Digital twin of a wind farm
Prediction of the energy productivity of a wind power plant
The problem
Not knowing exactly how much energy our wind turbines will generate weakens our ability to participate in energy auctions, to bid for them, to set prices and increases uncertainty in this critical process for energy companies.
The opportunity
Thanks to advances in technology and Artificial Intelligence techniques (Machine and Deep Learning), we have the opportunity to take advantage of historical data, both from our organization and external data (weather data, for example) to predict with enough hours or days in advance the power that a wind farm will generate.
This helps significantly in decision making, reduces penalties for over or under estimation, reduces uncertainty and minimizes risk.
What is MathIT.Windfarm?
MathIT.Windfarm is a digital twin of a wind farm that helps energy companies with wind turbines installed anywhere on the planet to automatically predict days or hours in advance the power they will generate in 24 hours (minimizing the dependence on human expert knowledge) and to simulate possible operations in different scenarios with different boundary conditions.
MathIT.Windfarm uses powerful Machine Learning algorithms (time series, trees, random forest, SVM, regression, neural networks, ensembles…) to make predictions with the necessary granularity.
Business value
Improve our organization’s performance and accounts, reduce penalties, minimize the risk of human-expert dependency.
Why MathIT.Windfarm?
Profesionales en Inteligencia Artificial y en Investigación Operativa, en la aplicación práctica, sobre escenarios reales de alta complejidad, del estado del arte en las técnicas de optimización de procesos.
Expertos en la logística del transporte, con un elevado registro de proyectos en organizaciones de transporte y distribución.
Apasionados por resolver problemas operativos complejos y aportar el máximo valor de negocio a organizaciones logísticas desde la aplicación de estas capacidades.
Hiperpersonalización: no hay dos negocios iguales, ni dos operativas iguales. La flexibilidad de capturar y modelar las diferencias nos permite maximizar el valor aportado.
Amplio registro de proyectos de alto valor para grandes empresas nacionales e internacionales de alta demanda.
Valores diferenciales: conocimiento experto, innovación e inversión constante en actualización científico-técnica, flexibilidad, agilidad y adaptabilidad.
