Scaling distributed energy storage for grid peak reduction

Reducing peak demand is an important part of ongoing smart grid research efforts. To reduce peak demand, utilities are introducing variable rate electricity prices. Recent efforts have shown how variable rate pricing can incentivize consumers to use energy storage to cut their electricity bill, by storing energy during inexpensive off-peak periods and using it during expensive peak periods. Unfortunately, variable rate pricing provides only a weak incentive for distributed energy storage and does not promote its adoption at scale. In this paper, we present the storage adoption cycle to describe the issues with incentivizing energy storage using variable rates. We then propose a simple way to address the issues: augment variable rate pricing with a surcharge based on a consumer's peak demand. The surcharge encourages consumers to flatten their demand, rather shift as much demand as possible to the low-price period. We present PeakCharge, which includes a new peak-aware charging algorithm to optimize the use of energy storage in the presence of a peak demand surcharge, and use a closed-loop simulator to quantify its ability to flatten grid demand as the use of energy storage scales. We show that our system i) reduces upfront capital costs since it requires significantly less storage capacity per consumer than prior approaches, ii) increases energy storage's ROI, since the surcharge mitigates free riding and maintains the incentive to use energy storage at scale, and iii) uses aggregate storage capacity within 18% of an optimal centralized system.