Deep Energy AI provides advanced tools to evaluate the optimal sizing of battery storage systems based on cost, and control algorithms such as FCAS, peak lopping, and arbitrage on a wholesale passthrough contract. The software simulates battery-controlled loads using user-defined inputs, then calculates costs and revenue from tariffs on an interval-by-interval basis. This detailed analysis allows users to compare different battery storage scenarios against a business-as-usual (BAU) scenario, helping to identify the most cost-effective and efficient solutions. By providing a comprehensive evaluation, Deep Energy AI ensures that users can make informed decisions about their battery storage investments.
The market is currently filled with hype around battery storage, and it can be challenging to separate fact from fiction. Deep Energy AI cuts through the noise by providing data-driven insights and precise calculations. This allows energy modellers and asset owners to objectively evaluate the benefits of different battery storage scenarios, ensuring that investments are based on solid data rather than speculation. Accurate modeling of battery systems can provide new streams of revenue and improved participation in demand response programs. Embracing Deep Energy AI\u2019s battery evaluation capabilities supports better energy management, financial performance, and long-term sustainability goals.