摘要
农村地区照明用电行为受地理环境、经济水平及用户习惯等多重因素影响,呈现显著的时空异质性与能效管理粗放特征。传统电力调控手段因缺乏对用户行为规律的深度解析,难以实现精细化需求响应与新能源消纳协同优化,导致能源浪费与用能成本居高不下。人工智能技术的发展为海量用电数据挖掘、动态行为建模及智能决策提供了新路径。因此,文章就农村照明用电行为的内在机理与智能化调控策略展开系统性探讨,以期望构建数据驱动的能效优化框架,为农村低碳化用能转型与可持续发展提供理论支撑与实践参考。
Lighting electricity use in rural areas is influenced by multiple factors such as geographical environment,economic level,and user habits,exhibiting significant spatiotemporal heterogeneity and coarse energy efficiency management.Traditional power regulation methods,lacking in-depth analysis of user behavior patterns,struggle to achieve precise demand response and coordinated optimization of new energy consumption,leading to high energy waste and persistently high energy costs.The development of artificial intelligence technology offers new approaches for mining massive amounts of electricity usage data,modeling dynamic behaviors,and making intelligent decisions.Therefore,this paper systematically explores the intrinsic mechanisms of rural lighting electricity use and intelligent control strategies,aiming to construct a data-driven energy efficiency optimization framework to provide theoretical support and practical references for the low-carbon transformation and sustainable development of rural energy use.
作者
谢峰
王欣
XIE Feng;WANG Xin(State Grid Chaohu Power Supply Company,Chaohu 238000,China)
出处
《中国照明电器》
2025年第8期107-109,共3页
China Light & Lighting
关键词
农村照明
用电行为分析
人工智能
动态优化
rural lighting
electricity consumption behavior analysis
artificial intelligence
dynamic optimization
