Workshop's objectives and targets
AID4RES23 invites paper submissions in any area related to AI tools and applications for addressing the RES sector’s challenges. The workshop focuses on challenging and emerging areas in data management, machine learning and artificial intelligence methods and applications that use sensor data and/or big time-series data regarding the RES industry.
The workshop aims to provide participants with an in-depth understanding of the various machine-learning approaches and tools that can be used to develop, maintain, and optimize renewable energy systems, such as wind and solar parks. The workshop will focus on the most recent advances in machine learning and its applications, offering the participants the opportunity to learn about the various models and their efficacy in improving the performance of renewable energy systems.
The following themes in the domains of machine learning and data management techniques and applications for renewable energy systems should be included in the submitted works (but not exclusively):
- Machine learning methods and applications from Renewable Energy Sources (RES) (e.g classification, clustering, pattern extraction, support of decision making using decision trees, support vector machines, neural networks, etc.)
- Data management for RES (e.g. data lakes, time series management, data sharing and privacy, edge and cloud systems, challenges in data management etc.)
- Visual analytics and exploration of big and complex RES data, interactive visual analytics, visual representation of forecasting and prediction, etc.
- Data processing algorithms and techniques for data from RES, data mining and knowledge extraction for RES data.
- Conceptual design and architecture for IT systems specialized in RES data management, Standardization of RES data and applications, Evaluation of tools for RES data management and RES AI applications, Open, FAIR RES datasets and data generators.
- Data intensive and AI applications for wind and solar park operation and optimization (AI-driven methods and tools for optimizing the positioning and orientation of photovoltaic cells for maximum efficiency,data management applications for analyzing the performance of wind turbines in real time etc).