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Prioritizing cleaning activities in solar plants (soiling)
Cleaning strategies often rely on uniform schedules rather than data, leading to unnecessary costs and missed performance gains
The cost of non-targeted operations
Operators lack clear insights into where dirt accumulation most affects performance
Uniform cleaning schedules lead to unnecessary operations and increased costs
High-impact areas are not prioritized, reducing potential energy output gains
Lack of data-driven prioritization complicates maintenance scheduling and resource allocation
How NTT DATA helps
Detect surface variation patterns to identify areas with higher soiling levels
Pinpoint priority areas where cleaning delivers the greatest performance improvement
Shift from uniform schedules to data-driven intervention planning
Align cleaning activities with performance impact and resource efficiency
Avoid low-value cleaning actions by focusing on high-priority zones
Targeted interventions reduce unnecessary operational activities
Focused cleaning increases energy output from high-impact areas
Better planning enables optimized allocation of resources and schedules
Data-driven insights improve prioritization and execution of cleaning activities
