Abstract
A microgrid control system using multi-agent technologies is proposed. In this control system, operation planning is realized based on generation and load forecasting by using artificial neural network and fuzzy systems. Unit commitment of generations includes start/stop of power generations and energy storages. Load following function is accomplished by an adaptive control system based on conventional PI control scheme. To include, in a flexible manner, new generations or loads into the microgrid, multi-agent technologies might be applied. In this paper, at first proposed Microgrid control system is outlined and then field tests outline is stated.
| Original language | English |
|---|---|
| Title of host publication | 41st International Universities Power Engineering Conference, UPEC 2006, Conference Procedings |
| Pages | 232-236 |
| Number of pages | 5 |
| Volume | 1 |
| DOIs | |
| Publication status | Published - 2006 |
| Event | 41st International Universities Power Engineering Conference, UPEC 2006 - Newcastle upon Tyne Duration: 2006 Sep 6 → 2006 Sep 8 |
Other
| Other | 41st International Universities Power Engineering Conference, UPEC 2006 |
|---|---|
| City | Newcastle upon Tyne |
| Period | 06/9/6 → 06/9/8 |
Fingerprint
Keywords
- Generation and load forecasting
- Load following
- Microgrid
- Multi-agent system
- Operation planning
ASJC Scopus subject areas
- Energy Engineering and Power Technology
Cite this
Field tests of a microgrid control system. / Funabashi, T.; Fujita, Goro; Koyanagi, Kaoru; Yokoyama, Ryuichi.
41st International Universities Power Engineering Conference, UPEC 2006, Conference Procedings. Vol. 1 2006. p. 232-236 4218679.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Field tests of a microgrid control system
AU - Funabashi, T.
AU - Fujita, Goro
AU - Koyanagi, Kaoru
AU - Yokoyama, Ryuichi
PY - 2006
Y1 - 2006
N2 - A microgrid control system using multi-agent technologies is proposed. In this control system, operation planning is realized based on generation and load forecasting by using artificial neural network and fuzzy systems. Unit commitment of generations includes start/stop of power generations and energy storages. Load following function is accomplished by an adaptive control system based on conventional PI control scheme. To include, in a flexible manner, new generations or loads into the microgrid, multi-agent technologies might be applied. In this paper, at first proposed Microgrid control system is outlined and then field tests outline is stated.
AB - A microgrid control system using multi-agent technologies is proposed. In this control system, operation planning is realized based on generation and load forecasting by using artificial neural network and fuzzy systems. Unit commitment of generations includes start/stop of power generations and energy storages. Load following function is accomplished by an adaptive control system based on conventional PI control scheme. To include, in a flexible manner, new generations or loads into the microgrid, multi-agent technologies might be applied. In this paper, at first proposed Microgrid control system is outlined and then field tests outline is stated.
KW - Generation and load forecasting
KW - Load following
KW - Microgrid
KW - Multi-agent system
KW - Operation planning
UR - http://www.scopus.com/inward/record.url?scp=46849113869&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=46849113869&partnerID=8YFLogxK
U2 - 10.1109/UPEC.2006.367750
DO - 10.1109/UPEC.2006.367750
M3 - Conference contribution
AN - SCOPUS:46849113869
SN - 9781861353429
VL - 1
SP - 232
EP - 236
BT - 41st International Universities Power Engineering Conference, UPEC 2006, Conference Procedings
ER -