Turn solar performance data into investment decisions.
Monitoring shows whether equipment is operating. Performance analytics should explain how operational variance affects revenue, portfolio return, risk, and the next best action.
What solar asset performance analytics should answer
An investor-facing system starts with the original investment case and compares it with normalized operating results. The goal is not to create more alarms. It is to identify which variance is financially material and which intervention can recover the most value.
- How far actual production is from the weather-adjusted baseline
- How the gap affects revenue, IRR, NPV, and cash yield
- Which site, asset, event, or constraint explains the variance
- Which action has the strongest recoverable-value case
Why portfolio normalization matters
Multi-site portfolios often combine different inverter brands, meters, loggers, time zones, naming conventions, and data-quality rules. A canonical asset model makes sites comparable without discarding their source records. Every KPI should retain its source, formula, quality status, and model version.
From lost production to lost revenue
A production shortfall is not automatically equal to a financial loss. Contract terms, curtailment, market price, degradation assumptions, availability guarantees, and operating costs all change the result. KUNIES is designed to connect these layers so an investment team can prioritize action using financial impact instead of alarm count.
What a useful pilot proves
A focused pilot should measure time to trustworthy data, portfolio coverage, actionable findings, verified recoverable value, and the path to paid deployment. Claims about savings or performance improvement should follow an agreed measurement and verification baseline.