[MUSIC PLAYING]
SPEAKER: We're trying to solve one of humanity's biggest
problems, which is how will we sustainably generate
energy in this new world where energy usage will only go up
from here.
PRIYANKA VERGADIA: How do you approach
the monumental challenge of innovating renewable energy?
During a 13-year project that concluded in 2020,
the Makani team set out to take on the challenge using
technology inspired by kitesurfing.
I'm Priyanka, a developer advocate with Google Cloud,
and I wanted to learn more about how Google Cloud played
a part in the search for a new kind of wind-powered energy.
How were the kites tested and simulated
to further the project's progress?
The team gave me the inside scoop
on how Google Cloud powered the simulations and data processing
for the energy kites.
I am very excited to find out how the kite simulation
logs were collected, processed, analyzed, and visualized
to make continuous improvements to these kites.
But before we jump into the technical background,
let's see a quick overview of how wind-powered kites actually
work.
Makani's energy kite was an aerodynamic wing
tethered to a ground station.
To begin flight, the kite used rotors
to hover vertically in the air.
Once at full tether length, the kite
transitioned into crosswind flight,
flying in vertical loops.
As the kite flies, the rotors are
spun by the wind, generating electricity that is sent
down the tether to the grid.
The kite's path is managed by the flight computer, which
guides the kite even in turbulent wins
and safely returns it to the ground station.
So those are the basics.
But to understand how the Makani energy kite worked,
it is helpful to look at how the mechanics of a traditional wind
turbine translated into a crosswind kite.
The blade on a wind turbine redirect
wind and creates one force that pushes on the tower,
and another that pushes the blade forward.
The forward push of the blades turns a generator
to make power.
The crosswind kite is like freeing a blade from the tower.
The freed blade, now a wing, is able to grab more wind,
therefore making more power than it could when stuck to a tower.
The crosswind kite grabs more wind
and generates more power for the same size
wing from the wind turbine, but with less materials.
PAULA ECHEVERRI: Trying to extract power from the wind.
And that's what we would get closer to when we went testing.
It's like the actual wind, the physical world
where our technology had to work well.
So sometimes the challenges were it was not windy enough,
and we were sitting there waiting for wind.
And then sometimes it was too windy.
PRIYANKA VERGADIA: Because flying a real kite
is expensive, Makani's team created software
that would simulate the kite flying with all the wing
components, and as much of the physics
they could simulate close to a real kite.
They needed to run the kite at many different wind directions,
at different altitudes.
So they would generate hundreds of different configurations
to simulate the flight.
Then these configurations were fed
into Compute Engine instances that
would run the kite simulations.
The Compute Engine instances would be created dynamically
to run these simulations, generating log
files and reports, which would be then saved in Google Cloud
Storage.
And these Compute Engine instances
would eventually shut down themselves,
saving cost and staying efficient.
After that, the software engineers in the team
would pull these logs and analyze them.
They would look for issues, red flags, things such as "kite
did not fly very well."
There are some issues here.
They would make new modifications,
and then restart the simulation process again
to go through the logs again.
And this process keeps repeating until the team felt confident
that the real kite will not crash
under those circumstances.
Once satisfied with the simulations,
they would go to a real testing site, such as Hawaii or Norway,
to fly an actual kite.
And as the kite is flying, it would send the logs
to the Command Center on ground.
Once the flight is done, the logs
are then sent to Google Cloud Storage for engineers
to analyze again.
They repeat the same process, look at the data,
analyze it, make modifications to those configurations,
and then go back to the first stage.
Run a bunch of simulations, verify
that those changes will make the code fly better
and won't crash, and will repeat the entire cycle.
Now, let's talk about data analysis.
The engineers had two ways to analyze the data--
Manual lookup, which is downloading the file
to their computer, loaded into MATLAB, or use a Python program
and run their own analysis scripts.
But with a project like this, there
needs to be a well-defined, consistent analysis that
could run over and over on all the flight data.
For that, they built a data analytics frontend
on App Engine, where an engineer would
submit a request for all the logs in a particular time range
and analyze them with these predefined criterias.
App Engine will store the request into Cloud SQL
and send it to pub/sub messaging service.
Jenkins master will pull the analysis request
and distribute the job to a bunch of Compute Engine worker
instances.
These instances were always alive,
waiting for requests to be sent to them.
The worker would send a request to Cloud storage
for the log files for that specific date and time range,
process those logs for analysis, produce the results,
and then store them back in Cloud SQL
and publish to App Engine.
Essentially, the Makani team ran a bunch of simulations,
collected a ton of data, and learned from it.
Then they flew a real kite, studied that data,
and reiterated the process for the next successful flight.
Google Cloud played a critical role in this process
by providing them a scalable infrastructure for simulations
and data analysis, while keeping them
focused on the real problem of harnessing wind energy.
Though the Makani team's journey has drawn to an end,
they set up a portfolio of open source resources,
including technical reports, videos, documentation, patents,
code, and more.
Check out the Makani website to get a full overview.
If you are interested in learning more
about Makani's journey, they also
shared a full-length documentary,
which we have linked below.
Makani's goal was to harness wind energy,
and Google Cloud played a huge role
in providing the resources needed
to do just that without worrying about the infrastructure,
scale, and data processing.
In this behind the scenes series,
we will continue to explore how Google Cloud powers
incredible projects, such as Makani.
And I'm looking forward to taking this journey with you
all.