In recent years, the energy sector is undergoing major changes to accelerate the energy transition and to achieve a much more sustainable future, from a greater implementation of renewable energy, smart grids or electric mobility among others to achieve greater energy efficiency in companies.
In order to achieve this, the National Integrated Energy and Climate Plan (PNIEC 2021 - 2030) has set quite ambitious goals, including a substantial improvement of 39.5% in energy efficiency . Given this scenario, Artificial Intelligence becomes the best ally in driving the energy transition, helping to decarbonize the economy and make more efficient use of available resources.
Throughout this post, we will analyze what can be done by organizations to help achieve this goal and how they can increase energy efficiency in companies through the use of new technologies such as Artificial Intelligence.
What is energy efficiency in companies?
We can define energy efficiency in companies as obtaining the same goods and services for the organization, but in a way that optimizes the energy consumption used to produce them.
This optimization of consumption in turn generates a higher percentage of savings, both energy and economic, which contributes to continue investing in new energy efficiency actions.
Benefits of energy efficiency in companies
Improving energy efficiency has a number of long-term benefits for businesses:
- Minimizes environmental impact.
- Reduces costs and helps achieve a higher return on investment (ROI)
- Optimizes installations and improves the performance of equipment with an increase in its useful life.
- Helps to increase the productivity and global competitiveness of the organization.
Approximately 75% of the buildings that make up the European Union are estimated to be energy inefficient" - Pau Garcia, policy officer at the European Commission.
Efficient energy use: How can AI help companies?
Before going into detail about specific applications of AI in the field of energy efficiency in companies, let us describe very briefly and simply what this technology consists of:
Through advanced AI algorithms, machines are given the capacity to simulate human intelligence, being able to learn and reason on their own. All this makes it possible to comprehensively understand the large amount of data generated in the organization and automatically extract value from it. Some of its benefits are:
- Time savings in repetitive tasks, thanks to process automation.
- Greater control and accuracy of data, minimizing human error.
- It lowers the organization's operating costs and contributes to increased operational efficiency.
- Improved decision making
"Seventy-nine percent of managers believe they can be much more efficient if they are supported by AI."
Source: Artificial Intelligence in the real world - The Economist
Now that we have seen why it is necessary to promote energy efficiency in companies and how AI helps to achieve it, we are going to provide a series of measures that can be applied in a practical way in organizations with the support of an AI-based energy management system.
Energy efficiency measures in companies with IA
Throughout our history, we have encountered many companies that want to start becoming more efficient, but face some barriers to get started.
The first step to start implementing energy efficiency actions in companies is to know what is happening with the organization's energy consumption and identify areas for improvement. However, sometimes a good measurement infrastructure is not available or it is not known how to extract value from the data obtained.
In this section, we will analyze how AI solves many of these problems and what measures can be taken to address them.
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Reconstruction of consumption curves:
AI helps to obtain virtual consumption curves in the absence of data or when only the generic consumption shown on the bill is available.
Obtaining the load curve provides more detailed knowledge of how energy is consumed in the organization, which facilitates the implementation of saving measures such as adjustments in the contracted power, being able to solve errors in the energy bill or even modify the schedules of use of the equipment of an installation to be more efficient.
The energy management platform SMARKIA generates quarter-hourly load curves with an accuracy of close to 90% based on information from the invoice.
Virtual submetering:
Virtual submetering is performed thanks to NILM technology or non-intrusive load monitoring. This technology is used to disaggregate energy consumption and to know the consumption of each device individually.
This type of technology is especially useful in multi-site environment projects that have a low metering infrastructure. Let's see it with a small example:
Suppose we have the general consumption of a bank with 1,000 offices. From this consumption, a minimum installation of field equipment is made, generally between 2 and 5% of the total infrastructure. In our example, we would be talking about installing around 50 meters to be able to infer the remaining 950 with IA.
Thanks to virtual submetering, we are able to considerably reduce the cost of metering infrastructure, thus:
- Reduces the implementation time of the energy efficiency project.
