TY - GEN
T1 - Cooperative extremum seeking for power availability detection of photovoltaic cluster
AU - Li, Chaoyong
AU - Wang, Lizhi
AU - Zhang, Guoyue
AU - Wang, Jianan
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/6/28
Y1 - 2017/6/28
N2 - The power availability detection for geographically dispersed multiple Photovoltaic (PV) generators plays an important role in the management and control of PV-based smart grid systems. This paper proposed a distributed estimation scheme to enable local awareness of global PV capacity awareness at each PV station, using a cooperative extremum seeking conjecture. In particular, the proposed algorithm treated each PV as a node in networked systems, and takes full advantage of the discrete information flow among networked node, as well as model free behavior of extremum seeking method. More specifically, a dynamic average tracking algorithm is introduced to guarantee each PV not only be able to track its own individual maximum power point (MPP), but also the total MPP (i.e. power availability) of the PV cluster simultaneously and locally without any centralized facility. Simulation results validate the effectiveness of the proposed method.
AB - The power availability detection for geographically dispersed multiple Photovoltaic (PV) generators plays an important role in the management and control of PV-based smart grid systems. This paper proposed a distributed estimation scheme to enable local awareness of global PV capacity awareness at each PV station, using a cooperative extremum seeking conjecture. In particular, the proposed algorithm treated each PV as a node in networked systems, and takes full advantage of the discrete information flow among networked node, as well as model free behavior of extremum seeking method. More specifically, a dynamic average tracking algorithm is introduced to guarantee each PV not only be able to track its own individual maximum power point (MPP), but also the total MPP (i.e. power availability) of the PV cluster simultaneously and locally without any centralized facility. Simulation results validate the effectiveness of the proposed method.
UR - http://www.scopus.com/inward/record.url?scp=85046161344&partnerID=8YFLogxK
U2 - 10.1109/CDC.2017.8264135
DO - 10.1109/CDC.2017.8264135
M3 - Conference contribution
AN - SCOPUS:85046161344
T3 - 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
SP - 3246
EP - 3251
BT - 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 56th IEEE Annual Conference on Decision and Control, CDC 2017
Y2 - 12 December 2017 through 15 December 2017
ER -
