Companies aiming to reduce their carbon footprint and negative environmental impact are looking to adopt this as a solution. As a result, efficiency and plant performance regarding energy production becomes an area of focus and concern.
Data collection and analysis is improving renewable energy power plant management in terms of operational and financial efficiency. With data collection and analysis regarding renewable energy generation, storage and consumption patterns, providers have necessary insights that can be leveraged to optimise plant operations for the best performance and efficiency.
Pele Energy Group utilises data analysis to ensure power plants operate at peak efficiency. Power plants are equipped with weather stations that have sensors that monitor weather patterns, and climate conditions. In which, the data received makes it possible to forecast energy production.
Operating and maintaining a Renewable Energy Power Plant can be complex, hence the reliance on robust data collection and analysis. Plant engineers can predict the maintenance needs and optimize their maintenance operations because of the information provided by analysing the data. Plant engineers can receive timeous updates about the power plant’s performance and the reasons why it is performing at a certain level. Whether it be weather conditions or dust on the solar module for a solar power plant, data collected through the sensors is analysed to ensure optimal performance at all times. This allows plant engineers to do preventive and predictive maintenance to reduce the power plants’ downtime. Data analysis improves decision-making, understanding of the assets and improves processes.
The images are an example of how data capturing, and analysis assist a plant engineer in operating the plant. The data captured and indicated below indicates that 2 devices on this Solar PV plant were not performing optimally, thus the engineer can react immediately and resolve the issue.
Live data analysis allows for the improvement of reactions to operational needs and has the added benefit of favorable financial implications, by detecting maintenance needs in advance.