The pressing need for sustainable and efficient energy solutions has driven the exploration of hybrid systems combining biomass, photovoltaic, and other renewable sources. This study introduces the Cognitive Innovator Xcelerator (CIX), an advanced AI framework designed to optimize the design and integration of these complex systems. CIX employs a multi-faceted approach, integrating Intelligent Problem Mapping and ASIT Thinking Modules to analyze and address challenges in hybrid energy system design. By leveraging AI-driven idea generation and solution refinement, CIX facilitates a systematic exploration of potential design configurations. The application of CIX led to the identification of novel, efficient configurations for hybrid energy systems, surpassing conventional designs in energy output and sustainability metrics. Physical testing of the optimized design confirmed theoretical predictions, demonstrating significant improvements in energy efficiency and system integration. Through intelligent problem mapping and creative solution generation, CIX proves to be a powerful tool in advancing the development of sustainable hybrid energy systems.