University of Hertfordshire

Sustainability (Journal)

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Mouloud Denai - Guest editor

Mustapha Hatti - Guest editor


New rapidly evolving smart grid technologies such as distributed generation from renewable sources and energy storage, the gradual shift towards the electrification of transport and other sectors of the economy, the emergence of wide-area connected smart metering devices and sensors which are changing end-users behaviour, are leading to unprecedented paradigm shifts which are transforming the landscape of the traditional electricity grid. The electricity grid is becoming increasingly more complex with uncertainties and variabilities occurring at all levels in addition to the overwhelming large volume of information and control variables across the interconnected physical infrastructure. These challenges underscore the need for a new class of fast, robust and scalable tools with large-scale data analytics, multi-objective optimisation and control capabilities to improve the flexibility, reliability and resilience of the electricity grid without falling back to expensive reinforcement.
Computational intelligence techniques are nature-inspired computational methodologies and approaches based on Fuzzy Systems, Neural Networks and Meta-Heuristic Evolutionary algorithms which offer a unique solution to these challenges and are yet to become the key drivers poised to revolutionize the next generation low-carbon utility industry.
The aim of this special issue is to disseminate the latest, on-going research and development in the interdisciplinary area of computational intelligence applications to modeling, control and optimization of renewable energy and smart grid technologies.

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