Wind



The Scientific Alliance

#artificialintelligence

A variety of headlines appear in the Scottish papers this morning, including new research on beating cancer and how the PM alleges that bullying on social media is a threat to democracy. The UK front pages cover calls for a pardon for suffragettes and reaction to Trump's comment on the NHS among other issues.


How artificial intelligence will improve O&M

#artificialintelligence

Artificial intelligence is being applied to almost every industry in efforts to improve operations and trim costs. Here's how early efforts are already benefitting the wind industry. The world is entering the early stages of a technology revolution called artificial intelligence (AI). It is showing an impact in many different fields such as image recognition, fraud detection, and self-driving cars, to name a few. Machine learning techniques have resulted in remarkable performance improvements in each field to which it has been applied.


Robots Solving Climate Change - AlleyWatch

#artificialintelligence

The two biggest societal challenges for the twenty-first century are also the biggest opportunities – automation and climate change. The epitaph of fossil fuels with its dark cloud burning a hole in the ozone layer is giving way to a rise of solar and wind farms worldwide. Servicing these plantations are fleets of robots and drones, providing greater possibilities of expanding CleanTech to the most remote regions of the planet. As 2017 comes to end, the solar industry for the first time in ten years has plateaued due to the proposed budget cuts by the Trump administration. Solar has had quite a run with an average annual growth rate of more than 65% for the past decade promoted largely by federal subsidies.


'Crazy' North Sea wind farm island set for 2027

Daily Mail

A'crazy' artificial island in the North Sea that could supply renewable energy to 80 million people in Europe is set to open in 2027. Plans for the 2.3 square mile (6 square km) landmass suggest it will be surrounded by fields of offshore wind turbines and come with its own airstrip and harbour. The'North Sea Wind Power Hub', which will be home to a small team of permanent staff, will send electricity via long-distance cables to Britain and the Netherlands, and later to Denmark, Germany, Norway and Belgium. An artificial island (artist's impression pictured) with an airstrip and harbour is set to be built in the North Sea to help power Europe. Dogger Bank, 78 miles (125 km) off the East Yorkshire coast, has been identified as a potential shallow and windy building site for the £1.3 billion ($1.75 billion) project.


Machine Learning for Wind Turbine Blades Maintenance Management

#artificialintelligence

Wind energy is a clean resource, and one that is growing worldwide, since it is the most efficient renewable energy source [1,2]. Delamination is one of the most common problems in composite materials, caused by the disunion of their layers or by the detachment of their adhesive bonds. Low speed impact on working conditions can create a visible fault on WTB [4,5]. Similarly, delamination can be generated by an error in the manufacturing process. State space models are employed to predict the growth of delamination by stress/strain, fracture mechanic, cohesive zone, extended finite element method based models [7].


Wind Turbine Fault Detection Using Machine Learning And Neural Networks

#artificialintelligence

The increasing demand for energy as well as the rapid rise of greenhouse gas emissions due to the use of fossil fuels have made us invent new ways to generate renewable energy. The production of electrical energy based on wind power using wind turbines has become one of the most popular renewable sources since it can generate a reliable, clean energy with costs now comparable to conventional nuclear energy sources. Wind turbines are massive pieces of equipment and typically are installed in locations characterized by extreme climates to exploit the high wind energy potential. Regular on-site inspection and preventative maintenance of these equipment are required to sustain long-term returns. In addition to the maintenance tasks, random electrical and mechanical failures can cause prospective breakdowns and damages, and lead to machine downtimes and energy production loss.


How machine learning improves energy consumption

@machinelearnbot

At the intersection of machine learning and energy consumption stands an incredibly powerful force with the potential to transform the way we globally produce and consume energy. So powerful in fact, that the concept of merging machine learning and renewable resources has been named the "energy internet" by economic theorist and author Jeremy Rifkin or "digital efficiency" by Intel and GE. Going green with machine learning solutions can drastically improve the way we consume energy, in terms of lower operational costs, more efficient production, better use of natural resources and lower environmental impacts. Last year, Google, with the help of its U.K.-based subsidiary DeepMind, reduced the amount of energy used to cool its data centers by 40%. By introducing machine learning to compensate for the nonlinear interactions between equipment and environment, and using the unique architecture and environment of each data center, this decrease saves Google millions of dollars each year.


Artificial Intelligence Set To Boost Efficiency Of Solar & Wind CleanTechnica

#artificialintelligence

New research has posited that artificial intelligence will increasingly automate operations for the wind and solar industries, boosting their efficiencies in areas such as decision making and planning, condition monitoring, robotics, and inspections. The new position paper published this week by DNV GL -- international accredited registrar and classification society headquartered near Oslo -- entitled Making Renewables Smarter: The benefits, risks, and future of artificial intelligence in solar and wind, outlines the advances being made in robotics, inspections, supply chain, and the way we work and showcases a variety of opportunities for the solar and wind industries to embrace artificial intelligence (AI) applications to improve their efficiency. "The use of artificial intelligence in industries continues at an impressive rate -- in manufacturing, engineering, healthcare, transportation, finance, telecommunications, services, and energy," the authors of the report explain. "Artificial intelligence's ability to use machine learning to analyse historical and new data, make predictions, control physical operations, and make decisions at increasingly higher levels is having an immense impact." The report explores ways in which AI applications like machine learning can impact the efficiency levels of areas involved in the wind and solar industries such as decision making and planning, condition monitoring, robotics, inspections, certifications and supply chain optimization, as well as the way technical work is carried out.


Robots solving climate change

Robohub

The two biggest societal challenges for the twenty-first century are also the biggest opportunities – automation and climate change. The epitaph of fossil fuels with its dark cloud burning a hole in the ozone layer is giving way to a rise of solar and wind farms worldwide. Servicing these plantations are fleets of robots and drones, providing greater possibilities of expanding CleanTech to the most remote regions of the planet. As 2017 comes to end, the solar industry for the first time in ten years has plateaued due to the proposed budget cuts by the Trump administration. Solar has had quite a run with an average annual growth rate of more than 65% for the past decade promoted largely by federal subsidies.