Optimal demand response policies for inertial thermal loads under stochastic renewable sources

TL;DR

This paper develops optimal demand response strategies for thermal loads in microgrids, balancing renewable energy utilization and user comfort, revealing a transition from synchronized to desynchronized load behaviors under different models.

Contribution

It introduces a novel model that accounts for user comfort constraints, leading to a desynchronized optimal policy contrasting previous synchronized solutions.

Findings

Optimal policies promote renewable energy use and reduce non-renewable reliance.

Without comfort constraints, loads synchronize at a common temperature.

With comfort constraints, loads intentionally desynchronize to prevent surges.

Abstract

In this paper, we consider the problem of preferentially utilizing intermittent renewable power, such as wind, optimally to support thermal inertial loads in a microgrid environment. Thermal inertial loads can be programmed to preferentially consume from renewable sources. The flexibility in power consumption of inertial loads therefore can be used to absorb the fluctuations in intermittently available renewable power sources, and promote reduction of fossil fuel based costly non-renewable generation. Under a model which promotes renewable consumption by penalizing the non-renewable, but does not account for variations in the end-user requirements, the optimal solution leads to all the users' temperatures behave in a lockstep fashion, that is the power is allocated in such a fashion that all the temperatures are brought to a common value and they are kept the same after that point, resulting in synchronization among all the loads. In the first part, we showed that under a model which additionally penalizes the comfort range violation, the optimal solution is in-fact of desynchronization nature, where the temperatures are intentionally kept apart to avoid power surges resulting from simultaneous comfort violation from many loads.