PDF (2225K)
摘要
随着全球能源需求的持续增长以及对环境保护的日益重视,水电作为清洁能源在能源结构中的地位愈发重要。然而,传统的水电系统调控管理方式在效率、精准度以及应对复杂情况等方面存在诸多不足,难以满足现代能源系统的发展需求。在此背景下,基于人工智能技术对水电系统智能调控管理展开系统研究。通过引入智能数据采集、数据分析与预测以及智能决策等关键技术,构建基于人工智能的水电系统智能调控管理解决方案。该方案能够提升水电系统调控管理的效率与精准度,有效应对复杂运行环境,为水电行业的智能化发展提供有力支撑。
Abstract
With the continuous growth of global energy demand and the increasing emphasis on environmental protection, hydropower as a clean energy source is becoming increasingly important in the energy structure. However, traditional hydropower system regulation and management method have many shortcomings in terms of efficiency, accuracy, and the ability to deal with complex situations, which makes it difficult to meet the development needs of modern energy systems. Against this backdrop, this paper systematically studies intelligent regulation and management of hydropower systems based on artificial intelligence technology. By introducing key technologies such as intelligent data collection, data analysis and prediction, and intelligent decision-making, an artificial intelligence-based intelligent regulation and management solution for hydropower systems is constructed. This solution can improve the efficiency and accuracy of hydropower system regulation and management, effectively deal with complex operating environments, and provide strong support for the intelligent development of the hydropower industry.
关键词
人工智能
/
水电系统
/
智能调控
/
机器学习
/
故障诊断
Key words
artificial intelligence
/
hydropower system
/
intelligent regulation
/
machine learning
/
fault diagnosis
Author summay
张志红(1980—), 男, 工程师, 项目经理, 学士, 主要从事人工智能的水电系统智能调控管理研究。E-mail: 58313683@qq.com
[Author(id=1248649900636906359, tenantId=1045748351789510663, journalId=1221126710357164034, articleId=1248596710595895537, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=58313683@qq.com, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1248649900691432317, tenantId=1045748351789510663, journalId=1221126710357164034, articleId=1248596710595895537, authorId=1248649900636906359, language=EN, stringName=Zhihong ZHANG, firstName=Zhihong, middleName=null, lastName=ZHANG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=Xiamen Branch of China Anneng Group Second Engineering Bureau Co., Ltd., Xiamen 361021, Fujian, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1248649900733375362, tenantId=1045748351789510663, journalId=1221126710357164034, articleId=1248596710595895537, authorId=1248649900636906359, language=CN, stringName=张志红, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=中国安能集团第二工程局有限公司厦门分公司, 福建 厦门 361021, bio={"content":"张志红(1980—), 男, 工程师, 项目经理, 学士, 主要从事人工智能的水电系统智能调控管理研究。E-mail: 58313683@qq.com
"}, bioImg=null, bioContent=张志红(1980—), 男, 工程师, 项目经理, 学士, 主要从事人工智能的水电系统智能调控管理研究。E-mail: 58313683@qq.com
, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1248649900561408881, tenantId=1045748351789510663, journalId=1221126710357164034, articleId=1248596710595895537, xref=null, ext=[AuthorCompanyExt(id=1248649900578186098, tenantId=1045748351789510663, journalId=1221126710357164034, articleId=1248596710595895537, companyId=1248649900561408881, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Xiamen Branch of China Anneng Group Second Engineering Bureau Co., Ltd., Xiamen 361021, Fujian, China), AuthorCompanyExt(id=1248649900590769011, tenantId=1045748351789510663, journalId=1221126710357164034, articleId=1248596710595895537, companyId=1248649900561408881, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=中国安能集团第二工程局有限公司厦门分公司, 福建 厦门 361021)])])]
张志红.
基于人工智能的水电系统智能调控管理研究[J].
水利水电技术(中英文), 2025, 56(S2): 833-837 DOI:10.13928/j.cnki.wrahe.2025.S2.124