Abstract
Abstract The inclusion of temporal aspects in the environmental assessment of complex socio-technical systems is crucial. For power systems, such considerations allow computing the environmental impacts related to demand-side management strategies which could not be assessed with static data, such as temporal shifts of part of the demand from one period of the day to another. Several life cycle assessment (LCA) studies have included temporal aspects, but mostly regarding the system's production function. The consumption side of a socio-technical system, however, is also prone to fluctuate in time and its misrepresentation may lead to additional errors. In this study, the residential power demand of a set of Canadians' homes was modeled with a stochastic approach. Then, three different LCA approaches are compared: the use of an average or a marginal electricity mix and a combination of the two. The influence of the temporal granularity of data (yearly average or hourly data) on LCA results was also investigated. The case study of a simple demand-side management strategy illustrates the method. Results show that the assumption of a constant demand leads to errors regarding environmental impacts assessment, which may be as high as 136% depending on the period of the year assessed. Moreover, the wrong assumption regarding the nature of power demand leads to sub-optimal results for demand-side strategy: the use of an average electricity mix slightly increases greenhouse gas emissions, whereas applying a marginal mix decreases emissions by 10%.
Published Version
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