IEEE World Congress on Computational Intelligence (WCCI) 2024
YOKOHAMA, JAPAN, June 30 – July 5 2024
Organized by Fernando Lezama (flz@isep.ipp.pt), João Soares, Jose Almeida, Zita Vale, Wenlei Bai, and Kwang Y Lee
Energy is the driving force behind societal progress and individual well-being. As the energy landscape evolves, we must extend our focus beyond mere optimization to encompass control and optimization in complex energy systems. The increasing energy demands of emerging economies are inevitable, but in light of the planet’s limited resources and the significant climatic changes induced by the power sector, it is crucial to establish measures that safeguard environmental quality and promote sustainability.
Navigating the socioeconomic intricacies of the energy sector requires extensive research and preparation. However, the challenges faced in this domain are notorious for their complexity, stemming from factors such as high dimensionality, numerous restrictions, a lack of knowledge, and noisy or damaged data. Moreover, these issues often come with time constraints, demanding solutions in near real-time. Consequently, achieving near-optimal and accurate answers within a reasonable timeframe remains a persistent challenge for various energy problems.
Scope and Topics
This special session continues the previous editions held at CEC since 2018, now expanding its scope to include both control and optimization in complex energy systems. We invite submissions of papers that delve into the application of Evolutionary Computation (EC) to address practical challenges within the energy sector. These challenges may span different types of energy carriers, including heating, cooling, and electricity supply, across various market levels—from household to industrial. We are particularly interested in problems characterized by high complexity, unpredictability, dynamic goal settings, multiple objectives, and expansive search areas.
The overarching objective of this special session is to foster communication between energy engineers and developers of new EC applications, with a specific focus on solving issues related to energy optimization within complex systems. Additionally, it is worth noting that this Special Session is an integral part of IEEE CIS ISATC Taskforce 3 activities.
Topics should concern CI applications or theory in the energy domain, including, but not limited to:
- Distributed evolutionary approaches in the energy domain;
- AI-enhanced control strategies for Electric and plug-in hybrid vehicles;
- Dynamic optimization of electricity markets using Computational Intelligence (local, regional, and wholesale levels);
- Energy scheduling and management with Intelligent Control Systems;
- Explainability in evolutionary computation for energy systems through machine learning and other AI methods;
- Algorithm configuration and portfolio for evolutionary computation in the energy domain;
- Ensuring Fairness in the application of CI within energy communities;
- Joint optimization of Heat and electricity with Computational Intelligence-driven algorithms;
- CI-driven solutions for Hydrogen economy challenges in energy systems;
- Evolutionary computation approaches to provide explanations for interactive machine learning in energy problems;
- CI-driven solutions for Natural gas optimization problems in energy systems;
- Optimal power flow in distribution and transmission with CI-based control systems;
- CI-driven approaches for Residential, industrial, and district cooling/heating problems;
- Smart grid and micro-grid control using CI and evolutionary algorithms;
- CI-driven solutions for Solar and wind power integration and forecast in energy systems;
- Addressing super grids challenges with continental and trans-continental transmission using CI;
- Transportation & energy joint problems: CI and Control Perspectives.
Important Dates
Paper submission due (Extended): 15 January 2024 29 January 2024
Notification of acceptance: 15 March 2024
Final paper submission and early registration: 1 May, 2024
How to submit a paper
Further related bibliography
- [1] Almeida, J., Soares, J., Lezama, F., Vale, Z., & Francois, B. (2023). Comparison of evolutionary algorithms for solving risk-based energy resource management considering conditional value-at-risk analysis. Mathematics and Computers in Simulation.
- [2] Rodríguez-González, A. Y., Lezama, F., Martínez-López, Y., Madera, J., Soares, J., & Vale, Z. (2022). WCCI/GECCO 2020 Competition on Evolutionary Computation in the Energy Domain: An overview from the winner perspective. Applied Soft Computing, 125, 109162.
- [3] Lezama, F., Soares, J., Vale, Z., Rueda, J., Rivera, S., & Elrich, I. (2019). 2017 IEEE competition on modern heuristic optimizers for smart grid operation: Testbeds and results. Swarm and evolutionary computation, 44, 420-427.
- [4] Lezama, F., Soares, J., Faia, R., & Vale, Z. (2019, July). Hybrid-adaptive differential evolution with decay function (HyDE-DF) applied to the 100-digit challenge competition on single objective numerical optimization. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 7-8).