Using AI to Optimize Commercial-Scale Solar and Storage Design

When Winter Storm Uri hit Texas in February 2021, many businesses received unprecedented electricity bills, thanks to a spike in prices. A battery energy storage system (BESS) could have helped mitigate some of those costs, but designing one isn’t easy. It requires analysis of both historic and predicted future data points including utility rates, wholesale energy prices, weather and climate data, electricity consumption and solar photovoltaic (PV) power generation. Artificial intelligence (AI) is a powerful way to ingest and analyze all of that data — and to generate actionable intelligence.

In this white paper, you’ll learn how artificial intelligence can help businesses save money, go green and reduce uncertainty. The paper presents the case of a company in Plano, Texas, that had a solar PV system at the time of Winter Storm Uri, but no storage component to help mitigate spiking electricity costs. The result was a February utility bill equivalent to three years of normal electricity statements.

The paper outlines how AI and machine learning were used to analyze years of price, load and solar generation data, turning solar savings into diverse revenue streams and carbon offsets.