This symposium will discuss how data can be collected, processed, and analyzed for improving modeling, optimization, and control applications for emerging smart grid applications such as electric mobility, renewable energy integration, demand-response, energy internet, and carbon reduction. Primary data sources include phasor-measurement units, GHI measurements, smart meters, intelligent building sensors, EV driving patterns, and substation data. We particularly welcome papers proposing novel use of machine learning and artificial intelligence techniques to address issues related to the reliability, efficiency, and security of smart grids. The topics of interest include, but are not limited to:
- Data management strategies:
- Strategies for wide-area monitoring and visualization
- software/cloud architectures
- reliable and privacy-preserving data storage
- reliable and privacy-preserving data communications
- blockchain technologies
- Big Data Analytics:
- EV driving behavior analysis
- State estimation
- Demand response
- reliable and privacy-preserving power system operation
- Data-driven monitoring, protection, and control of electricity networks
- Applications of Data management and analytics to:
- power-grid transmission and distribution system automation
- energy internet and trading
- resource aggregation (renewables, electric vehicles, flexible demand, etc.)
- managing smart buildings/houses at scale
- dynamic utility pricing
- predictive maintenance
- Metaverse for the grid
- Carbon reduction and carbon neutrality
Organizers welcome studies with well-elaborated realistic case studies and real-world datasets.
