In the previous Energy Waste Sensei post, I, Sensei Bruce provided an overview of Global Adjustment (GA) and how classifications A (peak demand driven) and B (hourly consumption driven) dictate how you are charged. Knowing this will help us build upon our strategy of eliminating energy waste as you will learn today.
Data for 20/20 Vision on Your Energy Profile
How accurate is your data for starters? Are your measurement systems telling you what is really happening? Before any analytics can begin, we must ensure that there is a high-level of confidence in the data being retrieved. Verification of your data collection system is very important because it’s just as the saying goes, “garbage in, garbage out”. Bad data going in can only bring bad data out.
Breaking Down the Data to Uncover Insights
What do you know about your energy use? Well, for starters you probably know how much you’re paying, which is good. However, when we delve deeper into the analytics of your energy profile you can segregate the energy use into multiple categories. This lets you see beyond the aggregated data, which is important as it allows you to be able to identify misnomers, spikes, variation, and even trends! In our example in Figure A we have an idea that our total consumption is made up of lights, computers, elevators, cooling, etc.
Figure A: Example of Aggregated Electrical Consumption
Do you know where the energy waste is hiding? As we break down our energy profile we begin to see how your energy is allocated and we can identify our biggest consumer of electricity. This starts to tell a story about where the biggest charges of electricity come from. It is evident in this example that the cooling cost is more than 50% of the electrical energy profile and all other utilities make up the difference as shown in Figure B. We could break down all other utilities to further investigate that section if we wanted to and at CoEng Advisors we can do this for you with our unique analytic tool. However, there is no need since we already have a clear picture of where we need to focus.
Figure B: Energy Profile Segregated
Planning & Taking Action
How should you look at the data? As an Energy Waste Ninja in training remember: Always seek out the biggest piece of the pie first. But that’s not all, you must also monetize to identify which of the two groups has a higher savings opportunity.
Let’s fast-forward to having just completed an energy savings project. Do we simply hope that the savings are happening? The last time Sensei Bruce checked, hope wasn’t a plan! Energy Waste Ninjas know that after successfully implementing an energy savings project, monitoring and controlling our activities are key to ensuring that what we’ve invested in time and money are paying out dividend. Figure C represents the successful reduction of HVAC electrical use. You can see in this graph how we have identified the energy savings as illustrated by the green line.
Figure C: Energy Savings Identified
You can appreciate from Figure A compared to Figure C that there is a very different story being told. Which story do you prefer? As an Energy Waste Ninja, I know that Figure C must certainly be your favourite.
For all of the insights mentioned – good reliable data, segregation plan, monitoring and controlling, and reducing HVAC electrical consumption by as much as 30% – contact Sensei Bruce at CoEngAdvisors.com for details on how YOU can accomplish this success.
Next on Sensei Bruce’s BLOG: A look at how to get even more out of your analytics and shift your peak further through peak shifting strategies.