--With the proliferation of smart grids, smart cities face growing challenges due to cyber-attacks and sophisticated electricity theft behaviors, particularly in residential photovoltaic (PV) generation systems. Traditional Electricity Theft Detection (ETD) methods often struggle to capture complex temporal dependencies and integrating multi-source data, limiting their effectiveness. In this work, we propose an efficient ETD method that accurately identifies fraudulent behaviors in residential PV generation, thus ensuring the supply-demand balance in smart cities. Additionally, we introduce a data embedding technique that seamlessly integrates time-series data with discrete temperature variables, enhancing detection robustness. With the widespread deployment of smart grids, modern power systems are increasingly vulnerable to cyber-attacks and evolving electricity theft behaviors [1].

Thousands of residents were left without electricity after a food delivery drone crashed into power lines in Australia. The power company, Energex, had to shut down the network after a crew was called to the incident Thursday in Browns Plains, south of Brisbane. While Energex was able to restore electricity for about 2,000 customers within 45 minutes, 300 remained without power for at least three hours, due to being in close vicinity of the drone crash, ABC News said Friday. Energex spokesman Danny Donald told ABC Radio they had never seen delivery drones hitting the network. "We've never seen these delivery drones hit the network. "This is the first time that I've seen it happen.

In the fast-changing world, technologies such as Artificial Intelligence (AI) and Machine Learning (ML) are leading the next wave of productivity gains and tech changes. Artificial intelligence is the main branch of prediction-based technologies which includes domains like machine learning, neural networks and data science. The AI and ML technologies have thrown open a plethora of doors to new applications, solving complex problems and lessening the efforts. In the aame way, AI and ML may endorse the growth of the renewable energy sector in myriad ways. Enabling AI in grid management will also mean shifting from infrastructure-heavy legacy models to a grid that is more resilient and flexible.

Artificial intelligence and machine learning can be leveraged by power companies to get better forecasts, manage their grids and schedule maintenance. Decentralised energy sources can use AI and ML to predict energy consumption in households, comparing data from a specific part of the year and previous years. Artificial intelligence (AI) and machine learning (ML) have the capability to transform the renewable energy space and can be leveraged by power companies to get better forecasts, manage their grids and schedule maintenance. Consumers can also enjoy uninterrupted green energy and get upfront information about scheduled maintenance works in the grid that could result in power outages. Adoption of electric vehicles and electrification of heating systems in the next 10-15 years will add complexity to energy grids across the globe.

Hadi Ganjineh is Head of IT, Integrated Tech & Innovation at Super Energy Corp. focused on leading-edge digital business, tech & innovation. We use energy in many different ways in our lives, be it for lighting up our houses, running electronic appliances or as fuel in our vehicles. There are mainly two types of energy: renewable energy and non-renewable energy. Non-renewable energy includes fossil fuels like natural gas, petroleum and coal. However, these energy sources come from nature itself; it is impossible to renew them quickly.

Utilities take advantage of this by monitoring virtually every aspect of power generation, distribution and consumption using sensors that predict component failures, controllers that automatically reroute power from point to point, and smart meters that closely track customer usage and trends. Processing that much information is far beyond human computational capabilities, so utilities are relying on the IoT and artificial intelligence (AI) to make the grid more user-friendly, reliable, flexible, secure and profitable. Two years ago, our local power company installed smart meters in the area. Shortly after, they offered customers a choice of keeping their current flat electric rate or switching to a time-of-use model, where the cost of electricity varies, hour-by-hour, depending on supply and demand. During high-demand hours--usually midafternoon through the early evening--rates are higher.

We purchased a wide assortment of things, including an Aerogarden, a 4K monitor, an air purifier and Nintendo's Ring Fit Adventure. But the ones that proved the most memorable sometimes went unmentioned on our site. Here, a few of our staffers look back on at least one item that made it to their "best of 2020" list that deserve a shout-out before the year is over. I simply don't have space in my apartment for a proper home office. So ever since March my kitchen table has also served as a writing desk.

The latest iteration of this new era revolves around data, both collecting it and analyzing it in ways never before possible. Big Data, as it's often called, is changing the world, and these changes are substantial. Here is how data is impacting society and what changes to expect in the future. The availability of robust scientific data in the latter half of the 20th century revolutionized how doctors treated diseases and provided better outcomes for patients. However, the ever-increasing flow of new data has made it nearly impossible for doctors and even large medical organizations to make sense of what the best and latest information is saying.

When Chris Shelton, chief technology officer for electricity giant AES, takes the stage at a tech conference in San Francisco this week, he'll be the rare name in energy. The rest of the lineup looks more like traditional Silicon Valley tech: Google, Nvidia, Facebook and others. Shelton is headed to San Francisco for the AI Summit to talk about what he described to GTM as "one of the most exciting things out there" -- which is how the energy sector will be using artificial intelligence. Though, Shelton contends, it's still early days when it comes to how the sector will embrace AI in practice. According to Shelton, AES is exploring how AI can improve awareness, efficiency and maintenance of the company's grid systems and assets like solar farms and gas plants.