EOS LIVE DASH Chart Types

The chart types used in EOS LIVE DASH provide different visualization approaches according to the nature of the data and the type of analysis required, rather than presenting the same data in a single way. This section covers charts that can be used for direction and regime changes, time-series trends, category comparisons, and wide value ranges.

Important: The charts below are representative SVG visualizations created to explain how the corresponding chart types work. The values shown in the charts are not actual plant data; they are provided only as examples to support visual explanation.

1. Kagi

The Kagi chart, unlike conventional time-series charts, focuses on the direction, magnitude, and regime changes of values rather than time, and operates based on a reversal threshold. Although it originated in the financial world, when properly adapted it can become a powerful tool for direction and regime-change analysis in SCADA, power generation, and process monitoring applications.

Basic Operating Principle

  1. Direction-oriented plotting: The line moves upward when the value increases and downward when it decreases.
  2. Reversal threshold: If the value changes in the opposite direction by more than a defined absolute or percentage threshold, a new direction is initiated.
  3. Noise filtering: Small fluctuations are not plotted; only meaningful movements are displayed.
  4. Breaking an extreme: Moving above the previous high or below the previous low can determine whether the direction strengthens and the line behavior changes.

Applications in SCADA and Energy Systems

  • Power generation: Highlighting load pickup, load rejection, and operational regime changes in MW values.
  • Hydroelectric power plants: Monitoring meaningful direction changes in indicators such as reservoir level, turbine power, flow rate, vibration, water consumption, and alarm intensity.
  • Thermal power plants: Evaluating regime changes during boiler pressure and turbine loading/unloading phases.
  • Equipment health: Detecting persistent deterioration trends in vibration or other health indicators rather than isolated sudden spikes.

Example: If a ±2 MW reversal threshold is defined for turbine active power, small fluctuations such as 48–49–50–49 MW do not produce a visible direction change. Once the meaningful threshold is exceeded, load pickup or load rejection behavior becomes prominent.

When Is Kagi Particularly Valuable?

  • When small fluctuations need to be filtered from noisy sensor data.
  • When the direction of a long-term trend needs to be evaluated.
  • When regime or operational phase changes need to be identified.
  • When the question “In which direction?” is more important than “When?”.

2. Column3D

Column3D (3D Column) is a visually prominent chart type used to emphasize differences in magnitude and comparison among categorical or time-based data. It is particularly suitable for executive dashboards, presentations, and summary reports.

Column3D adds depth (Z dimension) and a perspective effect to the classic Column chart. The Z dimension does not carry an additional measurement here; instead, it creates a visual sense of depth and volume.

  • X axis: Categories or time periods.
  • Y axis: Measured value; for example, MWh, alarm count, or %.
  • Z dimension: Visual depth; it does not represent additional data.

Applications in SCADA and Energy Systems

  • Hourly, daily, or monthly generation comparisons.
  • Presentation of generation performance among units.
  • Comparison of alarm counts by location, group, level, or type.
  • Summary of turbine-based generation, downtime, and failure types.
  • Comparison of planned and actual generation on executive dashboards.
  • Visual presentation of efficiency, heat rate, and emission indicators.

Design note: Column3D is oriented more toward presentation and visual communication than detailed analysis. For precise numerical comparisons, 2D charts generally provide a more reliable visual reading.

3. Column2D

Column2D (2D Column) is one of the fundamental chart types used to compare categorical or periodic data clearly, accurately, and directly. Since it does not introduce perspective or 3D visual distortion, it is a strong choice for SCADA, power generation, and performance reports where analytical accuracy is a priority.

  • X axis: Hour, day, month, alarm type, or other categories.
  • Y axis: MWh, alarm count, percentage, or the relevant measurement.

