Special Session: Computational Intelligence Techniques for Observable Smart Grid and Sustainable Energy Systems
The IEEE World Congress on Computational Intelligence (WCCI) 2024
30th June - 5th July 2024, Yokohama, Japan
Supported by IEEE CIS Task Force on Computational Intelligence in the Energy Domain
Overview
The intensifying challenges of climate change combined with a surging energy demand underscore the crucial need to refine existing smart grid observability methodologies. Smart grid has revolutionized the interaction between renewable energy sources and consumers. At the same time, the Advanced Metering Infrastructure offers a wealth of data on energy usage, paving the way for detailed profiling of consumer demand, efficient load and renewable energy forecasting, as well as improved monitoring and data handling. With the escalating complexity of the grid, there is a growing need for advanced computational methods to oversee grid ecosystems, considering both utility and end-user perspectives. This necessitates more observable, accessible, and controllable network infrastructures.
This special session offers an opportunity for researchers from various research fields, such as machine learning, artificial neural networks, fuzzy logic, evolutionary algorithms, power and energy systems, communications, optimization, and control engineering, to share their insights on how computational intelligence techniques can enhance observability and electrical signal processing for Smart Grids and Sustainable Energy Systems. Electrical signal processing is a key component of such systems, as it enables the extraction of useful information, such as load profiles, power quality, energy consumption, and generation patterns. Computational intelligence techniques, such as artificial neural networks, fuzzy logic, and evolutionary algorithms, can improve the performance and accuracy of electrical signal processing methods, by providing adaptive, robust, and scalable solutions to the challenges posed by the smart grid.
The main aim of this special session is to bridge the gap between computational intelligence techniques and the pressing issues related to electrical power and energy systems. The session is supported by the IEEE CIS Task Force on Computational Intelligence in the Energy Domain (CI4Energy).
Topics covered
The topics of interest include but are not limited to computational intelligence techniques applied in:
- Behind-the-meter Solar Disaggregation
- Residential and Industrial Non-intrusive Load Monitoring
- Intelligent Load Forecasting
- Energy Theft Detection
- Cyber Security for the Smart Grid
- Forecasting of Renewable Energy Production and Demand
- Distributed Energy Resources (DER) Visibility and Monitoring
- Smart EV Charging and EV Aggregation Techniques
- Cloud and Edge Computing for Energy Monitoring
- High-Resolution Load Profiles Generation
- Demand User Profiling with Distributed Solar Generation
- Power Signal Analysis for Anomaly Detection
- Detection and Classification of Power Quality Disturbances
- Power Smoothing Methods for Solar Photovoltaic Power Fluctuation Mitigation
Submission Guideline
Please follow the submission guideline from the IEEE WCCI 2024 Submission Website. Special session papers are treated the same as regular conference papers. Please specify that your paper is for the Computational Intelligence Techniques for Observable Smart Grid and Sustainable Energy Systems. All papers accepted and presented at WCCI2024 will be included in the conference proceedings published by IEEE.
Important Dates
January 15thJanuary 29th - Paper Submission Deadline- March 15th - Paper Acceptance Notification
- May 1st - Camera-ready Submission
- TBA - Special Session
Organizers
- Giulia Tanoni, Università Politecnica delle Marche, Ancona, Italy (g.tanoni@pm.univpm.it)
- Djordje Batic, University of Strathclyde, Glasgow, UK (djordje.batic@strath.ac.uk)
- Stavros Sykiotis, National Technical University of Athens, Athens, Greece (stasykiotis@mail.ntua.gr)
- Emanuelle Principi, Università Politecnica delle Marche, Ancona, Italy (e.principi@staff.univpm.it)
- Lina Stankovic, University of Strathclyde, Glasgow, UK (lina.stankovic@strath.ac.uk)