Designing an Energy Management Dashboard that Drives ROI
Illustration: © IoT For All

Energy management in the lighting industry is an area ripe for innovation. Many companies are looking for ways to decrease energy consumption, improve sustainability, and reduce operational costs. Modern technology is increasingly enabling the achievement of these goals through interactive, data-centric dashboards Let’s explore how to design these energy management dashboards to glean actionable insights and ensure a robust ROI.

Step #1: Understand Your Objectives & Play with the “Art of the Possible”

Before diving into creating an energy management dashboard, it’s crucial to clearly define your objectives. The objectives can vary, from reducing energy consumption to maintaining regulatory compliance or improving cost-effectiveness.

Understanding goals guides data collection and determines the insights your dashboard should provide. Ask the following questions:

How does the data need to be consumed by a user?

  1. At what frequency will a user typically engage with the dashboard and the data it presents?
  2.  Does a user need to see every data point? Or does a user need to see a change?
  3.  What thresholds in changing data need a user’s attention now, tomorrow, next week, etc., and what methods are needed to engage the user for each?
  4.  Ex. Realtime notifications vs time window summaries?
  5.  What notification methods do this dashboard’s personas require (i.e., SMS, in-app, push, email, lights on a sensor or machine, etc.)

How can the data being produced become insightful through the presentation of data?

  1. What are the most actionable insights that need to be designed so your users can spend less time analyzing and more time acting?
  2.  Is data being tagged so it may be utilized in an ML model?
  3.  What visualization is appropriate for the user’s needs? And what affordances are appropriate?

What is possible for ML/AI and an anomaly detection system?

  1. Constant streams of data may require attention to detail to catch something through simple observation. If a data pipeline is mature enough, data can be tagged, and visualized, and users may be notified of critical conditions in their systems.
  2.  How is data being tagged?
  3.  Are there mechanisms for users to engage in supervised learning?
  4.  Is data being processed on the edge, in the cloud, or on the front end?

At what phase of data maturity is this system, and what capabilities are possible today vs near future vs far future?

Machine learning and artificial intelligence advancements have opened doors to predictive analytics in energy management. Your dashboard design could include features that predict future energy usage based on historical data and identified patterns.

Especially useful for planning, budgeting, and early identification of potential issues before they escalate:

  1. Descriptive: what happened?
  2. Diagnostic: why did it happen?
  3. Predictive: what will happen?
  4. Prescriptive: how do we make it happen?

Step #2: Gather and Integrate Relevant Data

Harnessing the power of data is an essential aspect of any energy management dashboard. Incorporating comprehensive data transforms your dashboard from a monitor to a platform for in-depth analysis and strategic decision-making.

In the lighting industry, the universe of data is vast. An effective energy management dashboard integrates diverse data streams for an understanding of your energy landscape.

Power Consumption Data

At its core, an energy management dashboard must monitor the power consumption of various lighting fixtures. This includes different types of lights, such as LED, halogen, and fluorescent bulbs, each of which has different energy requirements. Smart meters or integrated sensors within the lighting fixtures themselves could collect this data.

Runtime Hours

Another crucial piece of data is the runtime hours of each lighting fixture. By tracking how long each type of light is on, you can better understand usage patterns and identify opportunities for energy savings. Intelligent lighting control systems that monitor the on/off status of each fixture could collect this data.

Occupancy Patterns

Incorporating occupancy sensors into your data collection strategy can provide insights into when and where lighting is necessary. By understanding when spaces are occupied, you can optimize lighting schedules and even integrate automated controls to turn lights off when areas are unoccupied, enhancing energy efficiency.

Environmental Factors

Ambient light levels, influenced by factors such as time of day, weather conditions, and even the season, also play a role in lighting needs. Additionally, light sensor data and weather forecasts inform daylight harvesting, adjusting artificial light levels based on available natural light.

Additional Data Sources

Beyond these core data points, you must also consider other relevant information that could enhance your understanding of your energy usage. This could include data from HVAC systems, which can affect lighting needs, or occupancy comfort surveys, which can provide user feedback on lighting levels.

The next vital step after gathering this rich set of data is integration. The most effective energy management dashboards are those that can pull together data from different sources into one easy-to-use platform. This may involve integrating data from various types of sensors, databases, third-party systems, and even IoT devices.

For instance, you might combine occupancy data from IoT sensors with power consumption data from your facility’s smart meter system. You could also incorporate data from third-party weather services to provide real-time information on daylight hours, enhancing your ability to implement daylight harvesting strategies.

Data integration often involves advanced data processing techniques to ensure compatibility between data types and sources. This could also include data cleaning to remove errors, data transformation to convert data into a uniform format, and data visualization to present the data in an accessible, understandable way.

Step #3: Design Dashboards for Actionability

Effective dashboard design presents data in a format that supports decision-making, making it easily digestible. Utilize visual elements like charts, graphs, and color-coded indicators to highlight key metrics and trends.

An effective dashboard should demonstrate the business ROI of energy management efforts by showcasing metrics such as energy cost savings, reductions in CO2 emissions, and improvements in operational efficiency.

Dashboards also need to showcase the financial impact of energy management strategies by illustrating the return on investment (ROI) for the business.

This might include metrics like energy cost savings, reductions in CO2 emissions (which can translate into regulatory credits), and improvements in operational efficiency. By quantifying these benefits, you can show stakeholders the tangible value of your energy management strategies.

Energy management dashboards are essential for driving efficiency, sustainability, and business ROI in the lighting industry. Therefore, by gathering and integrating relevant data, designing for actionability, including predictive analytics, and demonstrating business ROI, your dashboard can become a powerful tool for informed decision-making and strategic planning.

In this way, we can shine a light on the path toward a more sustainable and cost-effective future.

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