Solar energy is the cheapest
source of electricity in many places, according to a report by the
International Energy Agency (IEA) on world energy in 2021. Despite this, solar photovoltaic plants are producing less than they could: energy production loses between 5-13% on average in the United States. This lower
productivity makes it even more difficult to limit the global temperature rise
to 1.5°C above pre-industrial levels to comply with the Paris Agreement.
Faced with the major problem posed by the climate crisis, the young Chilean civil industrial engineer decided to create the start-up SUNAI to optimize the production of solar plants with artificial intelligence algorithms and thus accelerate the decarbonization of electricity. Thanks to the potential of this breakthrough, this young man has been chosen among the winners of the Innovators under 35 Latin America 2022 awards of MIT Technology Review in Spanish.
Parrado elaborates, "Our clients see an annual increase in their power generation of more than 10.4%." They do this by compiling the big data generated by solar plants and turning it into operational guides with recommendations for solar plant operators to decrease their energy losses in the field.
By maximizing the benefits of solar production, SUNAI reduces the payback time and makes it easier for more companies and individuals to bet on these silicon plates that convert sunlight into green electricity. Such clean energy is "one of the best ways to combat climate change," adds the innovator.
Parrado's innovation is already improving the productivity of more than 150 solar plants in six Latin American countries. The engineer is now looking to expand his software with failure predictors, an automatic thermography module and a battery module. With these new services and more funding, the young man seeks to expand SUNAI so that more photovoltaic panels reach their maximum capacity to generate clean electricity and thus avoid releasing as many of the greenhouse gases that threaten our way of life as possible.