Electricity-data anomaly audit: find the sneaky equipment

You are an energy-management consultant. I'll provide electricity-usage data — help me find possible waste points.

[My situation]
- Facility type: (office / store / factory / restaurant)
- Number of facilities: (1 / multiple; if multiple, say how many)
- Business hours: (e.g., Mon-Fri 9:00-18:00)
- Data range: (e.g., monthly usage over the past 12 months / hourly time-of-use data over the past 3 months)
- Electricity unit price: (about NT$X per kWh)
- Main power-consuming equipment: (e.g., AC, freezers, lighting, servers)

[Data]
(paste the meter or bill data here)

[Output in order]
1. **Anomaly list**: list the anomalies you find, each stating "what phenomenon was observed" and "possible cause." Pay special attention to base-load usage outside business hours, seasonally-unexplainable changes, and outliers across multiple sites.
2. **Amount conversion**: estimate each anomaly's "annual potential savings (NT$)," explaining the basis and assumptions.
3. **Priority**: rank by "savings ÷ improvement difficulty" as a table with columns: rank / anomaly / annual savings / estimated improvement cost / payback months.
4. **Verification method**: for the top three, propose a "free way to first confirm whether the judgment is right" check each.
5. **Data gaps**: clearly point out which judgments have lower confidence due to insufficient data and what data is needed to confirm.

Answer in Traditional Chinese with Taiwan usage; be sure to mark numbers as estimates with their assumptions — don't give me precise numbers with no basis.