基于量子和声搜索算法的可再生能源渗透率组合预测模型研究  

Combined Prediction Model of Renewable Energy Penetration Rate Based on Quantum Harmony Search

作　　者：武雪婷 孙伟[1] 李沛妍 刘佳岩 李兵抗 张浩楠 WU Xueting;SUN Wei;LI Peiyan;LIU Jiayan;LI Bingkang;ZHANG Haonan(Department of Economic Management,North China Electric Power University,Baoding 071003,China;State Grid Xinyuan Materials Co.,Ltd.,Beijing 100053,China)

机构地区：[1]华北电力大学经济管理系,河北保定071003 [2]国网新源物资有限公司,北京100053

出　　处：《智慧电力》2024年第9期49-55,共7页Smart Power

基　　金：国家自然科学基金青年基金资助项目(72303064)。

摘　　要：“双碳”目标极大地促进了我国可再生能源的发展。针对可再生能源渗透率的准确预测问题,提出基于量子和声搜索(QHS)算法的可再生能源渗透率组合预测模型。首先,采用多层感知器筛选出与可再生能源渗透率强相关的因素;其次,选择4种不同的单项预测模型,采用改进折现均方预测误差加权(MDMFSE)组合模型对单项预测模型结果进行集成;最后,利用QHS算法对MDMFSE的加权系数进行动态优化,构建QHS-MDMFSE组合预测模型,实现对可再生能源渗透率的预测。算例分析表明,所提模型相较其他传统模型具有更高的预测精度,且稳定性更高。The target of carbon peak and carbon neutrality has promoted the development of renewable energy in our country.To accurately forecast the renewable energy penetration rate,a combined forecasting model based on quantum harmony search(QHS)is proposed.Firstly,the factors that are strongly related to the penetration rate of renewable energy are screened out using multilayer perceptron.Additionally,four different single-item prediction models are selected,and the results of the single-item prediction model are integrated by using the modified discounted mean square forecast error(MDMFSE)combined model.Finally,the QHS algorithm is used to optimize the weighting coefficients of the MDMFSE combined model dynamically.The QHS-MDMFSE combined prediction model is constructed to predict the penetration rate of renewable energy.The results of the case study indicate that the proposed model has higher prediction accuracy.

关 键 词：可再生能源渗透率 量子和声搜索 MDMSFE组合预测模型 动态赋权 多层感知器 

分 类 号：TM715[电气工程—电力系统及自动化]