AI Smart Grid Incentives for Retrofit Financing and Dispatch

The patent introduces an intermediary financing system that acts as a mediator between energy service providers and homeowners. This system includes a financing entity that provides on-bill financing, where the loan is repaid through a line item on the utility bill. This intermediary structure eliminates the barrier of high upfront costs by spreading payments over time through the utility billing system, thereby enabling homeowners to access energy-efficient retrofits without significant initial investment.

The patent replaces traditional rule-based algorithms with machine learning models that can automatically learn and adapt to individual homeowner patterns and preferences. The system includes trained machine learning models that analyze historical energy consumption data, weather patterns, and user behavior to generate personalized energy plans. This substitution of mechanical rule-based systems with intelligent learning systems enables the platform to provide highly customized recommendations without requiring complex manual configuration, thereby achieving both personalization and operational efficiency.

The patent divides the energy optimization system into multiple segmented components that operate at different levels. The demand response platform is segmented into a central optimization engine that handles high-level decision-making and local control algorithms at consumer premises that handle real-time execution. This segmentation allows the computationally intensive optimization calculations to be performed centrally without requiring full real-time processing at every device, thereby achieving real-time optimization effects while reducing overall computational burden through distributed architecture.