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This use case demonstrates how TrendMiner's functionalities can be leveraged to perform retrospective analyses, leading to enhanced productivity and efficiency in our power plant operations.

 

Background

In our power plant, managing fuel consumption efficiently is crucial for operational cost savings and environmental impact reduction. This use case focuses on a retrospective analysis aimed at reducing fuel consumption by adjusting PID (Proportional-Integral-Derivative) parameters within our system.

Challenge

The primary challenge was to reduce fuel consumption without compromising the performance and stability of the power plant. The desired outcome was to identify the impact of PID parameter adjustments on fuel consumption by comparing data from specific periods before and after the changes were implemented.

Solution

To address this challenge, the following steps were taken:

  1. Parameter Adjustment: The PID parameters were adjusted in our power plant system to optimize fuel consumption.

  2. Data Collection: Data from periods before and after the PID parameter adjustments were collected for analysis.

  3. Retrospective Comparison:

    • Visualization: Using TrendMiner, the main variables related to fuel consumption were visualized, and we navigated through time to specific periods before and after the PID parameter changes.
    • Layer Compare Table: The layer compare table functionality in TrendMiner was utilized to calculate the average fuel consumption for the defined periods.

     

  4. Reporting: The results were exported as an Excel report for further analysis and documentation.

Picture 1: Comparison of Key Parameters Before and After PID Adjustment: The table illustrates the average values for Total Power, Fuel In, and Post-Combustion Flow for the years 2019 and 2020, highlighting a significant reduction in fuel consumption (Fuel In) by 6.2% following the PID parameter adjustments.

Value

By implementing this use case, we achieved the following outcomes:

  • Fuel Consumption Reduction: A noticeable reduction in fuel consumption was observed after the PID parameters were adjusted.
  • Cost Savings: The decrease in fuel usage led to significant cost savings for the power plant.
  • Improved Efficiency: The retrospective analysis enabled us to identify optimal settings for the PID parameters, thereby improving overall operational efficiency.
  • Data-Driven Decision Making: The use of TrendMiner facilitated a data-driven approach to monitor and analyze the impact of changes, ensuring informed decision-making.
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