MULTIAGENT-BASED MICROGRID WITH ELECTRIC VEHICLE ALLOCATION PLANNING
The power grid paradigm is expected to be flexible, reliable, and capable of maintaining the stability of power flow from sources to loads within the grid as well as undergo unexpected circumstances during a disaster. It is expected to be able to deal with the problems which may occur in the grid du...
Saved in:
Main Authors: | , |
---|---|
Format: | Theses and Dissertations NonPeerReviewed |
Published: |
[Yogyakarta] : Universitas Gadjah Mada
2014
|
Subjects: | |
Online Access: | https://repository.ugm.ac.id/127930/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=68246 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Universitas Gadjah Mada |
Summary: | The power grid paradigm is expected to be flexible, reliable, and capable of
maintaining the stability of power flow from sources to loads within the grid as well
as undergo unexpected circumstances during a disaster. It is expected to be able to
deal with the problems which may occur in the grid during a disaster, such as
disconnected power links, power shortages, etc. The development of the power grid
paradigms involves the development of Smart Grid and microgrid. In order to support
the operation of Smart Grid and microgrid to deal with problems which may occur
during a disaster, electric vehicle has been considered as the ancillary services.
This research focuses on microgrid which are low voltage electrical networks
that interconnect small, modular generation sources, and proposes an allocation
planning method for electric vehicle (EV) in a multiagent-based microgrid. The
proposed method allocates EV to provide the demanding loads with power based on
demand of loads, stored power in each EV and distance from EV�s location to loads.
The simulation is performed using software agent named DASH and IDE named
IDEA framework. The agents are planted on several PCs to prove the effectiveness of
distributed control on microgrid as well as to demonstrate the communication during
the allocation method process.
From the simulation results we proved our method is effectively and efficiently
able to allocate EVs to several demanding loads based on demands, EV�s charged
power, and distance between EV�s location and loads. |
---|