TecOS START allows for the optimization of the start-up process (time, fuel consumption and power generation) of the power plants by using machine learning.
This solution makes accurate predictions (based on machine learning) of start-up time and cost, considering current plant conditions as it basis.
This tool enables the tracking of deviations so necessary corrections can be made in advance in order to avoid penalties.
The information provided by the system allows for the optimization of the power plants start-up process, improve process planification and early detection of deviations.
Improve time, fuel consumption and power generation estimations during the start-up process of the power plant, taking informed decisions.
Analyzes and optimizes your power plant’s start-up process.
Detailed and accurate start-up planning.
Suite's solution that allows for optimization of the start-up process of power plants that have frequent starts and stops, reducing the process costs and, thus, improving the facility's financial performance.
By applying machine learning algorithms, TecOS START yields precise estimates of start-up time, consumption of gas and auxiliaries, and energy generation throughout the entire start-up process.
Find out the start-up time required for your power plant based upon its initial conditions for improving your tasks planification, thus reducing fuel consumption and avoiding penalties.
TecOS START is the TecOS Suite's solution for predicting and monitoring your plant's start-up. With the help of TecOS START, you will be able to supervise key parameters and your plant will get connected to the grid on time and with the lowest possible cost.
Improve the tasks planning thanks to the estimates provided by TecOS START. This, in turn, improves efficiency and cuts down on fuel use during the plant's start-up process.
By analyzing the data generated, the evolution of critical parameters is identified during the different start-ups, allowing processes to be studied and optimized.
Yes, TecOS START can be used in combined-cycle plants with any type of technology.
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