基于源-荷不确定性的上海典型园区用能预测  

Energy usage forecasting in a typical Shanghai park based on source-load uncertainty

作　　者：李峥嵘[1] 蒋雅婷 LI Zhengrong;JIANG Yating(School of Mechanical and Energy Engineering,Tongji University,Shanghai 201804,China)

机构地区：[1]同济大学机械与能源工程学院,上海201804

出　　处：《西安工程大学学报》2025年第1期62-71,共10页Journal of Xi’an Polytechnic University

基　　金：国家重点研发计划(2023YFE0121000)。

摘　　要：为探究园区设计规划阶段建筑群用能及可再生能源供能的不确定性,采用自下而上的方法,利用EnergyPlus和PVsyst建立了上海典型园区建筑群的用能及光伏发电物理模型,生成了不同季节(供冷季、供暖季、过渡季)、天气类型(晴天、多云、阴天)及用能特征(工作日、非工作日)下的确定性情景集。基于场景分析法,通过拉丁超立方抽样和k-means聚类方法,生成并缩减了不确定性场景集,得到了典型用能曲线及其贡献率,并对园区不同情景的用能特征进行分析。结果表明,过渡季建筑群用能不确定性最大,供冷季、供暖季次之,不确定性上下区间变化率最大可达9.34%和9.76%。光伏发电的不确定性在晴天和多云天气下更为显著,尤其是在供冷季和供暖季,不确定性上下区间变化率最大可达13.25%和16.78%。源-荷双重不确定性下,光伏消纳率最多可降低10.24%,光伏弃光率最多可增加10.23%。并进一步指出储能技术在高不确定性情景下的重要性,特别是在供冷季高峰负荷和非工作日低负荷时段,储能系统的应用能够显著提升能源利用效率。To investigate the uncertainties in building energy consumption and renewable energy supply at the design and planning stages of an industrial park,this study adopts a bottom-up approach.Using EnergyPlus and PVsyst,physical models of energy consumption and photovoltaic(PV)power generation were established for a typical industrial park in Shanghai.Deterministic scenario sets were generated for different seasons(e.g.cooling,heating,transition),weather types(e.g.sunny,cloudy and overcast),and energy consumption characteristics(working days and non-working days).Based on the scenario analysis,Latin Hypercube Sampling and k-means clustering methods were used to generate and reduce uncertainty scenarios.Typical energy consumption curves and their contributions were obtained,and the energy consumption characteristics of the park under different scenarios were analyzed.The results show that energy consumption uncertainty in the transition season is the highest,followed by the cooling and heating seasons,with the maximum range of uncertainty variation reaching 9.34%and 9.76%.PV power generation uncertainty is more pronounced on sunny and cloudy days,especially in the cooling and heating seasons,with the maximum range of uncertainty variation reaching 13.25%and 16.78%.Under dual uncertainties of source and load,PV utilization rate can decrease by up to 10.24%,while PV curtailment rate can increase by up to 10.23%.These findings highlight the importance of energy storage technologies in scenarios with high uncertainty,particularly during peak load periods in the cooling season and low load periods on non-working days.The application of energy storage systems can significantly improve energy utilization efficiency.

关 键 词：用能 可再生能源供能 场景分析法 负荷预测 不确定性分析 拉丁超立方抽样 

分 类 号：TK01[动力工程及工程热物理]