Behavior enabled IoT: A software architecture for self-adapting a renewable energy community

Abstract

The availability of large amounts of data generated by a growing number of Internet of Things devices disseminated in everyday life objects joined with the ability to use data from various sources, to gain insights into human behaviors and subsequently influence them (Internet of Behaviors), is opening the way to novel applications and paradigms for their development. Designing and engineering these applications is still a challenge due to the lack of systematic approaches and reference architectures. In this paper, we introduce the Behavior-enabled IoT paradigm to help architects and engineers design complex IoT applications based on the integration of cyber–physical systems with behavior-enabled models. We instantiate the approach by designing the architecture of a platform for governing a renewable energy community to provide an optimal trade-off between quality of service (i.e., maximizing shared load) and quality of experience (i.e., ensuring a satisfying comfort to community people) through the production of day-ahead scheduling based on expressed people preferences. The architecture is designed following a specific methodology for developing BeT systems and the obtained platform has been tested in a simulated environment. The results show the potential benefits for the community in terms of revenues, quality of experience, and quality of services. BeT-driven strategies, such as day-ahead scheduling for user device activation, provide a cost-effective way to match consumption to renewable energy production and prove to be an alternative to battery storage support systems or even an improvement.