CRAFTCIRLEM: enhanced Climate Resilience And Flexibility in complex urban environments Through integrating Collective Intelligence and Reinforcement Learning into Energy Management

Climate change challenges urban life and induce chains of events with disastrous consequences. Climate adaptation of buildings and urban areas is essential as they accommodate many people. This can be challenging without compromising sustainability and user comfort.

There is a need for flexible and climate-resilient energy management approaches that account for complex and multifaceted interactions in urban areas, affected by factors, such as climate, user behaviour and adopted technology.CRAFTCIRLEM develops an innovative demand side management (DSM) system based on collective intelligence (CI) and reinforcement learning (RL), called CIRL-DSM.

CI is a form of distributed intelligence that emerges in collaborative problem solving and decision making.

RL is an area of machine learning about learning the optimal behaviour in an environment to obtain maximum cumulative reward.

CIRL-DSM enables the simple and secure communication and control of buildings and energy systems in a scalable manner (from building to urban scale) with a minimum need for ICT upgrade and energy simulation.

CRAFTCIRLEM will investigate the theoretical basis of developing and integrating CIRL-DSM while accounting for user comfort, sustainability, and climate change adaptation, with a special focus on climate resilience.

CRAFTCIRLEM gains from a multidisciplinary consortium as well as the developed knowledge in the previous and ongoing projects of the team.