Crowdsourcing Energy Data for Participatory Renewable Energy Planning and Modeling

As renewable energy is increasingly fed into regional energy networks, they face significant additional spatial and temporal load fluctuations, making a reliable energy supply more difficult. This is particularly true in the context of varying weather conditions. Thus, diverse energy data on a building or household-level are essential for sustainable renewable energy planning and modeling. However, such data are hardly accessible – if existing at all – because they are mostly owned by private companies like energy providers or network operators. In this paper we tackle this challenge and propose a crowdsourcing approach to acquire fine-grained building and household-specific energy data. Further, we present a technical infrastructure which is based on (mobile) location-aware technologies. We focus on two complementary user interfaces for data acquisition, namely a web application and a smartphone app. The results demonstrate that crowdsourced building and household-specific energy data can support renewable energy planning and modeling processes.