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