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.

Benefits

TIME AND COST SAVINGS

This solution makes accurate predictions (based on machine learning) of start-up time and cost, considering current plant conditions as it basis

START-UP PROCESS OPTIMIZATION

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

AVOIDANCE OF PENALTIES

This tool enables the tracking of deviations so necessary corrections can be made in advance in order to avoid penalties

DATA ANALYSIS

Improve time, fuel consumption and power generation estimations during the start-up process of the power plant, taking informed decisions

TecOS START features

Analyzes and optimizes your power plant's start-up process

  • Early detection of deviations
  • Find out fuel consumption during start-up
  • Reduce consumption of fuel and auxiliaries during start-up

Detailed and accurate start-up planning

  • Plan your start-ups, obtaining real estimates for time and cost
  • Supervise critical processes
  • Receive alerts that have been configured for your plant
Optimization Planification

Up to €5000 reduction of fuel consumption
during a start-up process

Find out your hypothetical savings
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What can you do?

TecOS START is the TecOS 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.

The analysis of the data generated through TecOS START allows users to study the start-up process and detect the different actions that can be taken to improve and optimize said process.

The application of machine learning algorithms to your process provides accurate estimates of the amount of time required for the process. TecOS START adapts based upon your plant's historical data, allowing for estimates to be improved and tailored.

Supervise the critical parameters that come into play during plant start-up and receive alerts if they undergo significant deviations. All of this information is provided to staff by means of high-performance displays that have been designed with the highest human factors engineering standards in mind.

Ask about your pilot project

How does it work?

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

TecOS START Start-up Planning

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

TecOS START Optimization of Start-up

By analyzing the data generated, the evolution of critical parameters is identified during the different start-ups, allowing processes to be studied and optimized

FAQs

Yes, TecOS START can be used in combined-cycle plants with any type of technology

Yes, TecOS START is tailored to each and every plant and it adapts to operational procedures and processes.
The machine learning algorithms are adaptable to each plant features and are trained in each start-up process of your plant

Yes, during the implementation phase, Tecnatom trains plant staff so that they can easily use the tool during start-ups

Users with permissions can view start-up processes on any connected device through an internet browser

This product is transferable to other steam power plants technologies that suffer from high-cycling start-ups

Our clients opinions

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