电动汽车聚合下的微能源互联网优化调度策略
随着可再生能源规模化接入电网,需配备更多的储能设备以减少峰谷差,这使得投入成本大大提高.电动汽车聚合的负荷特性类似储能,其主动参与能源互联网能量优化调度,将减少储能设备的成本,进而提高微能源互联网的经济效益.提出了电动汽车聚合下的微能源互联网优化调度策略.首先,基于AP(affinity propagation)数据挖掘技术的电动汽车负荷聚类分析,提出了基于极限学习机预测模型的电动汽车短期预测方法.其次,提出电动汽车聚合下的微能源互联网优化调度策略,利用电价激励电动汽车有序充电以减小负荷峰谷差进而降低系统发电成本.最后,仿真验证该优化调度策略的有效性....
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| Published in | 中国电力 Vol. 56; no. 5; pp. 80 - 88 |
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| Main Authors | , , , , , , |
| Format | Magazine Article |
| Language | Chinese |
| Published |
国网河北省电力有限公司经济技术研究院,河北石家庄 050011%南京邮电大学自动化学院人工智能学院,江苏南京 210023
2023
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1004-9649 |
| DOI | 10.11930/j.issn.1004-9649.202211034 |
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| Abstract | 随着可再生能源规模化接入电网,需配备更多的储能设备以减少峰谷差,这使得投入成本大大提高.电动汽车聚合的负荷特性类似储能,其主动参与能源互联网能量优化调度,将减少储能设备的成本,进而提高微能源互联网的经济效益.提出了电动汽车聚合下的微能源互联网优化调度策略.首先,基于AP(affinity propagation)数据挖掘技术的电动汽车负荷聚类分析,提出了基于极限学习机预测模型的电动汽车短期预测方法.其次,提出电动汽车聚合下的微能源互联网优化调度策略,利用电价激励电动汽车有序充电以减小负荷峰谷差进而降低系统发电成本.最后,仿真验证该优化调度策略的有效性. |
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| AbstractList | 随着可再生能源规模化接入电网,需配备更多的储能设备以减少峰谷差,这使得投入成本大大提高.电动汽车聚合的负荷特性类似储能,其主动参与能源互联网能量优化调度,将减少储能设备的成本,进而提高微能源互联网的经济效益.提出了电动汽车聚合下的微能源互联网优化调度策略.首先,基于AP(affinity propagation)数据挖掘技术的电动汽车负荷聚类分析,提出了基于极限学习机预测模型的电动汽车短期预测方法.其次,提出电动汽车聚合下的微能源互联网优化调度策略,利用电价激励电动汽车有序充电以减小负荷峰谷差进而降低系统发电成本.最后,仿真验证该优化调度策略的有效性. |
| Author | 贺春光 杨书强 袁超 窦春霞 安佳坤 张菁 王涛 |
| AuthorAffiliation | 国网河北省电力有限公司经济技术研究院,河北石家庄 050011%南京邮电大学自动化学院人工智能学院,江苏南京 210023 |
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| Author_FL | HE Chunguang WANG Tao DOU Chunxia AN Jiakun YUAN Chao YANG Shuqiang ZHANG Jing |
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| Keywords | AP数据挖掘技术 电动汽车聚合 微能源互联网 能量优化调度 极限学习机预测模型 |
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| Publisher | 国网河北省电力有限公司经济技术研究院,河北石家庄 050011%南京邮电大学自动化学院人工智能学院,江苏南京 210023 |
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| Snippet | 随着可再生能源规模化接入电网,需配备更多的储能设备以减少峰谷差,这使得投入成本大大提高.电动汽车聚合的负荷特性类似储能,其主动参与能源互联网能量优化调度,将减少储能... |
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| Title | 电动汽车聚合下的微能源互联网优化调度策略 |
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