Attention. Energy distribution grids are now under high voltage. Smart energy allocation runs the wires.
The demand for smart energy grids and energy monitoring software is on the rise. Energy consumers large and small are demanding energy distribution based on their needs. One-size-fits-all is no longer acceptable. But how can an energy distributor determine how much energy a school needs versus a factory in order to distribute energy as efficiently as possible? To figure this out, an energy distributor needs to rely on consumption standards of energy monitoring software for different types of buildings.
One of our clients, a Belgian company that appears on Deloitte’s Technology Fast 50 list, approached us with an ambitious goal to extend its global reach with new locations in the United States, Canada, and France that would serve 1.5 million users. Part of our solution was to improve our client’s integrated workplace management system, but first we needed to validate our smart energy distribution concept in the real world. To this end, we needed to define an energy consumption standard for a facility type of our choice. We chose local schools as the playground for our experiment.
We collected data about energy consumption patterns of local schools
As a starting point, we gathered measurements for five public schools located in the same district to ensure similar utility services, weather, and geo-conditions. Next, we modeled the hierarchy of utility meters in our energy management system. Then we entered measurements for energy consumed between 2012 and 2014.
Figure 1. Hierarchy of utility meters
After obtaining measurements from the utility meters, it was critical that we analyzed the data correctly.
When we look at the data from the utility meter, we see only bold numbers. Even if records are high, we don’t know the cause of the elevated energy usage. To understand consumption patterns, we need to rely on more comprehensive calculations. We should use data for normalized degree days, consider working hours, and on-premise people during facility operation. It is very important to ensure comparison of adequate data to build accurate benchmarks.
We analyzed specific metrics to establish commodity benchmarks
Our energy monitoring software provided us with calculating algorithms for all necessary correlations. We calculated energy use per square meter, normalized weather-related consumption patterns, and defined periods of peak load. The resulting metrics gave us more accurate and comprehensive insights into energy consumption patterns. As an example, you can see how these five different schools used electricity over the period for which we collected measurements.
Figure 2. Analysis of electricity consumption across five schools
As we can see, School No. 30 had a much higher consumption rate than the four other schools. This means that School No. 30 should be targeted for an energy saving strategy. At the same time, the four other schools had relatively similar consumption rates. We used these schools for our electricity consumption benchmark. We then applied the same approach to other commodities to establish benchmarks for each type.
Figure 3. Energy consumption benchmarks
We unified benchmarks into one consumption standard for schools
With all the data at hand, we were able to establish a reasonable energy consumption standard for schools as an examined facility type. We developed a district standard based on four schools, excepting School No. 30, which was targeted for improvements. The energy management system that our client developed provides flexibility to account for additional information, thereby justifying higher or lower energy needs in practice and guaranteeing that the standard doesn’t harm normal building operations. Energy distribution companies can use industry standards for energy consumption to:
- Understand end-user energy demands
- Optimize pricing strategies based on energy consumption patterns
- Maximize energy savings to reduce costs and protect the environment
- Create a strategy for more efficient use of alternative energy sources
A brighter future at lower cost
Projecting further, standards for different building types and industries can serve as a basis for government institutions to introduce energy policies for entire states.
The benefits from these standards are far-reaching. If we collect data on consumption patterns for the last 30 years, it’s possible to reach a government level to change energy distribution for a smart grid nationwide.
At the time of launch, our client had the following goals:
- Collect, store, and analyze up to 50,000 data points per second
- Realize a 50% drop in short-term peak loads and a 15% drop in overall peak loads across the user base
- Reduce electricity bills by 10%
- Obtain enough data for demand-based planning and benchmarking
- Improve meter infrastructure to provide a real-time, integrated view of the grid
- Predict ROI for energy distribution projects
This energy management solution is currently the most advanced on the market because of its wide user base and the unparalleled amount of data it collects. The energy distribution perspective here is fired up to shine brightly. By moving away from blind allocation of resources to smart distribution, energy distributors can earn customer loyalty and compete for lion’s share on the power market.
If sustainable energy management is a priority for you, please contact our experts to discuss how we might lend some expertise. If you’re looking for more real-world examples of our experience in building energy management applications, you can find other related projects here.