WCCI-CEC 2020 : WCCI/CEC 2020 Special Session 26 - Evolutionary Algorithms for Complex Optimization in the Energy Domain
Call For Papers
IEEE WORLD CONGRESS ON COMPUTATIONAL INTELLIGENCE (WCCI) 2020
19 – 24th July, 2020, Glasgow (UK)
Organized by Fernando Lezama (firstname.lastname@example.org), Joao Soares, Zita Vale, Ruben Romero
The increasing energy demand that will be derived from developing countries is inevitable. Sustainability and efficiency are, therefore, critical taking into account the known limited world resources. Energy optimization and resource management play a substantial role in achieving the required sustainable growth. In fact, efficient approaches of energy optimization are highly relevant in the planning, operation, and control of energy systems. Many optimization problems in the energy domain are complex and exhibit features such as high-dimensionality, high number of constraints, lack of information, noisy and corrupted data. Also, sometimes such problems present time constraints requiring solutions in near real-time. Hence, achieving good and accurate solutions in a reasonable amount of time remains a challenge for several energy problems. Even the state-of-the-art exact solutions require alternative tweaks that often do not achieve the necessary algorithm performance and applicability. Evolutionary Computation (EC) has already demonstrated good performance in a wide range of applications in the energy domain and emerged to overcome issues of traditional algorithms to find feasible solutions in real-world applications. In fact, the ratio of EC applications in the energy field has been steadily increasing in the last few years and its importance in this field is just starting.
This special session is a follow-up of the previous editions in CEC. Papers concerning the application of EC to real-world problems in the energy domain are welcome. The problems can be focused on different parts of the energy chain (e.g., heating, cooling, and electricity supply) and different consumer targets (e.g., residential or industrial level). Problems dealing with uncertainty, dynamic environments, many-objectives, and large-scale search spaces are more than welcome. This special session aims to close the gap between energy engineers and the latest applications of EC to optimization problems in the energy domain. Besides, this special session is linked to the competition on “Smart grid optimization problems.” Therefore, participants are also welcome to submit the results of their algorithms to our session.
Topics should be related to EC in the energy domain including, but not limited to:
Electric and plug-in hybrid vehicles
Heat and electricity joint optimization problems
Hydrogen economy problems
Multi/many-objective problems in the energy domain
Natural gas optimization problems
Optimal power flow in distribution and transmission
Residential, industrial and district cooling/heating problems
Smart grid and micro-grid problems
Solar and wind power integration and forecast
Super grids problems (continental and transcontinental transmission system)
Transportation & energy joint problems
Distributed evolutionary approaches in the energy domain
Paper submission due: 30th Jan. 2020
Notification of acceptance: 15th Mar. 2020
Camera-ready deadline: 15th Apr. 2020
Author registration deadline: 15th Apr. 2020
How to submit a paper
Select CEC-26 and our SS name under the main topic in the upload paper section
Further related bibliography
 F. Lezama, J. Soares, P. Hernandez-Leal, M. Kaisers, T. Pinto, and Z. Vale: Local Energy Markets: Paving the Path Towards Fully Transactive Energy Systems, IEEE Transaction on Power Systems, IEEE (2018).
 J. Soares, B. Canizes, M. A. Fotouhi Gazvhini, Z. Vale, and G. K. Venayagamoorthy, “Two-stage Stochastic Model using Benders’ Decomposition for Large-scale Energy Resources Management in Smart grids,” IEEE Transactions on Industry Applications, 2017.
 F. Lezama, J. Soares, E. Munoz de Cote, L. E. Sucar, and Z. Vale, “Differential Evolution Strategies for Large-Scale Energy Resource Management in Smart Grids,” in GECCO ’17: Genetic and Evolutionary Computation Conference Companion Proceedings, 2017.