Integration guides for monitoring.

The platform provides comprehensive monitoring across four levels: Plant-level (aggregate performance, total generation, plant-wide PR), Inverter-level (DC/AC power, efficiency, temperature, MPPT performance), SCB-level (string current/voltage, health scoring, connection tracking), and String-level (individual string current, voltage, power output, and performance diagnostics).

HelioExpect Predictive Monitoring offers 74+ visualization types including real-time charts, heatmaps, performance trends, comparison graphs, geographic maps, and customizable dashboards. All visualizations update in real-time using WebSocket connections for instant data refresh.

The platform uses WebSocket technology for real-time data updates. Monitoring data refreshes continuously as new measurements arrive from your solar assets. You can configure update intervals from 1-minute to 15-minute granularity based on your monitoring needs.

The system uses advanced machine learning algorithms to analyze historical equipment data and identify patterns that precede failures. It creates site-specific models analyzing inverter, SCB, and string performance data. The AI learns from equipment behavior patterns, environmental conditions, and operational parameters to predict when components are likely to fail, providing 0-100% health scores, failure probability estimates, and specific maintenance recommendations.

HelioExpect Predictive Monitoring prevents 30-50% of unplanned downtime through early failure detection and proactive maintenance scheduling. The system predicts failures days in advance, allowing you to plan maintenance activities during optimal windows and avoid costly emergency repairs.

Health scores range from 0-100% for each component. 90-100 (Excellent): Continue normal monitoring. 70-89 (Good): Normal operations. 50-69 (Fair): Schedule inspection within 30 days. 30-49 (Poor): Plan maintenance within 2 weeks, increase monitoring. 0-29 (Critical): Immediate inspection required, consider emergency maintenance. Each score includes trend analysis and specific recommendations.

Minimum: 1 month of continuous historical data for basic predictions. Optimal: 6-12 months of data to capture seasonal patterns, weather variations, and equipment behavior changes. Required data includes power output, temperature, voltage, current, and environmental conditions. Data quality is crucial - gaps can reduce prediction accuracy. For new sites, the system uses transfer learning from similar sites.

The platform provides 4 severity levels: Critical (immediate action required, production-impacting), High (requires attention within hours, significant performance degradation), Medium (monitor closely, plan maintenance within days), and Low (informational, minor issues requiring eventual attention).

Yes, administrators can create custom alert rules through the UI. The system supports 24 comprehensive rule templates with 9 operators (>, ≥, <, ≤, =, ≠, Between, Outside, In List), 9 metrics, 8 aggregations, time windows, AND/OR logic, context filters, and cooldown periods to prevent alert spam.

Start with Critical alerts affecting production, then High severity alerts. Use site filters to focus on assigned locations. Check the production impact column to see which alerts cost the most energy. The platform allows bulk operations to acknowledge, resolve, or assign multiple alerts simultaneously.

Alerts can be delivered via real-time dashboard notifications, email alerts with customizable recipients, push notifications (when configured), and webhook integrations to external systems like Slack, Teams, OpsGenie, or PagerDuty.

The platform supports automated scheduled reports (daily, weekly, monthly), ESG impact reports with carbon metrics, performance ratio analysis, period comparisons (week-over-week, month-over-month, year-over-year), maintenance logs, and custom reports. All reports can be exported in PDF, CSV, Excel, or JSON formats.

Period Comparison allows you to compare current performance with previous periods using flexible time ranges. Select your current range and set the baseline to 'Same period last week/month/year.' The system automatically aligns data, calculates deltas, and generates comparison charts with KPIs showing percentage changes.

The system automatically calculates CO2 avoided (tons), trees equivalent, cars removed from roads, homes powered, and lives improved. These metrics are based on your site's energy production and regional emission factors. Reports comply with GRI, SASB, and other disclosure frameworks.

Yes, you can export raw data at various granularities (15-min, hourly, daily, weekly, monthly) in CSV, Excel, or JSON formats. Use the download icon above charts or navigate to the Export section. For large datasets, the system allows batch exports to prevent timeout issues.

Navigate to Custom Dashboard, select your site, drag widgets from the library (74+ types available), configure granularity for each widget (15min, hourly, daily, etc.), arrange widgets using drag-and-drop, save the layout with a name, and share the configuration with your team. Each dashboard supports multiple tabs and layouts.

Yes, dashboards can be customized for different roles. Create separate dashboards for executives (high-level KPIs), O&M teams (detailed diagnostics), investors (financial and ESG metrics), and field technicians (maintenance and alert views). Role-based access control ensures users only see authorized data.

Yes, you can export dashboard configurations as JSON files and share them with team members. Users can import these configurations to replicate the exact layout and widget settings. Dashboards can also be set as default views for specific user roles.

The platform tracks MPPT efficiency (maximum power point tracking performance), string health (current, voltage, power for each string), DC/AC power conversion, temperature profiling (ambient, module, inverter temperatures), performance ratio (PR) at all levels, capacity utilization, and efficiency trends over time.

Each string is monitored individually for current, voltage, power output, and performance anomalies. The system detects underperforming strings, reversed polarity (safety critical), dead strings, high-resistance connections, and soiling impact. String-level data helps pinpoint issues to specific rows or modules.

MPPT (Maximum Power Point Tracking) efficiency measures how well inverters extract maximum power from solar panels under varying conditions. Low MPPT efficiency (typically <95%) indicates inverter issues, shading problems, or panel degradation. The platform tracks MPPT efficiency in real-time and alerts when it drops below configurable thresholds.

Yes, HelioExpect provides comprehensive REST APIs for programmatic access to monitoring data, alerts, predictions, and reports. API access includes authentication via API keys, rate limiting, webhook support for real-time notifications, and complete documentation with code examples.

Yes, you can export maintenance logs and work orders as CSV for import into your CMMS (Computerized Maintenance Management System). The platform also supports webhooks to automatically push maintenance recommendations and alerts to external systems.

The platform integrates with Slack, Microsoft Teams, OpsGenie, PagerDuty (via webhooks), FTP/SFTP for automated data delivery, email services for automated reports, and BI tools (Tableau, Power BI) via CSV/JSON exports. Custom integrations can be built using our REST API.

The platform supports 4 user roles: Admins (manage users, configure settings, access all sites, enable integrations), Managers (view assigned sites, manage alerts, schedule maintenance, export reports), Employees (view dashboards, add operational notes, limited site access), and Guests (read-only access for investors, auditors, or partners).

Administrators can assign specific sites to users based on their role and responsibilities. Users only see sites they're authorized to access. This is useful for multi-site portfolios where different teams manage different locations or for providing limited client access.

Yes, the platform maintains complete activity audit trails including user logins, alert acknowledgments and resolutions, configuration changes, data exports, and maintenance actions. Audit logs are available for compliance and security reviews.