EOS LIVE DASH Area and Distribution Charts

The chart types used in EOS LIVE DASH provide more than real-time monitoring of SCADA and energy data. They help users understand accumulation, continuity, relationships between variables, operating regions, and anomalous behavior. This section examines Area2D, SplineArea2D, Scatter and ZoomScatter charts, particularly from the perspective of power generation facilities and HPP applications.

Visual note: The charts on this page are representative SVG drawings. They do not contain actual plant data; they are used to visually explain the analytical purpose supported by each chart type.

1. Area2D

Area2D (2D Area) is the area-filled version of the Line chart, emphasizing the magnitude of a value along a time or sequential axis and strengthening the visual perception of accumulation/impact over time. In SCADA, power generation, and performance reports, it is particularly useful for visually emphasizing concepts such as overall impact, volume, and continuity.

Basic Structure

  • X Axis: Time or sequential category.
  • Y Axis: Measured value; for example, MW, MWh, %, hours, flow rate, or level.
  • Area: The region below the line is filled to emphasize the visual weight created by values over time.

When Is Area2D Used?

  • To visually emphasize accumulation or total impact over time.
  • To make the continuity of a process value more apparent.
  • To create a strong overall view on executive screens and summary reports.
  • To show the contribution of multiple areas to the overall total when several areas are used.

SCADA and Energy System Use Cases

  • Overall electricity generation: Daily generation profile, load curve, and demand–generation balance.
  • HPP power generation: The accumulation effect created by hourly/daily generation over time.
  • Reservoir fill level: Monitoring seasonal and periodic changes in reservoir level with a sense of volume.
  • River flow rate: Visualizing the time-distributed impact of flow load rather than focusing only on sudden peaks; providing visual support for flood and spillway planning.
  • Turbine contributions: Using a Stacked Area approach to monitor the contributions of Turbine-1, Turbine-2, and Turbine-3 to total generation.
  • Water use–energy conversion: Interpreting which time periods use more water together with the corresponding energy output.
  • Lost energy/curtailment: Visually emphasizing the effect of maintenance outages, grid curtailments, and low-flow periods on ungenerated energy.
  • Rainfall–reservoir response: Comparing rainfall amounts with changes in reservoir level.
  • Minimum ecological flow: Monitoring the continuity of released water flow over a day or month.

Interpretation approach: In Area2D, the size of the area visually strengthens the impact created by the value over time. However, when calculating physical energy or volume, axis units, sampling interval, and calculation method must also be taken into account.

2. SplineArea2D

SplineArea2D combines the Area2D approach with a spline (smoothed curve). The purpose is to visually reduce sharp breaks between measurement points and present the overall trend, continuity, and area effect in a smoother manner.

Combination of Two Fundamental Features

  1. Area: Emphasizes the magnitude of the value and the visual accumulation it creates over time.
  2. Spline: Uses smooth transitions instead of segmented straight lines, making the overall behavior easier to interpret.

Basic Structure

  • X Axis: Time or sequential data.
  • Y Axis: Measured value such as MW, MWh, %, °C, level, or flow rate.
  • Line: Spline curve.
  • Area: The region below the curve is filled to strengthen the perception of continuity and impact.

SCADA and Energy System Applications

  • Daily generation profile: Presenting the overall generation trend more smoothly in noisy measurements.
  • Temperature changes: Monitoring overall temperature behavior rather than focusing on short-term breaks.
  • Reservoir level: Understanding the seasonal and long-term behavior of water levels where sudden physical breaks are not expected.
  • River flow rate: Observing the continuity of flow as it rises, peaks, and returns to normal following rainfall.
  • Stacked SplineArea: Smoothly monitoring the contributions of turbines to total generation over time.
  • Water use: Highlighting the average behavior of water usage over time.
  • Lost energy: Presenting outages and generation losses more intuitively as accumulated effects.
  • Rainfall–reservoir level relationship: Monitoring the natural delay between rainfall and reservoir response more smoothly.

Caution: Spline provides visual smoothing. Therefore, in situations where sudden alarms, sharp limit violations, or exact examination of actual measurement points are critical, it should be evaluated together with complementary charts such as Line/Scatter so that the raw data behavior is not hidden.

3. Scatter

The Scatter chart is one of the fundamental analytical chart types used to examine the relationship, correlation, operating regions, and anomalous behavior between two or more numerical variables. It is particularly useful in power generation facilities and SCADA performance analysis for directly answering the question: “How does Y behave when X changes?”

Basic Logic of a Scatter Chart

  • Each point: Represents a measurement instant or data pair.
  • X Axis: Independent variable; flow rate, wind speed, irradiance, load, etc.
  • Y Axis: Dependent variable; power, efficiency, heat rate, voltage deviation, etc.
  • Time: Not mandatory; the purpose is to examine relationships between variables rather than time sequence.

