids on the basis of network formation and provides an overview of recent research on control of networked microgrids. In addition, a state‐of‐the‐art review of optimisation methods is provided to solve the energy optimisation problem in networked microgrids. Furthermore, the advantages and challenges of the networked operation of microgrids are presented as for possible research directions in the future.

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“…After resource allocation we determine surplus or deficiency SD ij of resource to the load using Equation 10. Load having more RA i j reference resource RR i j has surplus resource (SD i j >=0), otherwise deficiency of resource.…”

Section: Load Synchronization Algorithm For Energy Management Of Evmentioning

confidence: 99%

“…There are many real time simulators such as RTDS, HYPERSIM and ARENE [11][12][13][14]. These simulators have the capability to test the power network in real time like QualNet [10]. Real time simulator has the capability to run complex models at the same time as the physical time.…”

Section: Co-simulation Platform For Energy Management Systemmentioning

confidence: 99%

“…The use of distributed control in multiple adjacent areas may lead towards adverse situation, hence the global control can provide better control and is necessary [8,9]. Similar to wide-area controllers (WACs) microgrid energy supply and management system (ESMS) use the distributed energy management services using IEEE 802.11 Wi-MAX [10]. The ESMS has the capability to transmit and receive the information.…”

Section: Introductionmentioning

confidence: 99%

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Impact of Energy Management of Electric Vehicles on Transient Voltage Stability of Microgrid

Khalid

Lin

Zhuo

et al. 2015

WEVJ

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There is cause and effect relationship between increase in load due to increasing penetration of electric vehicles (EV) load that causes unbalanced conditions and affect the power quality such as voltage degradation and even damage the equipment if the system is not properly managed. This paper presents detailed review of energy supply and management in conjunction with load synchronization through EVs for maintaining transient voltage stability by providing reactive power support for the stability of power grid in vehicle-to-grid mode of operations. The energy management system is considered at different levels such as, stand-alone PV, stand-alone wind, stand-alone battery storage, stand-alone EV parking lot, residential feeder and commercial building feeders. First we proposed energy management algorithm, to limit the peak power drawn by EVs from distributed energy resources of microgrid, such that additional electrical resource will be transferred to resource constrained devices. The EVs negotiate based on their demand, priority and available electrical resource such that during higher electricity price the higher priority vehicles still require resource and perform uninterrupted operation. The transfer of electrical resource from one load device to another will help in reducing peak demand and improving the efficiency of the system. Secondly we proposed transient voltage stability margin index (TVSMI) to test the capability of EVs in contributing storage and supply services to the grid. The energy management control simulations are realized in DIgSILENT Power factory.

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IEC61850 Based Operation, Control and Management of Utility Connected Microgrid Using Wireless Technology

Cited by 8 publications

References 12 publications

QoS management in smart grids: a Markovian approach

QoS management in smart grids: a Markovian approach

Control and optimisation of networked microgrids: A review

Impact of Energy Management of Electric Vehicles on Transient Voltage Stability of Microgrid

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