实时匹配本地发电和需求:采用高分辨率负荷建模

M. Degefa, M. Lehtonen, M. Mcculloch, Ken Nixon
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引用次数: 4

摘要

在大多数研究中,用于解决匹配当地发电和需求问题的最低时间分辨率数据是每小时。很少有人尝试使用微小的时间分辨率来捕捉高度随机的性质。本研究利用名为Suricatta的高分辨率家庭负荷建模平台来评估实时匹配的潜力。在本研究中,使用1分钟和1小时分辨率数据来评估光伏和风力涡轮机的负载匹配指数以及蓄电池和需求响应解决方案。结果表明,在需求响应规划和风力涡轮机世代的情况下,1分钟数据分辨率具有相对较高的相关性。此外,天气变量的昼夜性质及其与典型芬兰家庭季节性消费的负相关性强调了对存储系统和/或需求响应计划的需求,以增强配电系统级风力发电机组和光伏发电机组的匹配。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-time matching of local generation and demand: The use of high resolution load modeling
In most studies, the lowest temporal resolution data used in addressing the problem of matching local generation and demand is hourly. There are very few attempts that use minute level temporal resolution capturing the highly stochastic nature. This study utilizes high-resolution household load modelling platform called Suricatta to assess the potential for matching in real-time. In this study, 1-minute and 1-hour resolutions data is used to evaluate load matching index of PVs and wind turbines along with storage battery and demand response solutions. The results demonstrate the relatively high relevance of 1-minute data resolution in case of demand response planning and also for wind turbine generations. Besides, the diurnal nature of weather variables together with their negative correlation to the typical Finnish household seasonal consumption emphasizes the need for storage systems and/or demand response plans to enhance matching of distribution system level wind turbine and PV generations.
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