Using In-Home Energy Storage to Improve the Resilience of Residential Electricity Supply

Abstract

Electricity-supply interruptions can be costly and disruptive. Electricity-supply reliability and resilience can be enhanced by customers having on-site energy storage, which supplements electricity-system supply. This paper proposes a two-stage stochastic optimization model that can be used in a rolling-horizon fashion to schedule such use of energy storage. We demonstrate the model with a case study that combines electricity-supply-reliability data for a real-world electric utility, survey data regarding residential customers’ willingnesses to pay for backup energy during electricity-supply disruptions, and a highly resolved Markov chain model of building-occupant behavior and associated electricity use that is calibrated to census data. We find that the low probability of an electricity-supply disruption occurring during any given time-step limits the charging of the energy storage in anticipation of possible disruptions. We demonstrate two approaches to reduce this myopic use of energy storage. Our case study shows that penalty parameters can be used to control the conservatism of the model in using as opposed to retaining stored energy during an electricity-supply disruption. Overall, we show the viability of on-site energy storage to enhance electricity-supply reliability and resilience and the feasibility of our model and algorithm for real-time control of energy storage for such a real-world application.

Keywords

• Energy storage
• electricity-system reliability
• stochastic optimization