Plant performance drill-down dashboard

Overview

The plant performance drill-down dashboard enables BESS operations managers to analyze individual plant performance in detail after selecting a plant from the portfolio overview. The dashboard provides multiple interconnected visualizations that work together to help you identify performance patterns, troubleshoot issues, and perform root cause analysis. All visualizations respond to your interactions—clicking any chart element filters related data across the entire dashboard, enabling focused investigation of specific time periods, metrics, or conditions.

The dashboard supports comprehensive analysis workflows including trend identification across time periods, comparative analysis of different metrics, pattern recognition through heatmap visualization, and granular data exploration through sortable and filterable tables.

Accessing the plant performance dashboard

From the portfolio overview dashboard, click a specific plant to navigate to the plant performance detail page. The dashboard displays the plant name clearly at the top and maintains your context throughout your analysis session. You can return to the portfolio overview at any time to select a different plant.

Plant performance overview section

The top section of the dashboard displays KPI cards that provide quick insights into overall plant performance:

Plant efficiency

Shows the overall efficiency of the plant for the selected time period. This metric helps you assess how effectively the plant converts stored energy during charge and discharge cycles.

Performance metrics

Display key performance indicators specific to BESS operations. These metrics update automatically when you change date ranges or apply filters.

Cycle count

Shows the total number of charge-discharge cycles that are completed during the selected period. This metric helps you track battery usage and plan maintenance activities.

Above the KPI cards, you can select date ranges and comparison periods to analyze performance across different time frames. The dashboard maintains your date range selection as you interact with visualizations, can ensure consistent analysis scope.

Interactive bar chart visualizations

The comparative bar chart section displays multiple bar charts showing performance metrics across different categories or time periods. Charts use color coding to distinguish between primary metrics (blue) and secondary metrics (red or pink), making it easy to compare different data series.

Each chart includes clearly labeled Y-axis metric names and X-axis categories or time periods. Hover over any bar to display a tooltip with detailed values. The bar highlights when you hover over it, providing visual feedback. Click on any bar to drill down to a more detailed view—the system filters related data in other sections of the dashboard, enabling focused analysis of the selected category or time period.

Trend analysis bar chart

The trend analysis section displays a horizontal bar chart showing performance trends over time. Time-series data appears on the Y-axis (dates), while performance values extend along the X-axis as horizontal bars. The chart uses consistent color coding and includes grid lines for easy reading.

The trend chart supports zoom-in and out functions, allowing you to focus on specific time ranges or view longer periods. Pan or scroll through extended time periods to explore historical data. Hover over any bar to view exact values and dates in a tooltip. Click a bar to filter related data throughout the dashboard.

You can change the time granularity to view data at daily, weekly, or monthly intervals, depending on your analysis needs. Select specific date ranges to focus on particular periods of interest. Export chart data for further analysis in external tools or for reporting purposes.

Interactive heatmap visualization

The heatmap section provides a color-coded visualization that helps you identify patterns across multiple dimensions. Rows represent one dimension (such as time periods or components), while columns represent another dimension (such as metrics or parameters). Color intensity indicates performance levels using a blue gradient—darker colors typically indicate higher values or better performance.

The heatmap includes clear axis labels and a color scale legend that explains the meaning of different color intensities. Hover over any cell to display a tooltip showing exact values. When you hover, the corresponding row and column headers highlight, making it easy to identify the specific data point.

Click any cell to drill down to detailed data for that specific combination of dimensions. The system filters the detailed data table to show only relevant records and updates-related visualizations to highlight the selected data. The heatmap supports zoom and pan functions for exploring large datasets, and you can export the heatmap as an image for documentation or presentations.

Detailed data table

Below the visualizations, the detailed data table provides granular access to all underlying data. The table includes columns for timestamp or date, component or asset ID, multiple performance metrics, status indicators, and calculated values.

The table supports comprehensive data manipulation capabilities:

• Sort by any column in ascending or descending order to identify the highest or lowest values
• Apply filters to multiple columns simultaneously to focus on specific data subsets
• Use the search function to locate specific records by any field value
• Show or hide columns to customize the table view for your analysis needs
• Navigate through large datasets by using pagination controls
• Select the number of rows displayed per page (10, 25, 50, or 100 records)

You can select individual rows by clicking them, or select multiple rows by using checkboxes. Export selected rows or all data to CSV or Excel format for further analysis, reporting, or integration with other tools. Copy data to the clipboard for quick transfer to other applications.

Cross-visualization interaction

All visualizations in the dashboard interact with each other, providing a cohesive analysis experience. When you click a bar in any chart, the system filters the heatmap and data table to show only related data. When you click a heatmap cell, the system filters the data table and highlights related bars in the charts. Selecting a date range updates all visualizations simultaneously to reflect the new time period. Selecting specific metrics updates all views to focus on the chosen data.

The system displays loading indicators during updates, helping ensure that you know when data is being refreshed. Your filter state persists when you navigate between different sections of the dashboard, maintaining analysis context. A "Clear all filters" option allows you to reset the dashboard to its default state. Active filters display clearly at the top of the dashboard, showing you exactly what data subsets you are viewing.

Using the dashboard for operational analysis

The plant performance drill-down dashboard supports several key operational workflows:

Trend identification

Use the trend analysis chart to identify performance patterns over time. Look for gradual changes that may indicate degradation, seasonal variations, or the impact of operational changes. Compare trends across different time granularities to understand both short-term fluctuations and long-term patterns.

Pattern recognition

Use the heatmap to identify patterns across multiple dimensions simultaneously. Look for clusters of high or low performance, systematic variations across components or time periods, or anomalies that deviate from expected patterns. The color-coded visualization makes it easy to spot patterns that might be difficult to detect in tabular data.

Performance troubleshooting

When you identify performance issues in the KPI cards or charts, use the interactive features to drill down to specific time periods or components. Click bars or heatmap cells to filter the data table to relevant records. Sort and filter the table to identify common characteristics of problematic periods. Export filtered data for detailed investigation or sharing with maintenance teams.

Root cause analysis

Combine multiple visualizations to investigate the causes of performance issues. Start with the trend chart to identify when issues began. Use the heatmap to see whether issues affect specific components or occur during specific conditions. Filter the data table to examine detailed metrics during problem periods. Compare performance across different metrics to identify correlating factors.

Comparative analysis

Use the bar charts to compare performance across different categories, time periods, or operating conditions. Select different date ranges to compare current performance against historical baselines. Use the data table sorting and filtering to identify the best and worst performing periods or components.