We are seeking a solution that includes mechanisms/algorithms for selecting optimal transformer parameters based on the actual load conditions present in the power grid. The selection of transformers should take into account various types of data from different sources (e.g., slowly changing passport data, rapidly changing measurement data from smart meters, and data from the SCADA system, as well as information from the inventory system about equipment statuses). The system should have reporting capabilities and the ability to create action recommendations (e.g., transformer replacement).

We are looking for a solution that will help identify potential benefits in the operational and commercial optimization of renewable energy production units. The goal is to utilize available production data (streaming) from selected generation units and build a data system/model that can generate financial and operational benefits, for example through balancing, commercial and operational recommendations, etc.

We are looking for a solution that can provide short-term (e.g., 3-hour) and accurate (e.g., 15-minute granularity) forecasts of electricity production from renewable energy generation units. The solution should utilize available production data (streaming) from selected generation units and develop a highly accurate algorithm for short-term electricity production forecasting. The solution must continuously adjust forecasts and adapt to the most up-to-date weather information. Upon project completion, ownership and copyright of the algorithm (work) must be transferred to ORLEN S.A.