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Digital Twins for Energy Grids


Physical systems, such as electricity grids, are very complex and thereby difficult to model. Digital twins provide a solution. "Digital Twins are one of the top technological trends" Here will we discuss a literature review (2021) that was performed by researchers at Bosch Engineering. The review focused on how digital twin and "big data" technology can be applied to complex physical systems, such as energy grids. Without further ado, let's dive in.

Industry collaboration powers new generation of grid emergency control technology


Grid operators face big challenges and big opportunities when it comes to managing through emergency conditions that disrupt power service. The increasing number of power outages in the United States cost an estimated $30–50 billion and affect millions of customers each year. The challenge and the opportunity both lie in optimizing power system responses when the unexpected happens. Optimization can minimize the effects of these events. Researchers at Pacific Northwest National Laboratory (PNNL) are collaborating with partners at Google Research, PacifiCorp, and V&R Energy to develop a real-time adaptive emergency control system to safeguard the grid against costly disturbances from extreme weather and other disruptive events.

Editorial: Data-Driven Solutions for Smart Grids


To address this complex issue, the most promising research directions are oriented toward the conceptualization of improved information processing paradigms and smart decision support systems aimed at enhancing standard operating procedures, based on pre-defined grid conditions and static operating thresholds, with a set of interactive information services, which could promptly provide the right information at the right moment to the right decision maker. To effectively support the deployment of these services in modern smart grids it will be incumbent upon the scientific community to develop advanced techniques and algorithms for reliable power system data acquisition and processing, which should support semantics and content-based data extraction and integration from heterogeneous sensor networks. This research topic contains four articles.The paper Optimal Balancing of Wind Parks with Virtual Power Plants by Vadim Omelčenko and Valery Manokhin addresses data-driven solutions in the context of optimization of virtual power plants. This work proposes the use of machine learning to process available data measurements. The goal is to balance the power production and at the same time maximize the revenue of a portfolio of power plants with different technologies (biogas, wind, batteries, etc.) considering uncertainty in both price and power production.The paper Supporting Regulatory Measures in the Context of Big Data Applications for Smart Grids by Mihai A. Mladin discusses the policy and regulatory aspects. This paper focuses in particular on big data applications to the ongoing "energy transition" process built on higher renewable energy integration and digitalization, and discusses how this can help regulatory measures through societal acceptance and involvement.The paper Data Consistency for Data-Driven Smart Energy Assessment by Gianfranco Chicco addresses the issue of data consistency and discusses data-versus model-based approaches.

How to develop a digital twin for highly complex systems


After discussing in my last two articles how digital twins can revolutionize the energy industry and how our Heat Transfer Twin can help HRSG (heat recovery steam generator) operators save millions of dollars, today I'd like to take a closer look at how a Heat Transfer Twin could be developed. As already explained, conventional inspections of HRSG walls and tubes require considerable manual effort and take up to three weeks. To reduce this expense, it's important to know in advance where corrosion might have occurred. However, identifying corrosion risks is very complicated because corrosion depends on several factors. We need to know if and how much liquid is in the steam, and where it hits the tubes.

IAEA Teams up with ITU and UN Family to Promote AI for Good


… to work together in identifying artificial intelligence (AI) applications that accelerate reaching the UN Sustainable Development Goals.

Electrochemistry, from batteries to brains


The members of her lab study fuel cells, which convert hydrogen and oxygen into electricity (and water). They study electrolyzers, which go the other way, using electricity to convert water into hydrogen and oxygen. They even study computers that attempt to mimic the way the brain processes information in learning. What brings all this together in her lab is the electrochemistry of ionic-electronic oxides and their interfaces. "It may seem like we've been contributing to different technologies," says Yildiz, MIT's Breene M. Kerr (1951) Professor in the Department of Nuclear Science and Engineering (NSE) and the Department of Materials Science and Engineering, who was recently named a fellow of the American Physical Society.

Imtiaz Adam Joins Marktechpost As An Advisory Board Member


WIRE)--Imtiaz Adam joins Marktechpost as an Advisory Board Member. Imtiaz Adam (MBA, MSc) is a leading AI influencer and hybrid Data Science and business strategy specialist. Imtiaz is the founder of an AI startup, Deep Learn Strategies Limited (DLS). Imtiaz has been a speaker at major events such as during the WEF at Davos where he spoke at a panel on AI. He is a Sloan Fellow in Strategy from London Business School with an EMBA exchange at Columbia Business School.

Drone attack on PA substation was first one to target energy grid, according to Homeland Security

Daily Mail - Science & tech

A modified commercial drone may have been responsible for an attempted attack on a Pennsylvania power substation last year, the first reported case of a drone assault on the U.S.'s energy infrastructure. Authorities believe a DJI Mavic 2 drone with a thick copper wire tethered to it was found in June 2020 was likely intended to disrupt operations'by creating a short circuit to cause damage to transformers or distribution lines,' according to a joint intelligence bulletin from the FBI, Department of Homeland Security, and the National Counterterrorism Center released October 28. If the wire had come into contact with any of the power plant's high-voltage equipment it could have resulted in a short circuit, power failure or even a fire, according to New Scientist. The Drive reported the drone was recovered by authorities from a substation near Hershey, Pennsylvania, about 100 miles from Philadelphia. No groups has claimed responsibility: The device's camera and internal memory card had been removed and identifying labels were removed, in a likely attempt to obscure its origins.

Drone tried to attack the US electrical grid last year, report reveals

New Scientist

A modified consumer drone was used in an attack on an electrical substation in the US last year, according to a report from the FBI, Department of Homeland Security and National Counterterrorism Center. The report, which is being circulated to law enforcement agencies in the US, highlights the incident at a substation in Pennsylvania last year as the first known use of a drone to target energy infrastructure in the US. The location isn't specifically identified, but the drone crashed without causing damage. The drone was modified with a trailing tether supporting a length of copper wire. If the wire had come into contact with high-voltage equipment it could have caused a short circuit, equipment failures and possibly fires.

Artificial Intelligence and IoT


Let's analyze our own bodies. We the humans begin to have six senses like touch, smell, vision, hearing, tasting, and the sixth sense. I'm not sure some researchers are saying the sixth sense is about sensing one's body in space. Our human body is fully connected with nerves whenever you touch or taste anything you will feel or sense something about that action you have done. How you are able to classify the sense whether that it is good or bad?