首页|基于BiGRU自注意力机制和LQPSO的多能源微电网预测与调度

基于BiGRU自注意力机制和LQPSO的多能源微电网预测与调度

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  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
为了更准确地预测微电网太阳能发电功率，针对光伏出力的特性，在双向门控循环单元(BiGRU)的基础上引入自注意力机制，更充分的发掘光伏出力的时序特性，并考虑不同时间节点对预测结果的影响。随后，提出了一种改进的量子粒子群优化(QPSO)算法对组合预测模型的超参数进行优化。最终提出的LQPSO-BiGRU-self-attention混合模型能够更有效地预测太阳能发电功率。此外，考虑电、氢、可再生能源等多种能源的协调利用，构建了考虑经济和环境成本的多目标优化模型。针对多能源微网系统的综合优化调度问题，提出了结合莱维飞行的两阶段自适应多目标量子粒子群优化(MO-LQPSO)算法。该算法有效地平衡了全局和局部搜索能力，增强了对复杂非线性问题的求解能力。通过对比仿真验证了所提方案的有效性和优越性。
Prediction and scheduling of multi-energy microgrid based on BiGRU self-attention mechanism and LQPSO
To predict renewable energy sources such as solar power in microgrids more accurately,a hybrid power prediction method is presented in this paper.First,the self-attention mechanism is introduced based on a bidirectional gated recurrent neural network(BiGRU)to explore the time-series characteristics of solar power output and consider the influence of different time nodes on the prediction results.Subsequently,an improved quantum particle swarm optimization(QPSO)algorithm is proposed to optimize the hyperparameters of the combined prediction model.The final proposed LQPSO-BiGRU-self-attention hybrid model can predict solar power more effectively.In addition,considering the coordinated utilization of various energy sources such as electricity,hydrogen,and renewable energy,a multi-objective optimization model that considers both economic and environmental costs was constructed.A two-stage adaptive multi-objective quantum particle swarm optimization algorithm aided by a Lévy flight,named MO-LQPSO,was proposed for the comprehensive optimal scheduling of a multi-energy microgrid system.This algorithm effectively balances the global and local search capabilities and enhances the solution of complex nonlinear problems.The effectiveness and superiority of the proposed scheme are verified through comparative simulations.

MicrogridBidirectional gated recurrent unitSelf-attentionLévy-quantum particle swarm optimizationMulti-objective optimization

段宇宸、李鹏、夏静

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School of Automation and Intelligence,Beijing Jiaotong University,Beijing 100044,P.R.China

Goldwind Science&Technology Co.Ltd.,Beijing 100176,P.R.China

微电网 双向门控循环单元 自注意力 莱维量子粒子群优化 多目标优化

National Natural Science Foundation of ChinaBeijing Natural Science Foundation

519770044212042

2024

10.1016/j.gloei.2024.06.007

全球能源互联网(英文)

全球能源互联网(英文)

CSTPCDEI
ISSN：2096-5117
年,卷(期)：2024.7(3)