Time Series Trend Widget

Introduction

Description

The Time Series Trend Widget is a dynamic visualization tool designed to display time-series data on a two-dimensional chart, where the X-axis represents time and the Y-axis represents measured values. It supports multiple display styles—points, sparklines, and columns—allowing users to tailor the visual output to their analytical needs.

Purpose

This widget enables renewable energy professionals to monitor trends, detect anomalies, and compare performance metrics over time. It is particularly useful for tracking operational data from Solar, Wind, and Battery Energy Storage Systems (BESS), helping stakeholders make informed decisions based on historical and real-time data.

Target Audience

Business Users: Plant managers, energy analysts, and operations teams seeking high-level insights into performance trends.
Technical Users: Engineers, data scientists, and system architects responsible for configuring dashboards and reports for operational monitoring.

Key Features & Use Cases

1. Configurable Data Points

Users can select specific metrics to visualize, such as power output, temperature, or state-of-charge.

Use Case – Solar Plant Dashboard
A solar operations manager configures the widget to display hourly DC power output across the past 7 days. This helps identify periods of underperformance due to shading or inverter issues.

2. Conditional Color Filters

Apply color rules to highlight values that meet certain conditions (e.g., thresholds, ranges).

Use Case – Wind Farm Report
An analyst sets conditional filters to color wind speed values above 12 m/s in green and below 4 m/s in red. This visually flags periods of optimal and suboptimal turbine performance.

3. Multiple Display Styles

Choose between points, sparklines, or columns to suit the context of the analysis.

Use Case – BESS Monitoring Dashboard
A technical architect uses sparklines to show the state-of-charge trend for each battery unit over the past 24 hours. This compact view allows quick comparison across multiple units.

4. Time Granularity Control

Adjust the time resolution (e.g., minute, hour, day) to zoom in or out of trends.

Use Case – Solar Plant Report
A report compares daily energy generation over the past month, helping stakeholders assess the impact of seasonal changes.

Data Types Used

The Time Series Trend Widget visualizes structured time-series data, typically organized as:

X-Axis: Timestamp
Represents the time dimension of the data. This can be configured to show data at various granularities such as minute, hour, day, or month depending on the analysis needs.
Y-Axis: Numeric Value
Displays the measured or calculated value associated with each timestamp. This could represent any quantitative metric such as production output, environmental readings, or financial indicators.
Optional: Category or Series Identifier
Used when displaying multiple data series (e.g., different assets or locations) on the same chart. This allows comparison across units like turbines, solar arrays, or battery modules.
Optional: Conditional Formatting Rules
Applied to the Y-axis values to visually highlight thresholds, anomalies, or performance bands using color filters.

Widget Use in BI App Types

Use in Dashboards

In dashboards, the Time Series Trend Widget provides real-time monitoring and quick visual insights. It is commonly used to track live performance metrics across multiple assets.

Example – Wind Farm Operations Dashboard

A dashboard displays wind speed and power output trends for each turbine using sparklines. Conditional formatting highlights turbines operating below expected thresholds, enabling fast operational response.

Use in Reports

In reports, the widget supports historical analysis and performance reviews. It helps stakeholders understand long-term trends and evaluate asset performance over time.

Example – Monthly BESS Performance Report

A report includes column-style time series charts showing daily charge/discharge cycles for each battery unit. This helps identify usage patterns and informs maintenance planning.