Evolutionary computation (EC)—a set of optimization algorithms mostly inspired by biological and evolutionary processes—is arguably one of the most successful branches of computational intelligence (CI) used by practitioners all over the world in all areas of engineering.

On the other hand, smart grids are intelligent electrical networks enabling bidirectional power flows and communication between energy sources (traditional, distributed, and renewables) and smart devices (loads, storage, smart appliances). While smart grids promise benefits for users and operators (e.g., the enhance of features such as flexibility, reliability, sustainability, efficiency, etc.), their evolution into a complex socioeconomic environment—requiring a great deal of analysis and planning—is pushing the application of accepted deterministic solutions to its limits. In some cases, these solutions are not suitable for dealing with issues related to high-dimensionality, lack of information, noisy and corrupt data, and real-time requirements, among numerous other real-world considerations.

Thus, EC embracing algorithms that are tolerant to imprecision, uncertainty, and approximation can play a key role as an efficient tool to deal with the challenging scenario encountered in many smart grid applications. This Special Issue aims to address and disseminate the state-of-the-art research and development in the application of evolutionary computational in smart grids.

Dr. Fernando Lezama
Dr. Joao Soares
Prof. Dr. Zita Vale
Dr. Tobias Rodemann
Guest Editors

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