Colour your cloud green to harness clean energy

Our head is in the cloud, but we are keeping the earth in mind.Our commitment to a sustainable future for the earth takes a lot of forms, whether buying renewable energy or using machine learning to build a High resolution map of the entire planet.

Building a sustainable future is a team effort. In addition to cutting carbon emissions and thinking, we hear from our users that they are doing this work too. 

Organisations are using Google cloud platform to learn more about the environment, explore new ways to protect the earth's resources, better harness renewable or simply improve the sustainability of their IT infrastructures. Sharing some of the positive environmental impacts our customers are driving with google cloud.

Artificial intelligence demand will be increasing over the years. Artificial energy has made human lifes easier than ever before. Smart homes are one of them. Learning artificial intelligence will pave the way for a better career as in the future, no company will be able to survive without AI skills. Artificial intelligence institute in Delhi like Madrid Software Trainings have made careers of 5000 professionals in the industry.

We build sustainability into our cloud 

We are committed to delivering cloud with sustainability built in, so our customers can get the benefits too and more easily build a sustainable future. It takes seconds to spin your cloud services and get all the computing power you need for your business, it's so on demand that it's easy to forget that cloud services still run in a data center powered by electricity on physical servers.

Sustainable cloud starts with energy efficient data centers. Google has been  putting its own machine learning (ML) technology to use in our centers to make them more efficient.

Cooling servers require a lot of electricity. Neural networks to predict the optimal cooling settings based on data are captured every 5 mins.This has improved server cooling efficiency by 30%.

Concerns about climate change, energy security and dwindling fossil fuel reserves are making way for more integrated and complex approaches to the generation, distribution and management of renewable energy. Energy and utility companies must transform their business to deliver cost effective and reliable energy resources while keeping reliable energy resources in mind.

AI is also improving educational opportunities and access for learners. The aspiring artificial intelligence scientists will be working in different sectors may be in the medical, energy sector, sustainable transportation and creating smart cities.This will not be possible without AI.  

Artificial intelligence would be an indispensable skill in future. Similarly, No artificial intelligence learning would be complete without Madrid Software Trainings courses for AI. Certification courses for AI would make all the difference. 

Smarter energy systems will save lots of currency in operating costs and reduce the need to build more capacity, anticipate detection and respond to problems quickly, empower consumers and help integrate electric vehicles and energy from renewable sources.

The same way ML technology helps us with cooling effects with our renewable energy efforts too by better predicting the output of some of our wind energy. We had been committed to renewable sources of energy because we realize the reversing climates change requires a transition to carbon free energy. 

So we use neural networks to predict the wind output of some of the farms based on weather forecast data helping us to increase wind energy by 20%.

Using google cloud to support their users in a more sustainable way which reduces digital environmental footprint.

They are also building new applications that tackle climate challenges and using data to make more informed decisions about environmental impact. 

Making use of solar energy

Google cloud tools to make home solar accessible to all. Enough sun hits the earth every hour to power the global economy for a year. The challenge is capturing energy from all of those rays for people to use. Google maps and google project sunroof, sun-power corporation built their new instant design service improving the solar design process by making it 97% faster. This new service showcases how cloud AI and CPU make a great working team.

The earth is pretty big and to see what changes are going around the globe often to crunch an incredible amount of data and understand the use for cloud computing. Google cloud teams  come together with a machine learning engine to form an end to end pipeline which creates raw data. Time series look at the earth's land cover and can help and track and understand things like deforestation, urbanization, water resources changes. 

Challenges of the renewable energy and Artificial Intelligence can help - 

• Main challenge is unpredictable weather for producing renewable energy.

• Solar and wind energy are the leading sources of renewable energy.

• Recent developments in energy storage  technology are quite promising.

• Demand for renewable energy will only increase in the future.

• Demand for Machine learning and other emerging technologies to improve productivity and overcome shortfalls will be huge.

How AI can help improve the renewable energy sector -

• It has taken up new roles in human life by serving as a virtual assistant in our homes operating our cars and more

• Electric grid is one of the most complex machines on earth. It rapidly evolves with the addition of variable renewable energy resources.

• Due to inherent variability of wind and solar, the current grid faces many challenges in accommodating the diversity of renewable energy.

Reliability of renewable energy and modernize the overall grid.

• Smart, centralized control centers-  Energy grid can be interconnected with devices and sensors to collect a large amount of data.when coupled with AI,  this data can give insights to the grid operators for better control operations. They can make weather and load predictions that can overall improve the integration and efficiency of renewable energy.

• Improved integration of micro-grids -  AI can help with the integration of micro-grids and managing disturbed energy. Community level renewable energy generation units are added to the primary grid.Hard to balance energy flow with the grid. AI can play a vital role in solving the quality and congestion issues.

• Improved safety and reliability-  Biggest goal of AI is to manage the intermittency. It can also offer improved safety,efficiency,reliability.

• Help understand the energy consumption patterns, identify the energy leakage.  The health of the equipment is also important for producing good results.

• Expand the market-  the integration of AI can help the renewable suppliers expand the market place by introducing the service models and encouraging higher participation. AI powered systems will be able to analyse the data related to energy collection. Targeting new customer markets.

• Companies that are using AI to improve renewable sources of energy 

•  Xcel energy 

• General  electric.

• Power scout

More and more companies are getting involved in AI infrastructure technologies. More IT firms are using AI skills in the workplace.Companies like Amazon web service, Google cloud platform, IBM cloud, Siemens are hiring in large numbers. 

But the supply is not matching with the demand. Madrid Software Trainings has created More than 1000 data scientists in the industry and are still counting. Free trial classes for data science seats are filling up fast. Hurry and book your seats! Make your career in artificial intelligence!