共 35 条
Adaptive Consensus-Based Robust Strategy for Economic Dispatch of Smart Grids Subject to Communication Uncertainties
被引:169
作者:
Wen, Guanghui
[1
,2
]
Yu, Xinghuo
[2
]
Liu, Zhi-Wei
[3
]
Yu, Wenwu
[1
]
机构:
[1] Southeast Univ, Sch Math, Nanjing 210096, Jiangsu, Peoples R China
[2] RMIT Univ, Sch Engn, Melbourne, Vic 3001, Australia
[3] Huazhong Univ Sci & Technol, Coll Automat, Wuhan 430074, Hubei, Peoples R China
基金:
澳大利亚研究理事会;
关键词:
Adaptive algorithm;
distributed control;
economic dispatch;
leader-following consensus;
smart grid;
MULTIAGENT SYSTEMS;
DEMAND RESPONSE;
ALGORITHM;
D O I:
10.1109/TII.2017.2772088
中图分类号:
TP [自动化技术、计算机技术];
学科分类号:
0812 ;
摘要:
The economic dispatch problem is investigated in this paper for a class of smart grids subject to unknown communication uncertainties. Compared with existing works related to economic dispatch where the dispatch algorithms are carried out by a centralized controller, a new kind of distributed dispatch algorithms are developed to achieve optimal dispatch of electric power by appropriately sharing the load among different generating units while guaranteeing consensus among incremental costs. An adaptive weight-adjustment technique is suggested that enables the dispatch algorithms to choose the communication weights among neighboring generating units which yield consensus of incremental costs under both cases with or without capacity limitations. The achievement of such a consensus leads to optimal dispatch of electronic power and secures the system performance against unknown communication uncertainties. Meanwhile, it is proved that the power demand and supply of the considered smart grids will be kept in a balanced state during the dispatch process. The interesting issue of how to assign the power outputs among generating units to balance the power demand and supply of the considered smart grids is also addressed. Finally, the numerical results of several case studies have been provided to verify the effectiveness of the proposed algorithms.
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页码:2484 / 2496
页数:13
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