Paper Conference

Proceedings of Building Simulation 2017: 15th Conference of IBPSA

     

Generating High Resolution Near-Future Weather Forecasts for Urban Scale Building Performance Modelling

Hu Du, Michael Barclay, Phil Jones
Welsh School of Architecture, Cardiff University Bute Building, King Edward VII Avenue, Cardiff, CF10 3NB, United Kingdom DuH4@cardiff.ac.uk

DOI: https://doi.org/10.26868/25222708.2017.234
Abstract: The EU committed to lower greenhouse gas emissions 40% by 2030 from 1990 baseline. Building sector is the largest contributor to global greenhouse gas emissions emitting approximately a third of total emissions. To achieve the target, the United Kingdom (UK) Government’s Department for Business, Energy & Industrial Strategy and the Government’s regulator body for gas and electricity markets (Ofgem) is developing strategy to enable and enhance the use of demand-side response, energy storage and distributed generation. The Government’s research funding body - the Engineering and Physical Sciences Research Council has identified energy efficiency and security, reliable infrastructure as priority areas for strategic development in its Delivery Plan 2016-20. For implementing these changes and successfully managing the transition in building energy sector, quantitative tools and dataset are needed to understand and predict the dynamic demands from buildings and generations (particularly those from renewables) at urban and national scale. They are crucial elements for informing decision making within building and energy network control system. Traditionally, understanding the performance of buildings requires high quality local weather data for building simulation and evaluation. The weather data are often ‘secondary’ data obtained from nearby airport weather station or through local measurement. The ‘secondary’ data are often so-called Typical Meteorological Year (TMY) data in the USA, or Test Reference Years (TRY) in Europe. TMY/TRYs were chosen from past 20-30 years data using the Finkelstein-Schafer statistic method. They reflect the most ‘typical’ conditions over a long period (decades), which are not suitable for understanding current building performance (recent months or a year). Local weather stations are often very expensive to install, particularly for urban scale modelling, and it takes long time and significant effects to collect data.
Pages: 868 - 875
Paper:
BS2017_234