返回列表 发布新帖

[电工技术] 基于随机森林和长短期记忆网络多元负荷预测的综合能源三层规划调度

8 0
admin 发表于 2025-1-27 16:00 | 查看全部 阅读模式

基于随机森林和长短期记忆网络多元负荷预测的综合能源三层规划调度
摘要:针对综合能源系统负荷不确定性对规划和调度造成的高成本低效率问题,提出一种基于多元负荷预测的3层规划调度模型,主要包括预测层、规划层和调度层;基于随机森林回归网络和长短期记忆网络构建了多元负荷的长期和短期预测模型;以综合规划调度成本和调度运行成本最小为目标,采用改进粒子群算法和CPLEX求解器获取最优系统综合成本及配置方案;通过不同场景下的规划调度,分析了设备状态与系统成本。通过对比所构建的3层模型与常规双层模型的规划调度结果,证明了3层规划调度模型的经济性与可靠性。

Abstract:In allusion to the problem of high cost and low efficiency in power planning and dispatching due to load uncertainty in integrated energy system, a multivariate load forecasting-based three layer planning and dispatching model, in which the forecasting layer, the planning layer and the scheduling layer were included, was proposed. Based on random forest regression network and long- and short-term memory network a long-term and short-term multiple load prediction model was constructed. Taking the minimum integrated planning and dispatching cost and the minimum dispatching and operation cost as objectives, adopting improved particle swarm optimization algorithm and CPLEX solver, the optimal system comprehensive cost and allocation scheme was obtained. By means of planning and dispatching under different scenarios the equipment status and system cost were analyzed. Comparing the planning and dispatching results obtained by the constructed three layer model with that obtained by conventional two layer model, it is proved that the three layer planning and dispatching model possesses better economy and reliability.

标题:基于随机森林和长短期记忆网络多元负荷预测的综合能源三层规划调度
英文标题:Three-level Planning and Scheduling of Comprehensive Energy Based on Random Forest R egression-Long- and Short-Term Memory Network Multivariate Load Forecasting

作者:李玉凯, 韩佳兵, 于春浩, 王全, 杨蒙, 赵钧,

关键词:综合能源系统, 多元负荷预测, 规划调度, 随机森林回归, 长短期记忆神经网络,

发表日期:2021-12-10
2025-1-26 20:55 上传
文件大小:
2.34 MB
下载次数:
60
高速下载
【温馨提示】 您好!以下是下载说明,请您仔细阅读:
1、推荐使用360安全浏览器访问本站,选择您所需的PDF文档,点击页面下方“本地下载”按钮。
2、耐心等待两秒钟,系统将自动开始下载,本站文件均为高速下载。
3、下载完成后,请查看您浏览器的下载文件夹,找到对应的PDF文件。
4、使用PDF阅读器打开文档,开始阅读学习。
5、使用过程中遇到问题,请联系QQ客服。

本站提供的所有PDF文档、软件、资料等均为网友上传或网络收集,仅供学习和研究使用,不得用于任何商业用途。
本站尊重知识产权,若本站内容侵犯了您的权益,请及时通知我们,我们将尽快予以删除。
  • 手机访问
    微信扫一扫
  • 联系QQ客服
    QQ扫一扫
2022-2025 新资汇 - 参考资料免费下载网站 最近更新浙ICP备2024084428号
关灯 返回顶部
快速回复 返回顶部 返回列表