AI Software Deployment for Smart Grid Battery Storage
Larsh Johnson, Chief Technology Officer • Stem
AI-driven smart energy storage software uses advanced artificial intelligence and machine learning to optimize the operation of these batteries by automatically switching between battery power, onsite generation and grid power. Its core benefits include to track savings and battery performance in real time; use machine learning to maximize bill savings; predict solar generation and optimize battery storage; automatically store and release energy to maximize customer savings; manage and optimize multiple sites; integrate with market operators and utilities and automate wholesale energy market transactions; and maximize wholesale market revenues.
As Chief Technology Officer, Larsh Johnson leads hardware and software engineering to meet the unique needs of Stem’s C&I, utility and energy market customers. Prior to joining Stem, Larsh was Chief Technology Officer at Siemens Digital Grid, where he led technology development teams on products spanning from consumer metering, demand response and analytics to control center software and grid automation. He joined Siemens via the acquisition of eMeter, a Bay Area software company of which he was a co-founder and responsible for innovation and development of meter data management, analytics and advanced smart grid applications. Larsh was a founding member of the Department of Energy’s Gridwise Architecture Council (GWAC) and remains a member emeritus.