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cooperative control and advanced management of distributed generators in a smart grid

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Date Issued:
2013
Abstract/Description:
Smart grid is more than just the smart meters. The future smart grids are expected to include ahigh penetration of distributed generations (DGs), most of which will consist of renewable energysources, such as solar or wind energy. It is believed that the high penetration of DGs will resultin the reduction of power losses, voltage profile improvement, meeting future load demand, andoptimizingthe use of non-conventionalenergy sources. However, more serious problems will ariseif a decent control mechanism is not exploited. An improperly managed high PV penetration maycause voltage profile disturbance, conflict with conventional network protection devices, interferewith transformer tap changers, and as a result, cause network instability.Indeed, it is feasible to organize DGs in a microgrid structure which will be connected to the maingrid through a point of common coupling (PCC). Microgrids are natural innovation zones for thesmart grid because of their scalability and flexibility. A proper organization and control of theinteraction between the microgrid and the smartgrid is a challenge.Cooperative control makes it possible to organize different agents in a networked system to actas a group and realize the designated objectives. Cooperative control has been already appliedto the autonomous vehicles and this work investigates its application in controlling the DGs in amicro grid. The microgrid power objectives are set by a higher level control and the application ofthe cooperative control makes it possible for the DGs to utilize a low bandwidth communicationnetwork and realize the objectives.Initially, the basics of the application of the DGs cooperative control are formulated. This includesorganizing all the DGs of a microgrid to satisfy an active and a reactive power objective. Then, thecooperative control is further developed by the introduction of clustering DGs into several groupsto satisfy multiple power objectives. Then, the cooperative distribution optimization is introducedto optimally dispatch the reactive power of the DGs to realize a unified microgrid voltage profileand minimizethelosses. Thisdistributedoptimizationis agradient based techniqueand itis shownthat when the communication is down, it reduces to a form of droop. However, this gradient baseddroop exhibits a superior performance in the transient response, by eliminating the overshootscaused by the conventional droop.Meanwhile, the interaction between each microgrid and the main grid can be formulated as aStackelberg game. The main grid as the leader, by offering proper energy price to the micro grid,minimizes its cost and secures the power. This not only optimizes the economical interests ofboth sides, the microgrids and the main grid, but also yields an improved power flow and shavesthe peak power. As such, a smartgrid may treat microgrids as individually dispatchable loads orgenerators.
Title: cooperative control and advanced management of distributed generators in a smart grid.
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Name(s): Maknouninejad, Ali, Author
Qu, Zhihua, Committee Chair
Lotfifard, Saeed, Committee Member
Haralambous, Michael, Committee Member
Wu, Xinzhang, Committee Member
Kutkut, Nasser, Committee Member
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2013
Publisher: University of Central Florida
Language(s): English
Abstract/Description: Smart grid is more than just the smart meters. The future smart grids are expected to include ahigh penetration of distributed generations (DGs), most of which will consist of renewable energysources, such as solar or wind energy. It is believed that the high penetration of DGs will resultin the reduction of power losses, voltage profile improvement, meeting future load demand, andoptimizingthe use of non-conventionalenergy sources. However, more serious problems will ariseif a decent control mechanism is not exploited. An improperly managed high PV penetration maycause voltage profile disturbance, conflict with conventional network protection devices, interferewith transformer tap changers, and as a result, cause network instability.Indeed, it is feasible to organize DGs in a microgrid structure which will be connected to the maingrid through a point of common coupling (PCC). Microgrids are natural innovation zones for thesmart grid because of their scalability and flexibility. A proper organization and control of theinteraction between the microgrid and the smartgrid is a challenge.Cooperative control makes it possible to organize different agents in a networked system to actas a group and realize the designated objectives. Cooperative control has been already appliedto the autonomous vehicles and this work investigates its application in controlling the DGs in amicro grid. The microgrid power objectives are set by a higher level control and the application ofthe cooperative control makes it possible for the DGs to utilize a low bandwidth communicationnetwork and realize the objectives.Initially, the basics of the application of the DGs cooperative control are formulated. This includesorganizing all the DGs of a microgrid to satisfy an active and a reactive power objective. Then, thecooperative control is further developed by the introduction of clustering DGs into several groupsto satisfy multiple power objectives. Then, the cooperative distribution optimization is introducedto optimally dispatch the reactive power of the DGs to realize a unified microgrid voltage profileand minimizethelosses. Thisdistributedoptimizationis agradient based techniqueand itis shownthat when the communication is down, it reduces to a form of droop. However, this gradient baseddroop exhibits a superior performance in the transient response, by eliminating the overshootscaused by the conventional droop.Meanwhile, the interaction between each microgrid and the main grid can be formulated as aStackelberg game. The main grid as the leader, by offering proper energy price to the micro grid,minimizes its cost and secures the power. This not only optimizes the economical interests ofboth sides, the microgrids and the main grid, but also yields an improved power flow and shavesthe peak power. As such, a smartgrid may treat microgrids as individually dispatchable loads orgenerators.
Identifier: CFE0004712 (IID), ucf:49817 (fedora)
Note(s): 2013-05-01
Ph.D.
Engineering and Computer Science, Electrical Engineering and Computer Science
Doctoral
This record was generated from author submitted information.
Subject(s): Smart grid -- distributed generators -- cooperative control -- cooperative distributed optimization -- microgrid
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFE0004712
Restrictions on Access: public 2013-05-15
Host Institution: UCF

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