
Dipartimento
DIPARTIMENTO DI ENERGIA
Descrizione
The course offers lectures on AI methods and their practical application to energy components and systems. It has a modular framework with two mandatory modules: Module 1: AI fundamentals Module 2: Implementation of AI methods using the Python Data Science Stack. The participant can also choose from a portfolio of modules dedicated to the application of AI in different energy domains: Module 3: AI for modelling thermal systems Module 4: AI for renewable generation forecasting/ AI for integration of electric vehicles Module 5: AI for reliability analysis and maintenance engineering of energy components and systems Module 6: AI for risk and resilience assessment of energy systems Lectures are held in English. All participants will receive a complete set of presentation slides with specific examples and case studies, selected reference lists and resources in electronic format. In the sessions of module 2, the general implementation of AI methods using Python Data Science Stack is practiced hands-on by the participants. The following modules also include hand-on practice, during which the participants directly apply the methods explained in the lectures to practical case studies of application. When you fill in the application form, please insert in the field «note candidate» the optional module or modules (3, 4, 5 or 6) you want to attend.
Progetto Formativo
Components and systems for electrical/thermal power generation, distribution and transmission are equipped with sensing capabilities, which provide data that is informative on their operative performance and status. These data and other information (e.g. maintenance reports. inspection images, etc.) can be analyzed by artificial intelligence (AI) algorithms and tools to extract information useful for operating the components and systems in an efficient, reliable, safe and sustainable way. The goal of this course is to provide the participants with methodological competencies, analytical skills, and practical knowledge on the existing algorithms and available computational tools of AI for system modelling analysis and simulation, virtual sensing, component health management, forecasting, control, and remote auditing, reliability analysis and risk assessment management, multi-objective and multi-level optimization, and decision support systems.
Requisiti
The expected participants to the course are data scientists, operation/maintenance engineers, asset/facility/energy managers, R&D and sustainability managers, researchers and PhD students working and studying in the areas of energy components and systems design, optimization, reliability and safety analysis, maintenance engineering, built environment, building simulation/management, HVAC and thermal systems, power system modelling, electrical mobility, renewable energy generation and other energy domains. When you fill in the application form, please insert in the field «note candidate» the optional module or modules (3, 4, 5 or 6) you want to attend.
Luogo
Politecnico di Milano - Campus Bovisa - Edificio BL25
Faculty e Staff
Direttore: ENRICO ZIO
Ente Erogatore
DIPARTIMENTO DI ENERGIA
Referente
GIULIA PERNICANO
0223993855
courses-deng@polimi.it
Locandina e Allegati
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LOCANDINA_AI_for_Energy_Systems_id_461.pdf
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