The BluWave-ai core product is an AI-enabled optimization and control platform which leverages a SaaS, cloud-based, two-tier architecture. The platform consumes data from the grid’s IoT devices (sensors, meters) and delivers real-time dispatch commands from its fast inference engine. It is predictive — performing analytics on incoming data, discovering patterns, and improving its performance as it operates. The platform achieves optimization levels well beyond conventional linear programming methods, with improvements up to 75% in some cases and enhances human operator accuracy by up to 200-300%.
Our machine learning platform optimizes the cost, availability, and reliability of different energy sources, both renewable and non-renewable, in real-time. This lets our customers improve their energy decisions for sustainability, reliability, and affordability.
BluWave-ai can improve the use of renewables with existing grid assets (solar PV, wind turbines, energy storage, etc.) in the range of 5-20%. The level of improvement depends on many variables including the renewable energy capacity compared to typical load and other sources of generation and variable load. For example, during the test phase at a metropolitan utility serving a city of 25M, the BluWave-ai platform improved load prediction to sub-1% error levels, which in operation translates to a huge savings in forecast inaccuracy penalties, overall cost savings, and reduced CO2 emissions.
BluWave-ai’s AI and IoT platform accelerates the energy transition by reducing the operational and cost uncertainties associated with operating grids with high renewable and DERS penetration, thereby increasing the reliability and resiliency of a clean power supply. BluWave-ai's light footprint solution better utilizes existing data and renewable energy hardware, for a sustainable energy transition.