What Does Scatter Show?

  • Positive correlation: Y generally increases as X increases.
  • Negative correlation: Y generally decreases as X increases.
  • Random distribution: No clear relationship exists or the relationship is weak.
  • Operating regions: Separation of normal operating clusters from abnormal/out-of-limit regions.
  • Outlier: Identification of anomalous points that may indicate sensor errors, equipment failures, or unusual operating conditions.

What Is Scatter Not?

  • It does not primarily show time trends like Line.
  • Time sequence is not the main purpose.
  • It is not, by itself, a tool for displaying average or total values.

Examples in Power Generation Facilities

  • HPP flow rate–power: Turbine characteristics, efficiency degradation, and possible cavitation operating regions.
  • Flow rate–efficiency: Investigation of optimum operating flow rate and blade/nozzle adjustment problems.
  • Turbine speed–vibration: Investigation of resonance regions and bearing/balance problems.
  • Load–efficiency: Part-load behavior and optimum operating point, particularly in thermal/gas power plants.
  • Water temperature–efficiency/loss: Investigation of density changes and seasonal performance differences.
  • Reservoir level–online ratio: Evaluation of start-stop behavior and operational constraints at low levels.
  • Oil pressure–alarm: Investigation of alarm threshold suitability and sensor drift.
  • Multiple turbines: Comparison of the behavior of multiple units on the same axes.
  • Wind power plants: Examination of wind speed–power relationships and cut-in, rated, and cut-out regions.
  • Solar power plants: Investigation of solar irradiance–DC/AC power relationships, panel soiling, and inverter losses.
  • Temperature–failure: Evaluation of the relationship between ambient temperature and failure frequency from a maintenance perspective.

EOS LIVE DASH data order: In the Scatter approach, the first data item entered can be treated as the independent variable on the X axis, while the subsequent data item or items can be treated as dependent variables on the Y axis. Therefore, data selection and ordering in report design is a design decision that directly affects chart interpretation.

4. ZoomScatter

ZoomScatter is an advanced use of the Scatter chart focused on zooming and detailed exploration. In SCADA and energy facilities that generate large volumes of data, it allows detailed examination of behavior within a selected small X–Y range without losing sight of the overall operating region.

How Does ZoomScatter Work?

  1. Overall data set: All points are displayed within the same X–Y coordinate system.
  2. Selection/zoom: The user selects a specific region or uses appropriate zooming actions to enter the critical operating range.
  3. Detail view: Points within the selected window are examined at a more detailed scale.
  4. Analysis: Micro-deviations, clusters, and outlier points can be investigated without disappearing into the overall chart.

Applications in HPPs

  • Flow rate–power micro-deviations: Zooming into a specific flow-rate range to investigate losses of several MW that appear normal on the overall chart.
  • Cavitation region: Examining vibration clustering within a specific head range in the net head–vibration relationship.
  • Part-load efficiency: Detailed investigation of efficiency degradation, for example within the 35–45% load band.
  • Resonance point: Detecting vibration bursts occurring within a very narrow RPM range on a speed–vibration chart.
  • Alarm threshold optimization: Identifying the value at which an alarm actually begins in a pressure–alarm intensity relationship and investigating false alarm thresholds.
  • Outlier forensic analysis: Providing a starting point for detailed investigation into whether a single point represents a sensor failure, a transient hydraulic event, or operator intervention.
  • Multi-unit comparison: Revealing differences between unit behaviors that overlap at normal scale but separate when zoomed in.

Key advantage: The value of ZoomScatter does not come merely from producing a “larger chart.” Its primary advantage is enabling a transition between overall behavior and micro-level behavior, allowing operators or engineers to examine a critical region independently of the complete data set.

A Practical Approach to Chart Selection

Chart Key Question Key Application
Area2D How strong or continuous is the effect created by the value over time? Generation, flow rate, reservoir, lost energy, and accumulation effects
SplineArea2D How can this trend be viewed more smoothly and with stronger physical continuity? Reservoir, flow rate, temperature, long-term generation, and stacked contributions
Scatter How does Y behave when X changes? Turbine characteristics, efficiency, vibration, load, and renewable performance
ZoomScatter Where is the critical micro-level behavior that is not visible in the overall chart? Narrow operating regions, micro-losses, resonance, alarm thresholds, and outlier analysis

EOS LIVE DASH design principle: Chart selection is not merely an aesthetic choice. It should consider whether the data represents a time series or an X–Y relationship, whether accumulation effects are important, how smoothly the physical trend should be represented, and whether small anomalous behaviors are critical for decision-making.

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