Climate change impact on the design of urban energy system

Abstract

The initial step of the distributed energy system design process is the determination of the energy demand that the system needs to cover. Building simulation is often used for this purpose requiring climate data for the examined period. The long lifetime of buildings corresponds to timescales when considerable changes in the climate are expected to occur. Design using historical or current weather data could lead to underperformance of energy systems that cannot meet future peak loads and/or to the introduction of new demands (e.g. for cooling), considering the long-term impact of climate change. The aim of this work is to firstly investigate the impact of climate change on the loads of buildings for a case study urban quarter in Switzerland and subsequently on the design of the urban energy system to meet the quarter’s needs. Multi-year weather files are created, ranging from 2020 to 2040, using raw data from selected GCMs and carbon scenarios for the examined location using a statistical downscaling technique known as morphing. The optimal design of the urban energy system is obtained using the energy hub concept, examining simultaneously the design (selection and sizing of the conversion and the storage devices) and operational aspects of the system, with minimization of total cost as the objective. Initially, the buildings’ energy demands are calculated for the current and the future climate scenarios and their impact is assessed. Subsequently, optimal energy hub design for the current and future climate scenarios are obtained, and their differences are examined in terms of total cost, but also optimal composition and size of the energy hub. However, since standard practice involves the use of current weather data, the impact of today’s design when operating under future climatic conditions is also assessed. The differences between the operation of the future climate optimised system and the today’s design in terms of operational patterns and resulting costs are examined and any potential hours when the demand cannot be met by the present-day design are quantified.