Tata Power Renewables has opened a Centre for Renewable Energy Analytics, Monitoring and Scheduling, known as CREAMS, at its Trombay plant on August 20. The facility is presented as one of the most advanced centralised renewable energy monitoring hubs in the country. CREAMS serves as an integrated digital command centre providing real time monitoring, analytics, forecasting, scheduling and performance optimisation of solar and wind assets across multiple states. The platform offers a unified view of the company's portfolio and enables operators to track performance round the clock and initiate corrective measures when required. The centre integrates data from both utility scale and distributed projects to provide situational awareness for operational teams. Operating through robust digital infrastructure, the centre provides 24x7 surveillance and operational support for renewable installations and underscores the growing role of data driven decision making in the clean energy transition. The centralised architecture has been designed to maximise generation and improve asset reliability. By combining analytics with advanced monitoring systems the centre aims to reduce operational losses and ensure regulatory compliance while enhancing overall efficiency across geographically dispersed projects. The facility continuously processes large volumes of operational data each day to support energy forecasting, grid scheduling and asset health monitoring. It is described as a tool for rapid detection of performance deviations enabling timely technical interventions and improved plant availability. With renewable capacity expanding across the country centralised control facilities such as CREAMS are increasingly important for efficient grid integration and reliable delivery of green power. Tata Power Renewables positions the Trombay facility as a key pillar in managing and optimising its growing renewable portfolio and supporting national clean energy objectives. It is intended to support decision makers and grid operators by improving forecast accuracy and facilitating coordinated responses during variability.