Convergent announces operation of Maryland solar and storage portfolio


Energy storage provider Convergent Energy + Power said it has reached operations on a three-project portfolio of solar-plus-storage systems developed for Choptank Electrical Cooperative, which serves Maryland’s Eastern Shore.

The three projects in the portfolio combine to contribute 4 MW/8 MWh of storage and over 2 MW of solar PV to Convergent’s existing portfolio in the Delmarva peninsula. Across the peninsula, the company has developed and now operates a portfolio of five solar and storage projects, in addition to the eight solar and storage systems totalling 37 MW/121 MWh of storage and 56 MW of solar PV that the company is currently developing in Upstate New York.

The Delmarva peninsula experiences a litany of extreme weather events that can compromise the region’s energy resiliency, namely hurricanes, flooding and extreme wind. Convergent’s portfolio was selected and constructed to increase the electrical system’s resilience in the face of these weather events, as well as to lower customer bills.

“Adding an energy storage system to existing solar PV is one of the best ways to optimize solar performance, lower energy costs, and increase reliability,” said Frank Genova, Convergent’s Chief Operating and Financial Officer.

Convergent was launched as a startup in 2011 to develop, own and operate large-scale storage for industrial customers and utilities. It initially self-funded its projects, raising $70 million to do so. Acquired by Energy Capital Partners in 2019, the company now has over $400 million invested in or committed to projects in operation or under development in 40 states and the Province of Ontario.

Convergent is also operating and overseeing maintenance for the 9 MW/36 MWh and 6 MW/24 MWh lithium-ion battery energy storage systems at one of Southern California Edison’s (SCE) substations in Santa Ana, California using Convergent’s energy storage intelligence, PEAK IQ.

The company’s PEAK IQ uses artificial intelligence and machine learning technologies to ensure energy is stored and dispatched at the most strategic times.

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