The rich text element allows you to cre
ate and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.
A rich text element can be used with static or dynamic content. For static content, just drop it into any page and begin editing. For dynamic content, add a rich text field to any collection and then connect a rich text element to that field in the settings panel. Voila!
Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.
In today’s multifaceted energy world, a growing number of prosumer assets are increasing the complexity of power grids. Decentralized systems with solar generation, wind turbines, and electric vehicles provide promise for a decarbonized future, but also bring along challenges for both utilities and prosumers.
One company, Fsight, is providing insight to the energy grid of the future with the development of a pilot project in Israel using its Energy AI solution.
“We are seeing a very complex market emerging, where the distribution company needs to allow more and more renewables and flexible energy assets to be installed behind the meter, while maintaining a stable local grid,” Emek Sadot, CEO of Fsight told pv magazine. “At the same time, prosumers who have installed such flexible assets want to optimize their energy flow to maximize the value of their investment.”
Energy AI is an integrated machine learning platform that provides predictive forecasting, optimization and peer-to-peer trading. The AI model learns and forecasts consumption and production of numerous grid assets for production. Then, the optimization engine manages the energy flow of each end user and makes real-time decisions regarding the buying, selling, and storing of energy. The system performs peer-to-grid and peer-to-peer trading to connect independent prosumers across an entire community or grid.
“It’s very logical to manage electricity consumption so that you sell when it’s expensive and buy when it’s cheap,” says Christian Kern, ex-Chancellor of the Republic of Austria and chairman of Fsight. “Artificial intelligence and deep learning can be applied in the energy sector in a very interesting way in this context.”
Fsight was founded in 2015 by energy industry heavyweights; the former Head of Energy CEE Siemens and former president and CEO of Israel Electric Company who serve as the company’s acting directors. Since then, the company has deployed ten commercial projects. At the beginning of 2019, the company launched its flagship Gilboa Iris Project. Located in an advanced energy community in Northern Israel, the pilot project will work with massive inflows of solar, wind, and storage systems, electric vehicles, multiple smart appliances, and anything with significant grid flexibility – all overlapped with the Energy AI platform.
“Energy AI bridges between the distribution company needs and the prosumer interest by calculating every moment the right incentive that will balance the local grid and at the same time optimizing the flexible assets accordingly,” said Sadot.
The sustainable community project is currently under simulation and the first phase of the pilot is planned for two years, with possibility for extension. Fsight says it currently has a handful of partners but is looking for three to five more to join the consortium. The company is in discussions with utilities, hardware providers, research institutions and companies to partake. Partners will receive full access to insights, all collected data, and analysis with the ability to test their businesses cases, market conditions and regulatory schemes.
“I believe we are facing the most complex challenges in the history of our civilization, but if we focus our energy and act together, we will overcome it,” concluded Sadot.