A novel hybrid agent-based model predictive control for advanced building energy systems
                Authored by Roozbeh Sangi, Dirk Mueller
                
                    Date Published: 2018
                
                
                    DOI: 10.1016/j.enconman.2018.08.111
                
                
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                Abstract
                The development of new energy efficient components and complex energy
concepts in recent years has heightened the need to design advanced
control strategies. The main objective of this research is to develop a
control strategy for building energy systems to save primary energy by
applying the concept of multi-agent systems. Most of the advanced
control strategies have been developed to be energy efficient, while
their objectives are obtained from energy analysis. However, an energy
analysis is unable to provide information on the quality of energy
streams flowing through a system. In this study, exergy is selected as
the objective of the optimization. To reach the goal of this research,
an agent-based control for building energy systems using the exergy cost
functions is developed. Agent-based control, which takes into account
the interactions among the components of the system, offers a promising
solution to the need for more advanced control strategies for complex
building energy systems. The classical agent-based control developed in
this study is combined with model predictive control, which leads to a
novel hybrid agent-based model predictive control for the optimization
of advanced building energy systems from an exergy point of view. For
evaluation purposes, a case study is defined and modeled, which is
controlled by a reference control and the agent-based under the same
circumstances through software-in-the-loop simulations. The results show
that the agent-based control is able to reduce the primary energy
consumption by 2 percent while maintaining the room air temperature at
the same level of the reference case.
                
Tags
                
                    Simulation
                
                    Multi-agent systems
                
                    Management
                
                    Building energy systems
                
                    Agent-based control
                
                    Model predictive control
(mpc)
                
                    Exergy
                
                    Hybrid control
                
                    Advanced controls
                
                    Hvac systems
                
                    Thermoeconomic analysis