How Big Data Analytics builds Energy Efficiency

How Big Data Analytics builds Energy Efficiency

Saving energy has been a major concern since households and companies started consuming greater amounts of energy, especially in the form of electricity, the major fuel for most operations and processes performed on a daily basis.

However, a few things have changed along the years when it comes to using energy more efficiently and consciously. Indeed, there is greater awareness in regards to the impact of non-renewable sources of energy to the planet and in the emission of greenhouse gases.

The way we measure energy consumption also evolved a lot. This has led to the collection of huge amounts of data regarding different energy consumption variables, which are not always properly analysed, or used whatsoever.

Big Data and how it relates to Energy Efficiency

Big data is a major trend in modern businesses, as data has become the most important asset for many businesses, or at the very least, very important resources to count with for making better business decisions, predicting customer behaviours and many other useful techniques.

In order for everybody to stay on the same page, let’s clarify what does big data mean, and what does make it different to plain data. 

Big data is indeed a dataset, but one that exceeds a considerably large number of rows or registers, and that might be much more complex than smaller datasets as it also contains a greater amount of columns (variables).

More data means better insights, at least it does in theory, especially now that data analytics, data science and machine learning have grown, and continue to iterate over data models and algorithms, as well as to further develop better ones.

The areas of application of big data analytics are pretty much anything where some measurable data can be collected, which is pretty much any type of business, industry or area of knowledge. And one area that can get very benefited from large datasets is energy management.

Why? Because the way companies and households consume energy are very varied, and depends on a large amount of factors, including the energy provider, the sources of the energy, the amount of devices, the number of workers in a company, and a large etcetera.

And understanding the energy consumption habits of a company is the first and most important step in order to achieve energy efficiency.

This way, big data analytics and data management can go hand in hand towards the goal of reducing the amount of energy used without compromising the level of efficiency and productivity in a company or industry.

Collecting quality energy data

The sources of energy and electric power are not identical between two countries, and sometimes not even between cities in the same country. But this doesn’t mean that energy cannot be properly measured.

Many companies have developed different hardware and devices for collecting data from energy. For example, using smart meters to record energy consumption, either hourly or even more often. This leads to large amounts of data being collected, hence, big data.

There are also energy management software – as DEXMA Platform – that offer complete solutions to actually detect, analyse and optimise energy consumptions and identify energy savings potential.

The way in which companies collect energy data depends to a large degree on subjective criteria, often decided by a Data Manager, who knows the way energy flows throughout the company, and how it affects different operations.

There are many factors that affect the way a company collects the energy and electrical consumption data. On one hand, two companies might need electricity for two completely different reasons; but, on the other, where a company is located affects the price of energy.

One common variable for most companies around the world is precisely how much they need to pay on a monthly or yearly basis in order to cover their current energy usage. Too large bills from the energy provider are often the first trigger of a company to start implementing energy efficiency projects.

From this initial awareness, asking the right questions is the best way to model appropriate and effective energy consumption data. For example, what are the goals of the organisation by reducing the energy used? Is it to reduce the expenses? Is it to positively contribute to the environment? You can also read our article about “Corporate Social Responsibility: Towards Sustainability & Energy Efficiency in Business Strategy” for more information.

energy data quality management

Getting insights from energy data

Having collected the appropriate data based on the variables and subjective factors that were considered by members of the organisation, as well as an Energy Manager; the following step is to get valuable insights that can help to achieve energy efficiency.

What is a valuable insight when it comes to big data analytics focused on energy consumption will greatly depend on the specific goals of the company. But in general, it is highly recommended to get answers on where and why the company consumes such an amount of energy.

For a business focused on manufacturing, there might be irregular cases of two machines that are exactly the same, doing the exact same work for an equal amount of time, and yet, data might throw that one of them is consuming more energy.

In such a case, finding out what is the origin of this irregularity is highly desirable, since, in order to properly reduce the amount of energy consumed in a certain operation, it is first necessary to normalise the output among devices, machines and processes.

The energy consumption habits from employees and members of a company or business are also variables that can be quantified, and from where a lot of value can be extracted in the form of insights, which can then allow to design plans and campaigns to reduce the usage of energy.

Finally, finding realistic ways of reducing energy consumption of a company during the performance of the different operations that comprise its economic activities, is the most useful way of obtaining valuable insight from the energy dataset.

The scalability of energy analytics

Applying changes on the way the company uses energy and resources also implies the necessity of preserving a short, medium and long term vision that allows to ensure that energy consumption will remain efficient without hindering the company’s growth.

This might seem especially easy for small businesses, maybe those on the startup phase; as well as those in the service sector, which can have an easier time collecting data energy and successfully reducing their consumption of energy.

But large companies and manufacturers also need to look forward, as they might grow or diversify in the future. This foresight makes it necessary to implement scalable energy efficiency projects from the outset, so that they can continue to save on their bills and thus devote the money saved to developing other growth-focused activities.

Big data analytics has unlocked many possibilities that used to be overlooked a bit more than a decade ago. Among these possibilities, improving the way businesses use energy in order to achieve energy efficiency, and move from there towards sustainability. This means a huge transformation in the company’s culture and values. A change that nowadays, many companies are looking forward to implementing.

DEXMA Energy Management Tools