Distributed MPC for thermal house comfort with shifting loads and limited energy resources

This paper presents a distributed predictive control methodology for indoor thermal comfort that optimizes the consumption of a limited shared energy resource using a demand-side management approach that involves a power price auction and shifting appliance loads. The control objective of each subsystem is to minimize the energy cost while maintaining the indoor temperature in range. In a distributed coordinated environment, the control uses multiple dynamically decoupled agents (one for each subsystem/house) aiming to achieve satisfaction of available energy coupling constraints. The system is simulated with several houses in a distributed environment.

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