基于太阳能发电预测的大学校园负荷调节应用

IF 1.2 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC Archives of Electrical Engineering Pub Date : 2023-06-28 DOI:10.24425/aee.2023.145418
Guozheng HANo, Shujuan TANo, Zihan ZHANGo, Guozheng Han
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引用次数: 0

摘要

:高校校园太阳能光伏发电系统,系统产生的电能满足校园负荷,多余的电能送入电网。一般来说,光伏发电系统的价格要比公用电力系统便宜。充分利用太阳能发电可以降低学校的用电成本。利用深度信念网络对太阳能光伏发电和电力负荷进行预测,并找到缺口。根据差距,调整校园的电力负荷,提高太阳能发电的利用率。通过对中国齐鲁理工大学长庆校区的实际应用发现,太阳能光伏发电利用率从2017年的91.24%有效提升至2019年的98.16%,年节电68610元(2019年)。
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Load regulation application of university campus based on solar power generation forecasting
: For a solar photovoltaic power system on a university campus, the electricity generated by the system meets the campus load, and the extra electricity is delivered to the grid. Generally, the price of the photovoltaic system is cheaper than that of the utility power system. The full use of solar electricity can reduce the electricity cost of the school. The deep belief network is used to predict solar photovoltaic generation and electricity load, and the gap is found. According to the gap, the power loads on the campus are adjusted to improve the utilization rate of solar power generation. Through the practical application of Changqing Campus of Qilu University of Technology in China, it is found that the utilization rate of solar photovoltaic power generation effectively improved from 91.24% in 2017 to 98.16% in 2019, and the annual electricity is saved by 68610 yuan (in 2019).
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来源期刊
Archives of Electrical Engineering
Archives of Electrical Engineering ENGINEERING, ELECTRICAL & ELECTRONIC-
CiteScore
2.40
自引率
53.80%
发文量
0
审稿时长
18 weeks
期刊介绍: The journal publishes original papers in the field of electrical engineering which covers, but not limited to, the following scope: - Control - Electrical machines and transformers - Electrical & magnetic fields problems - Electric traction - Electro heat - Fuel cells, micro machines, hybrid vehicles - Nondestructive testing & Nondestructive evaluation - Electrical power engineering - Power electronics
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