Complex Systems for an ICT-enabled Energy System

The European Energy Policy aims at achieving three core objectives: sustainability, competitiveness and security of supply. The achievement of these objectives requires a profound transformation of the energy system that will imply a huge and coordinated effort across several areas. This effort must rely on a sound analysis of different policy approaches, regulatory measures and technological choices. ICT must play a key role as one of the enablers of the energy system transformation, but also as an enabler of new advances in the modelling, analysis and governance of the system.

The energy system is a clear example of a large-scale socio-technical system composed by a myriad of heterogeneous elements, working at different scales, whose interplay gives birth to the overall system and its dynamics. The complex behaviour that emerges from these interactions drives classical modelling methods to their limits:

• Traditional electricity market equilibrium models require excessive simplifications to be computationally tractable, e.g. they assume that players have all relevant information about the other players or disregard the consequences of learning effects.
• Most conventional models of the electricity grid are based on a "centralised control" paradigm that badly fits the arising widespread adoption of renewable energy sources, which tend indeed to be distributed and stochastic in nature. Novel tools are needed to devise control, optimisation and management strategies for the future European Energy System.
• Classical models typically use deterministic forecasts that unrealistically presume we can precisely foresee the evolution of the energy system, they the intrinsic stochastic behaviour of many elements of the energy system and, as a consequence, lacks a comprehensive modelling of its uncertainty.

A characteristic of complex systems is the difficulty to predict its behaviour. This may happen when some elements of the systems are not completely specified (or their behaviour is not well understood) or because the number of variables is so large that it is beyond current simulation capabilities, but in most cases it is due to the fact that the complex, non-linear interactions between a large number of elements result in emergent phenomena that cannot be captured by classical modelling methods. The energy system is a worthy example of such a system, which suggests that its study from a Complex Systems perspective could help overcome the deficiencies of current modelling tools and offer new methods for a realistic, robust and flexible modelling and governance of the Energy system.

Complex Systems ICT-based techniques for the Modelling, Design, Control, Optimisation and Governance of the Energy System

Complex Systems Science has already been applied to the energy system with interesting results:

• Studies of traffic diffusion, spreading in complex networks or propagation of failures are some of the theoretical paradigms readily applicable to an energy system, which has been already described as a complex network.
• Agent-based modelling (ABM) has been applied increasingly along the last ten years to develop electricity market models with adaptive software agents.
• In addition to market models, other ABM applications, such as examining electricity consumer behaviour, developing decision support tools for power market participants or using software agents to perform distributed control, have also begun to be explored in the recent years.

However, much research is yet to be done:

• Recent studies have proven that an important component of complex systems lies in its underlying interaction network, which often has nontrivial topological properties that crucially affect processes occurring on the network. Despite the efforts to develop different complex networks models of the energy system, the knowledge on the processes which result from the interaction between evolving energy infrastructures and energy markets with network constraints is still very limited.
• Models of network growth need to evolve into novel and realistic models able to reproduce the growing mechanisms that are likely to take place in the electricity system, e.g. due to the inclusion of a massive amount of distributed renewable energy sources and the consequent "decentralisation" of the network.
• Though a significant number of research projects have contributed to the increasing literature on ABM for electricity markets addressing specific issues of the complex technological and socio-economic market environment, there is still a number of issues that require further research. As an example, the focus of most researchers has so far been placed on convergence towards stable market outcomes. The out-of-equilibrium dynamics remains to be examined in more detail.
• Calibration and validation of Complex Systems energy models is also a key issue.
• Mechanisms for the integration and autonomous adaptation of simulation and data mining constitute another emerging research field. The potential of grid technologies to offer solutions for large-scale, distributed simulations is to be explored.

ICT-enabled Complex Systems methodologies and techniques emerge as a promising tool to tackle some of the major challenges associated to the design, control, optimisation and governance of the future energy system, e.g. the design of robust and survivable networks, the optimisation of energy generation and consumption strategies or the design of energy markets and regulations. However, the interaction between the Energy, ICT and Complex Systems research communities is still insufficient to translate the academic research into new paradigms for the design and governance of the energy system.

ComplexEnergy aims at contributing to bridge this gap through:

• the merging of the three research communities;
• their active involvement in the identification of the most promising research topics and the formulation of new challenges; and
• the development of a sound roadmap for their implementation through FET programmes in FP7 and beyond.