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Solar photovoltaic (PV) has the potential to make an important contribution to global sustainability, however, the misalignment between solar production and residential demand presents challenges for widespread PV adoption. Combining PV and storage is one way that this challenge can be overcome. In this work, we use one year of smart meter data from 369 consumers in three different US regions and calculate their economic benefits from both PV and coupled PV-battery systems. We consider a range of different electricity pricing schemes from the consumer regions, including both Feed-In-Tariff (FIT) and Net-Energy-Metering (NEM) policies. Significantly, our work uses real demand data, real PV generation data and optimizes each individual consumer’s battery operation to minimize their electricity bill. Furthermore, we study the effect of batteries on consumer self-sufficiency, which is important because increasing self-sufficiency is a primary motivating factor behind battery adoption. We find that PV is profitable for the majority of consumers with most current pricing scenarios but PV-battery systems are always less profitable. However, batteries can provide very significant increases in self-sufficiency and we find that a majority of consumers can exceed 70% self-sufficiency with a 20 kW h battery and a PV system that produces the equivalent of their consumption. This is compared to an average self-sufficiency of 35% with PV only. Finally, recognizing that a number of factors could lead to profitable batteries in future, we study the sensitivity of battery profitability to future electricity prices in a FIT scenario, also accounting for future decreases in PV and battery costs. We find that if PV-battery systems are to become better investments than PV-only for the majority of consumers, retail electricity prices above $0.40/kW h and FIT rates below $0.05/kW h are a likely requirement. [ABSTRACT FROM AUTHOR]

Energy storage can help integrate local renewable generation, however the best deployment level for storage remains an open question. Using a data-driven approach, this paper simulates 15-min electricity consumption for households and groups them into local communities of neighbors using real locations and the road network in Cambridge, MA. We then simulate PV for these households and use this framework to study battery economics in a high PV adoption, high electricity cost scenario, in order to demonstrate significant storage adoption. We compare the results of storage adoption at the level of individual households to storage adoption on the community level using the aggregated community demands. Under the simulated conditions, we find that the optimum storage at the community level was 65% of that at the level of individual households and each kWh of community battery installed was 64–94% more effective at reducing exports from the community to the wider network. Therefore, given the current increasing rates of residential battery deployment, our research highlights the need for energy policy to develop market mechanisms which facilitate the deployment of community storage. [ABSTRACT FROM AUTHOR]