电力系统保护与控制2026，Vol.54Issue(6)：104-113,10.DOI:10.19783/j.cnki.pspc.250768
基于DGJO-TCN-BiGRU的微电网集群优化调度
Optimal scheduling of microgrid clusters based on DGJO-TCN-BiGRU
摘要
Abstract
To address the issues of high generation costs and insufficient economic benefits of microgrid clusters under complex constraints,an optimal scheduling model for microgrid clusters based on the dual-population golden jackal optimization(DGJO)algorithm is proposed.First,with the objective of minimizing the total cost,an optimal scheduling model for microgrid clusters is constructed,incorporating operation costs,energy storage costs,electricity trading costs,and environmental costs.Second,the DGJO algorithm is developed,in which Lévy flight is employed to achieve adaptive convergence,a dual-population strategy is adopted to balance exploration and exploitation,and Harris hawks encircling and cache-foraging operators are incorporated to improve optimization accuracy.Then,DGJO is applied to optimize the hyperparameters of the temporal convolutional network(TCN)and the bidirectional gated recurrent unit(BiGRU),thereby improving convergence speed and model generalization capability.Finally,case studies demonstrate that the proposed model exhibits strong robustness under complex constraints and disturbance scenarios and effectively reduces the overall system cost.关键词
微电网集群/时间卷积网络/双向门控递归单元/优化调度/金豺优化算法Key words
microgrid clusters/temporal convolutional network/bidirectional gated recurrent unit/optimal scheduling/golden jackal optimization algorithm引用本文复制引用
王延峰,赵家学,曹育晗,孙军伟..基于DGJO-TCN-BiGRU的微电网集群优化调度[J].电力系统保护与控制,2026,54(6):104-113,10.基金项目
This work is supported by the National Natural Science Foundation of China(No.62272424 and No.62276239). 国家自然科学基金项目资助(62272424,62276239) （No.62272424 and No.62276239）
