基于时间序列的电能路由器能流预测模型

来源 :水电能源科学 | 被引量 : 0次 | 上传用户:kakayang
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为解决以电能路由器为基本节点的能源互联网中的能流预测问题,分析了居民用电、大型商业用电、小型商业用电、光伏出力四类能流的主要影响因素,利用时间序列中的ARIMA模型构建了不同性质的能流预测模型,在此基础上综合考虑不同性质的能流和能源局域网的路由策略,进而构建了电能路由器能流预测模型。将该模型应用于New Hampshire Electric Co-op(NHEC)2013年3月的能流预测时,发现在路由策略下分布式电源充分条件下储能设备充裕时,对电能路由器能流EEF无影响;储能设备有限时,对EEF影响较大,EEF频繁波动;无储能设备时,对EEF影响较大,10:00~19:00时波动大;在分布式电源有限条件下,三种储能设备情况下,对电能路由器能流EEF均影响较大。 In order to solve the problem of energy flow prediction in energy internet based on energy router, the main influencing factors of household energy consumption, large commercial power supply, small commercial power supply and photovoltaic power output are analyzed. By using time series The ARIMA model constructs the energy flow forecasting model with different properties. Based on this, the energy flows of different nature and the routing strategy of the energy LAN are comprehensively considered, and then the energy flow forecasting model of the power router is constructed. When this model was applied to the energy flow forecast of New Hampshire Electric Co-op (NHEC) in March 2013, it was found that there was no impact on the EEF energy flow when the energy storage equipment was sufficient under the distributed power supply under the routing strategy. When the energy storage equipment is limited, the EEF has a great influence on the EEF, and the EEF fluctuates frequently. When there is no energy storage device, it has a great influence on the EEF and fluctuates greatly from 10:00 to 19:00. Under the limited distributed power conditions, In the case of equipment, EEF, both of which can influence the energy router, has a greater impact.
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