Load regulation application of university campus based on solar power generation forecasting

• Autorzy: Han Guozheng , Tan Shujuan , Zhang Zihan

Identyfikatory

DOI

10.24425/aee.2023.145418

• Języki publikacji: EN

Abstrakty

EN

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 68 610 yuan (in 2019).

Słowa kluczowe

EN

load regulation; solar power generation forecast; photovoltaic generation

• Wydawca: Polish Academy of Sciences, Committee on Electrical Engineering
• Czasopismo: Archives of Electrical Engineering
• Rocznik: 2023
• Tom: Vol. 72, nr 2
• Strony: 429--441
• Opis fizyczny: Bibliogr. 23 poz., rys., tab., wz.

Twórcy

autor

Han Guozheng

• School of Information and Automation Engineering Qilu University of Technology (Shandong Academy of Sciences) No. 3501, Daxue Road, Changqing District, Jinan 250353 Shandong Province, PR China

• https://orcid.org/0000-0002-2645-0160

autor

Tan Shujuan

• School of Information and Automation Engineering Qilu University of Technology (Shandong Academy of Sciences) No. 3501, Daxue Road, Changqing District, Jinan 250353 Shandong Province, PR China

• https://orcid.org/0000-0002-4799-6066

autor

Zhang Zihan

• School of Information and Automation Engineering Qilu University of Technology (Shandong Academy of Sciences) No. 3501, Daxue Road, Changqing District, Jinan 250353 Shandong Province, PR China

• https://orcid.org/0000-0001-5199-8059

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).