LAUSR

Energy systems in buildings, especially heating, ventilation, and air conditioning are often operated inefficiently. The key to efficiency is the building automation control system: this paper examines the optimization of control strategies in building automation using a cognitive system that operates on a knowledge base, which provides the necessary semantic information. This system shall generate, assess, and execute control strategies, and find optimal control solutions. By introducing an intelligent system that identifies specific control strategies for a building and optimizes toward its specific usage, we achieve the advantage of automatically generating automation and control solutions, saving the efforts for manual adaptation. We introduce the knowledge base and the cognitive system, and explain the methodology and algorithms used to implement the required functions. The approach is applied to a building energy management use case that optimizes the operation of a ventilation system.