How AI can Store and Save Energy for Solar Developers?
Solar developers are yet to equip their systems with AI-driven technologies. AI can help increase value and in turn, resulting in escalated margins.
FREMONT, CA: Artificial Intelligence (AI) enabled energy storage is giving rise to intelligent solar as renewable energy on the grid has increased, along with the increasing customer demand to take control over their opinions on energy sources and costs. It avails newer tools for utilities and grid operators to balance out variable generation and congestion in the grid during distribution.
The unlocking of value in energy storage has only a slight effect in terms of battery hardware. The primary method to transform the returns of a solar investment is AI. For the efficient evaluation of the system to leverage from the solar augmented storage, AI is necessary to perform the predictive analysis, ML, and grid-edge computing.
The detailed data helps increase the accuracy of AI, allowing it to make the optimal decisions about when to buy, generate, or store the energy. AI delivers the values with predictive analysis from the customer’s solar affected load. Then it moves on to optimize various related factors and takes real-time economic decisions that benefit the customers, owner, and the grid.
A widespread agreement stating, with the capture of more value from the Investment Tax Credit (ITC), adding AI-powered energy storage will enhance the value of returns for the customers is accepted. It gives the users greater control and flexibility all through the project lifetime during which, customers face approximately five to six rate changes. In addition to rate changes, regulatory, and financial changes that alter the value of investments for good or bad is also expected. Unfortunately, not many of the developers understand that AI-based storage can enable the user access to new value streams and market exposure by turning the solar project into a dispatchable grid-facing asset.
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AI-driven storage systems can provide other services and contribute to the value stack. For example, when customers can access additional capacity payments from their utility or receive services from the grid payments in the wholesome market by giving the unused stored energy to reduce the aggregated load.
Energy storage can provide its customers, approximately five to 30 percent of added returns; without even including the additional future value of the reduced risk from stabilized rates. The solar developer, with the installation of AI-driven energy storage, attains a typical offer of 40 to 50 percent higher margin.
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