With the increasing penetration of distributed energy resources, such as electric vehicles (EVs), photovoltaics (PVs) and prosumers, it becomes more challenging for the central system to balance the demand and supply in real-time. Local energy markets and smart network services are seen as an efficient and promising solution to enable autonomous and decentralised demand and supply balancing at local level to share the burden of whole-system balancing. As a result, there are greater interests in investigating new market mechanisms and transactive energy management to support local energy trading and balancing, and how these mechanisms may impact on wholesale energy markets and incumbent suppliers, generators and network operators, and how they may support the integration of high volume of renewable energy and demand responses.

These new requirements in transactive energy management and energy markets call for advanced computational intelligence techniques to find efficient solutions from distributed and large-scale energy optimization to advanced energy forecasting. This special session aims to showcase the latest development in advanced applications of computational intelligence to smart energy management and smart energy markets. Topics of interest include, but are not limited to:

● Computational intelligence techniques in smart building/home energy management

● Energy management in energy-intensive sectors such as transportation and manufacturing

● EVs and microgrids modeling

● Transactive approaches to the demand flexibility management

● Novel demand-side management and demand response schemes

● Game-theoretic modeling and optimization in energy management and energy markets

● Auction design for decentralised energy markets

● Local energy trading with distributed energy resources

● Demand response/ renewable energy integration in the wholesale market

● Integration of wholesale and local energy markets

● Computational intelligence approaches for energy management and smart energy markets

● Hybrid computational intelligence for energy management and smart energy markets

● Stochastic/robust optimization and control in the market-driven smart energy systems

● Distributed/ decentralised optimization and control in the market-driven smart energy systems

● Hierarchical optimization and control in the market-driven smart energy systems

● Other advanced operation, control and management methods in the market-driven smart energy systems