You may have heard of the term Big Data before. Perhaps you’re wondering what it’s about or how it can be useful. If this is the case, you have come to the right place. In a few words, big data is what we call the large volume of data –both structured and unstructured– that inundates a business on a day-to-day basis.
The amount of data that enters a server is in fact enormous. Can you imagine, for example, a group of buildings equipped with 1,000 sensors which are constantly providing information about lighting every few minutes? That’s a lot of data!
Also, data usually comes in all types of formats. Both for this reason and because of its large volumes, is why arranging data is of utmost importance in order to facilitate its management.
Data by itself is not enough
When you combine big data with high-powered analytics, you can determine causes of failures and defects. Nevertheless, data analysis requires insight. You have to know that understanding won’t just hit you.
If you want good answers, you must ask good questions.
Here are some technologies which come in handy if you want to make the most of big data:
- Cheap and abundant storage
- Fast processors
- Affordable open source and distributed big data platforms
- Cloud computing and other flexible resource allocation arrangements
- Good BI software
Big data’s role in Energy Management
Broadly, data is what allows us to see how buildings operate since it provides valuable information about them. For example, it is quite useful to know the times when people turn the lights off prior to leaving a building. If they usually go out at 9:00 p.m. then at 9:15 p.m. it should be expected to not have any lights turned on and wasting energy.
Comprehensive energy management is possible only when the appropriate information is recorded during the process and provided in a processed form. Likewise, the transparent display of such results helps create awareness among personnel as well as better consideration about energy.
Caution: Hot Ovens!
In a recent case, a project of energy efficiency was enforced in several bakeries. Up to now, workers were used to turning ovens on at 7:00 a.m. and letting it stay on until 9:00 p.m. All those hours meant spending a lot of energy and even wasting it. The goal of the program was to lower energy supply to reduce such peaks without affecting sales.
Throughout five years, data was collected from the bakeries’ cash registers. This showed the times when certain products were purchased. For example, on a cold winter Monday customers would buy fresh baguettes first thing in the morning. Then there would come a period of many hours with not many sales. Then, more people would come after work or school to buy bread.
Big data and importance of calculations
Of course all shops have different peaks because of the habits of their clientele, but you get the point. To be able to see these highs and lows would allow us to make calculations which lead to important decisions. One of these would be switching off specific equipment (such as ovens) at certain hours of the day and therefore cutting use of electricity.
Timers can be set individually to each oven to automatically turn them off when the hour of the lowest peak comes. Accordingly, if it’s needed for some specific occasions of unexpected high peaks, this setting can be modified. It may sound a bit tricky but the ultimate goal is to facilitate the bakers’ work and, at the same time, to save as much energy as possible.
Nevertheless, there are some cases in which consumption of bread was so evenly spread during the day that we would be switching the ovens on and off many times for such a small period of time. Since doing this required a lot of energy, we would not get the effect we were looking for.
Why energy consulting is absolutely crucial
This is why energy consulting is crucial in such a project. An experienced energy consultant will consider the data results. Based on the people’s needs (bakers, workers or inhabitants) and the energy management processes that are going on, decide what the best way to go is.