Applications in SCADA and Energy Systems

  • Hourly, daily, and monthly generation (MWh).
  • Generation comparison by unit.
  • Numerical comparisons by alarm type.
  • Daily/monthly generation and downtime by turbine.
  • Hourly power distribution and annual energy generation.
  • Planned–actual generation comparison.
  • Generation by flow-rate or reservoir-level bands.
  • Comparison of fuel/source, efficiency, and emission indicators.

4. LogColumn2D

LogColumn2D (Logarithmic 2D Column) is a specialized variant of the classic Column2D chart in which the Y axis uses a logarithmic scale. It makes comparisons more meaningful when values span a very wide range and small but critical differences are hidden on a linear scale.

  • X axis: Categories such as seconds, hours, alarm type, alarm group, equipment, etc.
  • Y axis: Logarithmic scale such as 10⁰, 10¹, 10², 10³.

Applications in SCADA and Energy Systems

  • Harmonic levels (THD %).
  • Leakage current values (mA → A).
  • Short-circuit current levels.
  • Lost energy across a wide range according to failure type.
  • Comparison of unit downtime across very different durations.
  • Auxiliary system energy consumption.
  • Joint evaluation of rare and frequent events in alarm/event counts.
  • Comparison of flow loss–duration and generation losses across a wide range in HPPs.

Appropriate use: When values differ by approximately 10×–1000× and small values are also important for decision-making, LogColumn2D is particularly meaningful on analysis and engineering screens.

5. Bar3D

Bar3D (3D Horizontal Bar) presents categorical data using horizontal bars with a 3D perspective effect. It can be considered the horizontal counterpart of Column3D. It is particularly useful on executive dashboards where ranking, comparison, and visual emphasis are required.

  • Y axis: Categories; unit, region, equipment, day, or alarm group.
  • X axis: Measured value; MWh, alarm count, or %.
  • Z dimension: Visual depth; it does not carry additional data.

When Is It Preferred?

  • When category names are long.
  • When ranking from highest to lowest is required.
  • When visual impact is important.
  • When executive and presentation screens are being prepared.

Applications in SCADA and Energy Systems

  • Hourly, daily, and monthly generation comparisons.
  • Comparison of generation and alarm counts by unit.
  • Turbine downtime and failure types.
  • Generation by flow-rate groups or reservoir-level bands.
  • Fuel/source, efficiency, and emission comparisons.

6. Bar2D

Bar2D (2D Horizontal Bar) is a simple and reliable chart type used to present categorical data with high readability and analytical accuracy. It is particularly effective in SCADA and energy reports where category names are long and ranking is important.

  • Y axis: Categories; hourly, daily, monthly generation, or equipment-based alarms.
  • X axis: Measured value; MWh, alarm count, hours, or %.

Applications in SCADA and Energy Systems

  • Hourly, daily, and monthly generation.
  • Generation comparison by unit.
  • Comparison by alarm type.
  • Turbine-based generation, power distribution, and downtime.
  • Downtime by failure type.
  • Generation by flow-rate groups and reservoir-level bands.
  • Fuel/source, efficiency, and emission comparisons.

Strengths of Bar2D

  • Clear comparison: Differences in bar length are perceived quickly.
  • Ranking support: Best and worst performance can be identified easily.
  • Reduced misleading effects: Since there is no perspective or 3D effect, numerical comparison is more direct.

A Practical Approach to Chart Selection

Chart Main Purpose Key Application
Kagi Direction and regime change Noise filtering, direction analysis of load pickup/rejection
Column3D Visual emphasis and presentation Executive dashboards, summary reports
Column2D Direct numerical comparison Generation, alarm, and performance reports
LogColumn2D Comparison across wide value ranges Analysis/engineering screens, rare and frequent events
Bar3D Horizontal ranking and visual emphasis Long category names and presentation screens
Bar2D Clear ranking and analytical comparison Performance, alarm, and generation rankings

EOS LIVE DASH design approach: The chart type should not be selected solely according to visual preference. The selection should also consider whether the data is a time series, the width of the value range, the importance of direction changes, the length of category names, and whether the screen will be used primarily for analysis or presentation.

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