TY - JOUR AU - Shen, Bochao AU - Narayanaswamy, Balakrishnan AU - Sundaram, Ravi PY - 2015/02/10 Y2 - 2024/03/28 TI - SmartShift: Expanded Load Shifting Incentive Mechanism for Risk-Averse Consumers JF - Proceedings of the AAAI Conference on Artificial Intelligence JA - AAAI VL - 29 IS - 1 SE - Computational Sustainability and Artificial Intelligence DO - 10.1609/aaai.v29i1.9240 UR - https://ojs.aaai.org/index.php/AAAI/article/view/9240 SP - AB - <p> Peak demand for electricity continues to surge around the world. The supply-demand imbalance manifests itself in many forms, from rolling brownouts in California to power cuts in India. It is often suggested that exposing consumers to real-time pricing, will incentivize them to change their usage and mitigate the problem - akin to increasing tolls at peak commute times. We show that risk-averse consumers of electricity react to price fluctuations by scaling back on their total demand, not just their peak demand, leading to the unintended consequence of an overall decrease in production/consumption and reduced economic efficiency. We propose a new scheme that allows homes to move their demands from peak hours in exchange for greater electricity consumption in non-peak hours - akin to how airlines incentivize a passenger to move from an over-booked flight in exchange for, say, two tickets in the future. We present a formal framework for the incentive model that is applicable to different forms of the electricity market. We show that our scheme not only enables increased consumption and consumer social welfare but also allows the distribution company to increase profits. This is achieved by allowing load to be shifted while insulating consumers from real-time price fluctuations. This win-win is important if these methods are to be embraced in practice. </p> ER -