Project Overview

Our client contacted us to help detect where errors were occurring in their solar plant, so that when their team went to the production plant, they would know where to act, thus reducing their maintenance costs.

Project Objective

SAMA's objective was to detect where the error was occurring in the energy production chain.

Methodology Used

Our Discovery methodology and advanced analysis techniques allowed us to transform raw data into valuable information about what was happening on-site.
We performed data analysis to discriminate between normal and abnormal values in energy production levels, visualizing the relationship between different influencing factors, and analyzing variables of interest, such as irradiation or atmospheric temperature.

Process and Analysis

Data Collection and Preparation: We started with data collection, preparing, and structuring this information for analysis.

Data Cleaning: We optimized data quality by transforming it to be completely relevant and useful in finding faults in energy generation.

Analysis and Insights: We identified the set of faults that were causing the transformation from direct current to alternating current to be lower than expected.

Results Achieved

We identified specific periods and solar panels that were not generating the expected amount of energy, which could indicate equipment failures or maintenance issues. Through visualizations and analysis, a clearer view was obtained of how the solar plants were functioning, and how, when, and why energy generation conditions varied.

The data analysis allowed the company to detect specific problems in solar energy generation and take measures to correct them, thus improving the efficiency and reliability of their solar plants.

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