A multiagent approach to distribution system restoration

Nagata, T.; Tao, Y.; Sasaki, Hiroshi; Fujita, Hideki

doi:10.1109/pes.2003.1270384

Cited by 17 publications

(5 citation statements)

References 21 publications

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“…In (Amin, 2001), a conceptual framework for a power system self-healing infrastructure is envisaged. In (Nagata & Sasaki, 2002;Nagata et al, 2004;2003a;b), the authors presented a multi-agent system designed for distribution systems restoration. This works abstracts network buses as agents, along with a so called facilitation agent who is responsible for aiding negotiation processes among bus agents.…”

Section: Brief Discussion About the State Of The Artmentioning

confidence: 99%

Agent-Based System Applied to Smart Distribution Grid Operation

Issicaba¹,

Rosa²,

Franchin³

et al. 2012

Practical Applications of Agent-Based Technology

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Section: Brief Discussion About the State Of The Artmentioning

confidence: 99%

Agent-Based System Applied to Smart Distribution Grid Operation

Issicaba¹,

Rosa²,

Franchin³

et al. 2012

Practical Applications of Agent-Based Technology

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“…Resource redistribution RD j is calculated after satisfying the non-shiftable loads and iteratively distributes extra resource to resource deficient loads one unit a time, which is given by Equation 11. Next we calculate surplus/deficiency reserve after re-distribution SRAR i j or DRAR i j for loads 'i' at time of equilibrium 'T j ' as given in Equation12 and Equation 13.…”

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].…”

Section: Co-simulation Platform For Energy Management Systemmentioning

confidence: 99%

“…The transmission of control signal is based on predefined objective function for the enhancement of performance of dynamic system [11]. Numerous researchers have contributed in the area of intelligent systems and autonomous agents, such as [12] uses a general case of using agent in control systems, [13] motivates the uses of agents at different control levels e.g. feeder and load agents.…”

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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“…The Office of Naval Research (ONR) control challenge reference system is presented in the Fig.1 [17]. The complex system includes two finite inertia AC sources and buses, three zonal distribution zones feed by redundant DC power buses, and a variety of dynamic and nonlinear loads.…”

Section: B Navy Ship Reference Systemmentioning

confidence: 99%

Navy ship power system restoration using multi-agent approach

Momoh

2006

2006 IEEE Power Engineering Society General Meeting

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This paper presents a multi-agent system framework that performs system restoration for Navy ship. If Navy surface combatants' electric power supply interruption is caused by a fault, it is important to restore the power system as soon as possible to a target network configuration after the fault. The system views the problem as the interaction of simple independent agents. The approach is implemented using visual c++/JAVA and KQML programming languages. Simulation results have demonstrated that this method is able to reach target configurations.

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A multiagent approach to distribution system restoration

Cited by 17 publications

References 21 publications

Agent-Based System Applied to Smart Distribution Grid Operation

Agent-Based System Applied to Smart Distribution Grid Operation

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

Navy ship power system restoration using multi-agent approach

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