- Savings are generated much faster.
- They considerably increase the payback of the investment.
Once the savings achieved have been demonstrated, it is possible to deploy the actual metering infrastructure and invest in further energy efficiency actions in companies.
3. Anomaly detection:
Using advanced AI algorithms, we can observe whether the company's energy consumption is adequate or not. If there is any anomaly, the algorithms will automatically detect where it is and why it has occurred, as well as the impact this will have on the company.
In many cases, companies have platforms that allow them to configure, in a static way, different alerts based on the setting of a reference threshold. However, these systems will never detect if at a given moment that consumption is higher than usual, missing opportunities for savings and being more inefficient.
Some of the benefits our customers have found when using SMARKIA to detect anomalies are:
- Forecast much more accurately and adequately.
- Greater operational control and time reduction, as the platform itself notifies the personnel in charge of maintenance tasks.
- Reduction of emergency stops in production lines.
- Considerable cost savings.
4. Benchmarking and gamification strategies:
First of all, we will briefly describe what benchmarking and gamification applied to energy efficiency in companies consist of:
- Benchmarking: This consists of analyzing the errors and successes that take place at other company sites in order to extract ideas that serve as a reference point for improvement.
- Gamification: Methodology that applies game techniques in non-game environments. Applied to the field of energy management, it helps those responsible for maintenance and energy efficiency to be aware of whether the consumption of their buildings is within the average, helping them to improve and modify their behavior to be more efficient.
These terms are very fashionable nowadays, but we need a technology behind them to help us apply them correctly .
Sometimes, many users who start using an energy management system end up abandoning the process because they do not know how to take advantage of its full potential. By applying benchmarking and gamification techniques, the company's sites "compete" against each other, making it easier to learn what actions are taken in each of them and encouraging users to exploit the full potential of their energy management systems. By feeling that they are competing with each other, a considerable improvement in the energy performance of all buildings is observed.
At SMARKIA, we have observed how the use of gamification strategies can generate potential savings of close to 10%.
5. Detection of energy saving opportunities:
Thanks to the application of AI, automatic energy efficiency improvement opportunities are detected in companies through predictive models. In this way, the full energy saving potential of the organization can be exploited by obtaining personalized recommendations.
6. Remote management of installations:
Compared to a traditional BMS or SCADA system, a remote management system allows remote control of installations and autonomous adjustments. If we also rely on AI technology, all these processes will be optimized automatically:
The use of traditional BMS or SCADA systems means that a great deal of time is wasted interpreting volumes of data in order to operate the equipment. In addition, more and more companies have less and less personnel dedicated to maintenance tasks.
Through AI, it automatically detects potential improvements and operates on the equipment itself to modify it, with the aim of achieving a higher percentage of energy savings. Let's take a closer look with a graph:
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In the previous graph, we can see how by installing a control system we can achieve, at first, savings close to 20%. However, these savings are lost over time, as the system begins to become obsolete. In the green line we can see how an optimized control system maintained over time is capable of generating savings of up to 30%, although this amount of savings remains stable over time.
A control system to which Artificial Intelligence is applied can generate savings of up to 30%.
7. Business Intelligence:
Business intelligence aims to help energy efficiency projects get implemented much faster, helping to accelerate the energy transition. To do this, the use of AI helps to detect when it is the perfect time to offer an improvement to customers and show them a certain service, thus accelerating time-to-market.
Final conclusions:
Throughout this post, we have been able to see and analyze the importance of investing in energy efficiency in organizations, its benefits and how, thanks to the support of Artificial Intelligence, we contribute to accelerate the energy transition to achieve the objectives proposed by the PNIEC.
In SMARKIA we have seen how large organizations with numerous sites (shopping malls, hotels, hospitals, factories, etc.) have considerably improved their energy efficiency thanks to the support of an Artificial Intelligence based energy management system. You can get more information by contacting our team or get a DEMO of the platform through the following link: Smarkia | Contact
