JouleOS provides a comprehensive cloud based machine learning driven power portfolio management operating system that allows the utilities to forecast demand and schedule power.
The energy market of India is rapidly transforming with large-scale electrification schemes ensuring 24x7 power for all, increasing penetration of RE, and tighter policy measures to ensure smooth grid operations.
Owing to such reforms the power purchase cost of Utilities has significantly increased over the last few years. This is driving the requirement for utilities to predict the electricity demand precisely and implement optimized generation schedules so that the predicted demand is met at the least cost taking into account all available power resources like long-term PPA, TAM, DAM, and RTM.
Accurately predicting 15-minute demand for any given time horizon, forecasting prices in the TAM/ DAM and RTM, selecting the plants for implementing the least cost generation schedule and manually preparing bids and managing trading in various electricity markets can be manually intensive for operators relying on inaccurate weather data, spreadsheet-based tools and file-based approval processes.
JouleOS engine uses historical demand data, satellite-based Global High Resolution Atmospheric Forecasting data (temperature, wind speed, wind gust, rainfall, humidity), local station-based weather data, and data of special days to calculate the 15-minute time block-wise demand forecast on intra-day, day-ahead and week-ahead basis. Coupled with Mercados market intelligence on short-term prices, the engine provides power procurement optimization for our consumers. The engine complies will all prevalent regulations. The platform provides an integrated solution for selling/buying power on exchange platforms through automated bid preparation and approval modules.
