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Understanding the reliability of localized near future weather data for building performance prediction in the UK

机译:了解本地近期天气数据的可靠性,以进行英国建筑性能预测

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Access to reliable site-specific near future weather data is crucial for forecasting temporally-dynamic building energy demand and consumption, and determining the state of on-site renewable energy generation. Often there is a missing link between weather forecast providers and building energy management systems. This short paper discusses the potential to conduct building performance modelling using localized high resolution weather forecast freely available from the United Kingdom Met Office DataPoint service. It creates a great opportunity for building performance simulation professionals and building energy managers to re-use site-specific high resolution weather forecast data to predict near future building performance at both individual building and city scale. In this paper, authors have developed a framework of forecasting near future building performance and a Matlab script to automatically gather observed weather data from 140 weather stations and weather forecasts for nearly 6,000 locations in the UK. To understand the reliability of weather forecast, three-hourly forecasts of temperature, relative humidity, wind speed and wind direction are compared with observations from weather stations. This provides evidences to use the next 24-hour forecast to predict dynamic building energy demand and consumption, and determine the on-site renewable energy generation output. Because of the high accuracy of forecast, the rolling forecast can be recorded on daily basis to construct weather files for locations that do not have weather stations. This will increase current 14 locations of the CIBSE weather data to nearly 6,000 locations covering population centers, sporting venues and tourist attractions.
机译:获得可靠的特定地点的近期未来天气数据对于预测随时间变化的建筑能源需求和消耗,以及确定现场可再生能源的产生状态至关重要。通常,天气预报提供者与建筑能源管理系统之间缺少联系。本简短文章讨论了使用英国气象局DataPoint服务免费提供的本地化高分辨率天气预报进行建筑性能建模的潜力。它为建筑性能模拟专业人员和建筑能源管理人员提供了一个绝佳的机会,可以重用特定于站点的高分辨率天气预报数据,以预测各个建筑物和城市规模的近期建筑物性能。在本文中,作者开发了一个预测近期建筑物性能的框架和一个Matlab脚本,以自动收集来自140个气象站的观测天气数据和英国近6,000个地点的天气预报。为了了解天气预报的可靠性,将三小时的温度,相对湿度,风速和风向的预报与气象站的观测结果进行了比较。这提供了使用下一个24小时预测来预测建筑物动态能源需求和消耗以及确定现场可再生能源发电输出的证据。由于预报的准确性很高,因此可以每天记录滚动预报,以为没有气象站的位置构建气象文件。这会将CIBSE天气数据的当前14个位置增加到涵盖人口中心,运动场馆和旅游景点的近6,000个位置。

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