摘要
需求侧负荷特性的准确把握是构建园区能源互联网的前提与基础。文章从多元负荷的共性和耦合指标、负荷聚类与相关性分析等方面,探讨了基于数据驱动的用户负荷画像及其类型化方法;评述了单元用户冷、热、电负荷预测方法及园区整体负荷预测方法的研究现状,从同类负荷的时序调控及异类负荷的互补调控两个层面探讨了园区多元负荷的调控潜力;展望了本领域的未来研究方向。
The accurate grasp of demand-side load characteristics is the premise and foundation for the development of park-level energy internets.The data-driven load mapping and its classification methods are discussed from the aspects of the common and coupling indexes,as well as the clustering and correlation analysis of multiple loads.Following which,the load prediction methods for both single users and the overall park are reviewed.Moreover,the regulation potentials of multi-load within the park are analyzed from both the temporal regulation of same-type loads and the complementary regulation of different-type loads.Finally,the future research directions for load research are discussed.
作者
任洪波
陈杰
李琦芬
吴琼
杨涌文
赵鹏翔
Ren Hongbo;Chen Jie;Li Qifeng;Wu Qiong;Yang Yongwen;Zhao Pengxiang(Shanghai University of Electric Power,Shanghai 200090,China;State Grid Integrated Energy Service Group Co.Ltd.,Beijing 100052,China)
出处
《可再生能源》
CAS
CSCD
北大核心
2021年第2期245-251,共7页
Renewable Energy Resources
基金
国家自然科学基金项目(71804106)
上海市科委重点研究项目(19DZ1206800,19DZ1205700)。
关键词
能源互联网
负荷预测
负荷特性
调控潜力
行为动力学
energy internet
load characteristic
load forecasting
regulation potential
behavioral dynamics
