Article ID Journal Published Year Pages File Type
6894827 European Journal of Operational Research 2018 19 Pages PDF
Abstract
Decentralised community energy resources are often abundant in smaller, more rural communities. Such communities often lack the capacity to develop extensive energy concepts and thus to exploit these resources in a consistent way. This paper presents an integrated participatory approach to developing feasible energy concepts for small communities. The novelty lies in the combination of methods, the consideration of uncertainties, and the application to an exemplary municipality in Germany. Stakeholder workshops are combined with energy modelling and multi-criteria decision analysis (MCDA), and a high transferability is ensured with mainly public data. The workshop discussion revealed three values: economic sustainability, environmental sustainability, and local energy autonomy. A total of eight alternatives for the 2030 energy system are identified to achieve these values. We find that an alternative that seeks only maximization of economic sustainability should be rejected based on elicited preferences. Instead, several alternatives seeking a maximization of environmental sustainability with constraints on economic sustainability (i.e. total cost) and local energy autonomy consistently achieve the highest overall performance scores. A maximization of economic sustainability or local energy autonomy alone results in the lowest overall performance scores and should therefore not be pursued by the community. The intermediate alternatives demonstrate that an equivalent performance gain with respect to autonomy comes at higher costs than the same gain with respect to environmental sustainability. Similarities between the best performing alternatives in terms of technologies that can be installed by 2030 show that our methodology can generate concrete and robust recommendations on building-level measures for energy system design.
Related Topics
Physical Sciences and Engineering Computer Science Computer Science (General)
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