With the increased number of distributed energy resources DERs onto the grid, energy operators need a predictive system based on consumption and production patterns to help them avoid congestion and overvoltage events in the grid. In this article, we cover a specific project we are running under the i-nergy programme, an EU-funded initiative aiming to support and develop new AI-based Energy Services.
The main goal of virtualization is to provide a new operational environment, which is not bound to any computer hardware or operating system. Hardware components are typically designed to be robust and reliable, but they can also be expensive and difficult to modify or upgrade. Separating hardware from software allows for the software to be updated or modified without affecting the hardware.
Gartner's Emerging Technologies and Trends Impact Radar shows IT leaders where to capitalize on market opportunities. Its latest feature for 2023 points to EDGE AI as the next breakthrough technology. With the growing demand for real-time AI solutions and the need for decentralized data processing, AI at the Edge has been positioned as a critical technology this year.
Companies are increasingly interested in virtualizing electrical equipment because it offers a range of benefits for their operations. Firstly, virtualization reduces the need for physical infrastructure, which can result in cost savings, reduced maintenance requirements, and increased safety. In this article, we talk about the benefits of separating hardware and software in Substations.
Supported by the Basque Energy Cluster and Innovasturias, the I+CCM project that stands for "Intelligent Engine Control Centre" aims to develop a solution to equip the switchboards that make up an electrical system with intelligence and interaction capacity via Industrial IoT.
This year, STL Partners asked companies to provide more information on their financial milestones associated with edge computing, as well as for details on the practicalities of edge applications that they are enabling. By doing so, the firm was able to chart the increase in maturity of edge offerings, with more companies seeing significant revenue streams coming from their edge portfolio.
To operate more efficiently, water management operators face the challenge to monitor in a unified and comprehensive way all components that make up the OT and industrial automation architectures. The use of Edge Nodes allows connectivity with different equipment in each installation regardless of the various data reporting equipment. Discover how utility companies can access sophisticated intelligence to support water operators using Edge Computing.
How can the water industry benefit from IoT Edge and AI? IoT is one of the technologies that has made a strong entry into the water industry, developing solutions rich in monitoring, analytical, and automation features. Meanwhile, Artificial intelligence (AI) is making its mark on the water industry, powering intelligent operations using machine learning to optimize resource use and operational budgets for organizations.
In IoT deployments, it is common to hear the term Edge. Many IoT solution vendors, especially in the industrial environment, acknowledge the capabilities of the Edge to generate business value. But what is IoT Edge and what is its relationship with Edge Computing?
Industry at the Edge by Barbara is an annual event directed to the community of professionals, startups and corporations around technological innovation in the industry. In a horizon of uncertainty in terms of escalating costs Edge Computing is set to become a game-changer in the industrial revolution.
The growth of Edge technology is causing a revolution on the path to Industry 4.0, and the need has arisen to define different parts of the Edge and their functionalities. Concepts such as thin edge and thick edge have emerged from the exponential growth of Edge Computing technology, which industry experts claim is the key to the digital transformation of critical industrial infrastructures.
An increasingly complex Smart Grid requires two main aspects: visibility and, above all, the ability to automate decisions. This ability to make decisions autonomously is made possible through virtual applications on the edge nodes.