Edge computing plays a key role in sustainability and energy efficiency because it is specifically designed to bring applications and data closer to devices and their users. Increasing the deployment of edge solutions could be one of the answers to achieve the energy optimization goal that the industry is looking for.
Industrial prices have soared by almost 50% in the midst of the energy 'rally'. Rising gas, fuel and electricity prices have driven production prices to almost two consecutive years of uninterrupted increases.
The effects of the energy crisis have hit the industrial economy hard in 2021-22. During this period, industrial prices soared by 41.8% compared to the previous year. The data published by the National Statistics Institute (INE) show how industrial prices have chained almost 2 consecutive years upwards.
The intensive use of energy products has left industrial companies highly exposed to the impact of the current energy crisis. The main consequence of this impact has been the pass-through to industrial production prices. Thus, the industrial price index (IPRI), which is compiled by the INE, recorded an incremental variation of 10% in 2021 (the highest figure since 1985).
The collection and exploitation of data in industrial plants with new IoT technologies opens up a new avenue for process optimization, including energy efficiency. The birth of IoT has meant that organizations are dealing with more data-intensive technologies and devices than ever before, which not only enable the pursuit of new business opportunities, but also operational (including energy) efficiency.
As digital consumption of data increases in the Industry, your workloads are moving to the edge of the network in locations outside of the physical IT infrastructure. With that migration of resources comes the challenge of ensuring that data always remains accessible in a sustainable manner.
Edge computing plays a key role in sustainability and energy efficiency because it is specifically designed to bring applications and data closer to devices and their users. This helps organizations better react to changing consumer demands and improve processes to create more sustainable products.
This includes helping organizations to digitize their manufacturing processes by using data to generate real-time feedback and alerts to increase efficiency throughout their supply chain, including reducing energy costs and carbon emissions.
Edge computing is presented as a perfect solution to solve some of the serious energy cost problems faced by industrial companies. Increasing the deployment of edge solutions could be one of the answers to reach the energy optimization goal that the industry is looking for.
Beyond the energy efficiency solutions that can be deployed at the Edge, the edge systems themselves have some inherent features in their architecture that can help lower the carbon footprint and optimize energy use:
With the advent of edge computing, more efficient management of computing systems (essential in this new data economy) is possible, for example, by making resources "idle" when they are not needed. The orchestration and management of a distributed set of (smaller) data centers allows computing resources (and therefore energy) to be used efficiently.
Edge smart solutions can also help different types of companies to solve their energy efficiency needs through real-time sensors and take preventive measures in the network. Among the most relevant smart applications are:
Application of demand prediction and optimization through algorithms for energy management by monitoring the network with real-time sensors. Edge Computing makes it possible to execute energy flexibility processes wherever energy is generated or consumed, and to adapt demand to generation possibilities.
Small power generation 'power plants' are beginning to emerge in industrial centers, altering the balance of supply and demand. Thus the need arises to manage a large number of distributed elements of power generation and storage, to optimize the distribution and distribution of energy. Edge Computing facilitates an intelligent management of all these assets and makes it possible to treat all of them in an aggregated manner under the figure of "Virtual Power Plants".
The development of artificial intelligence algorithms in the Edge makes it possible to detect possible fraud and leaks in the consumption of the low-voltage network. The consumption of electrical energy through illegal connections to the grid means an unplanned increase in demand that can cause large losses to companies.
Thanks to the virtualization of infrastructures through Edge nodes, it is possible to reduce their physical space and consumption requirements.
The rise of Edge Computing as one of the enabling technologies in the digital transformation of the industrial sector is undeniable. Now it also represents an oxygen balloon in the difficult energy situation in which organizations around the world are immersed.
The introduction of a dynamic AI model supported by edge computing technology in today's industrial environments can significantly reduce energy use, reducing carbon emissions and initiating a drop in energy costs within a few months.
Looking for ways to reduce energy use is not new to the industry, but creating scalable ways to do so is.
Most of today's equipment is not operating at optimal levels, so significant energy savings can be achieved. Optimizing performance is critical to reducing energy use and increasing sustainability in an industrial environment.
Those companies that develop the capabilities to connect devices and efficiently collect and exploit real-time data will undoubtedly play a leading role in the Industry 5.0 of the future.
At Barbara, we are already deploying Edge Gateways at different points of industrial operations, which allow not only energy optimization in industrial infrastructures, but also the deployment of AI applications that automate business decisions, thus relieving pressure on operators. All this with a cybersecurity layer that makes the solution scalable and certifiable in an environment as demanding as the industrial one.
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