Efficiency in o&m for csp and solar power station through information about the weather and market

Efficiency in o&m for csp and solar power station through information about the weather and market

September 3


Publicación de los nuevos retos del programa I’MNOVATION 2019 Chile que buscan respuesta a los desafíos globales.

November 5


Cierre de la recepción de propuestas a los retos. ¿Todavía no has aceptado el reto? ¡Corre a inscribirte!

November 28


¡Demuestra al jurado que tu startup/scaluep/spin off es la ganadora!

October 13


Cada equipo presentará la solución desarrollada al comité de decisión que evaluará la continuidad y el escalado del proyecto.

30 000 $
30 000 $

Thermosolar electricity can provide energy 24 hours a day in an efficient, manageable manner. Cerro Dominador is a power station that combines photovoltaic energy with thermosolar energy. The thermosolar (Concentrated Solar Power) power station is the first in Latin America and has a capacity of 110 MW, to which is added the 100 MW of photovoltaic energy.

As it’s the first of its kind in Latin America, it involves new challenges regarding operation and maintenance which need to be addressed in a quick, efficient and digital manner. The thermosolar plant has a field of 10,600 heliostats that concentrate solar energy at a point at the top of a tower or receptor, which is 250m tall. The solar radiation is used to heat up melted salts which are used to generate steam, which feeds the turbine. Furthermore, it has a system for thermal storage of melted salts which allows it to produce energy consistently 24 hours a day.

At ACCIONA, we’re looking for startups that can help us with a digital tool that optimises the operation and maintenance of a mixed thermosolar power plant like Cerro Dominador. How could we optimise operations, considering the different modes of operation, based on the parameters and information analysis in real-time? How can we integrate the weather conditions and the sale of energy with the best scenarios and strategies, according to the reality of availability and the operation of the plant? How can we make the charging plans for the centre for 24/48 hours more efficient based on the analysis of real data regarding the facility? How can we integrate the different variables and modes of operation in a “Digital Twin” for digital visualisation? How can we foresee the maintenance needs for the systems, equipment or integral parts of the facility based on the analysis of real, historical parameters?