Mean Field Control for Efficient Mixing of Energy Loads
This work addresses the challenge of efficient demand response for aggregators managing large numbers of energy loads, offering a control method that improves recovery speed and comfort zone adherence.
The authors apply mean field control with nonlinear feedback to coordinate an ensemble of energy devices, achieving significantly faster recovery to steady state compared to fixed feedback, and demonstrating 'super-relaxation' where total energy consumption stabilizes faster than the device state distribution.
We pose an engineering challenge of controlling an Ensemble of Energy Devices via coordinated, implementation-light and randomized on/off switching as a problem in Non-Equilibrium Statistical Mechanics. We show that Mean Field Control} with nonlinear feedback on the cumulative consumption, assumed available to the aggregator via direct physical measurements of the energy flow, allows the ensemble to recover from its use in the Demand Response regime, i.e. transition to a statistical steady state, significantly faster than in the case of the fixed feedback. Moreover when the nonlinearity is sufficiently strong, one observes the phenomenon of "super-relaxation" -- where the total instantaneous energy consumption of the ensemble transitions to the steady state much faster than the underlying probability distribution of the devices over their state space, while also leaving almost no devices outside of the comfort zone.