Smart generation system: A decentralized multi-agent control architecture based on improved consensus algorithm for generation command dispatch of sustainable energy systems

被引:4
作者
Quan, Yue [1 ]
Xi, Lei [1 ,2 ]
机构
[1] China Three Gorges Univ, Coll Elect Engn & New Energy, Yichang 443002, Peoples R China
[2] China Three Gorges Univ, Hubei Prov Key Lab Operat & Control Cascaded Hydro, Yichang 443002, Peoples R China
基金
中国国家自然科学基金;
关键词
Automatic generation control (AGC); Consensus; Decentralization; Economic dispatch; Multi-agent; Multiple objectives programming; Smart generation system; FREQUENCY CONTROL; ECONOMIC-DISPATCH; AGC DISPATCH; POWER;
D O I
10.1016/j.apenergy.2024.123209
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The sustainable energies take increasing proportion in the power systems due to the "net-zero emission"goal, and the future trend is to make the new type power systems operate safely and stably while maintaining low carbon and economic efficiency. This paper proposes a novel smart generation system (SGS) architecture and a smart generation system consensus (SGSC) algorithm from the perspective of automatic generation control. The SGS is based on stratified sequencing method and multi-agent theory, which describes the dynamic and optimal generation dispatch of the units as a hierarchical decentralized multiple objectives programming problem. Further, the SGSC is proposed based on distributed Newton algorithm and leaderless consensus algorithm to solve the security performance degradation caused by decentralization. All the units are configured in parallel with the designed communication topology to achieve dispatch decentralization, thus ensuring lowcarbon, economical and safe operation of the new type power system. The effectiveness of the proposed algorithm is verified on a multi-layer, multi-zone smart generation system model with a high proportion of sustainable energies from macro and micro aspects. Different control methods are also used for performance comparison on the two-area load frequency control model with lower regulation costs and lower carbon emissions achievement.
引用
收藏
页数:12
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