IEEE World Congress on
Computational Intelligence 2018
Rio de Janeiro, Brazil, 08-13 July 2018

Special Session on
Computational Intelligence for
Energy Storage Systems Modeling and Management

Abstract & Topics:

Energy Storage Systems (ESS)s have become widely pervasive in several sectors, both in the civil and in the industrial engineering fields. Among the several applications, the most critical ones regard the storing of energy in the future Smart Grids and microgrids, and the power sourcing for Electric and Hybrid Vehicles. In this context, the management of the ESS represents a crucial task in order to guarantee efficient, effective and robust energy storing. In order to achieve a safe and reliable usage of ESSs, it is important to synthesize suitable models capable to predict the cell behavior in order to avoid damages, to estimate the State of Charge (SoC) and the State of Health (SoH), and to perform the cells equalization. Moreover, the design of efficient and effective algorithms for optimal energy flows routing in Smart Girds and microgrids is a challenging task, especially in presence of ESSs. Computational intelligence techniques represent a powerful approach to face the abovementioned tasks, allowing to deal with the strong nonlinear and dynamic behavior of electrochemical cells, as well as to design Energy Management Systems (EMS) able to cope with nonlinear and time variant systems, such as microgrids and Smart Grids, especially in presence of stochastic renewable energy sources.

Topics of interest include (but are not limited to) applications of Computational Intelligence techniques (Neural networks and Machine Learning, Evolutionary Optimization and Fuzzy Systems) to the following problems:

-       ESS modelling

-       ESS parameters identification

-       ESS state of charge estimation

-       ESS state of health estimation

-       ESS cell balancing

-       Neural Networks for non-linear system identification

-       EMS design for Smart Grids and micro grids in presence of ESSs

-       EMS in hybrid and electric vehicles

-       EMS in Smart Buildings

-       Computational Intelligence techniques for complex systems modelling

PDF version of this Call for Papers can be downloaded here.