Randomized Customer-Sensitivity-Aware Control of Thermostatic Loads for Better Integration of Intermittent Renewables

Abstract

Increased electric grid penetration of intermittent renewable energy sources has reduced the controllability of the generation side and created a need for more coordination between generation and load to maintain grid stability. Thermostatically controlled loads (TCLs) have long been seen as capable of providing a source of load flexibility. However, controlling thousands of small loads to create a better match between generation and consumption is a challenging task. Direct load control methods tend to be imprecise and invasive, while pricing-based methods can result in social push-back and produce unreliable results. Following an established trend aimed at limiting loads synchronization effects, a probabilistic control scheme is proposed. It is based on a novel type of aggregator-customer contracts. The latter are tailored a priori so as to account for a customer’s particular tolerance to loss of comfort versus interest in cost reduction. While through these contracts, aggregators have to obey preagreed constraints on their controls, the upside for them is that they can reliably anticipate the aggregate behaviors that their pool of loads can achieve. The control is decentralized via a single so-called pressure signal which is broadcast and acts locally, in a probabilistic manner, on thermostat set points. We demonstrate how the probabilistic nature of the control allows achieving a continuum of smooth potentially desirable aggregate load behaviors.