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JRC Smart Electricity Systems

Complex System Science for Smart Grids

Through this research stream we aim at investigating the present and future challenges in, and around, future smart energy systems, employing complexity sciences for modeling and analysing the dynamics and interactions of a broad range of actors and components constituting the technical (physical and cyber), socio-economic, and environmental aspects of those systems.

Our view on the proposed research agenda is based on the following points

Our view on the proposed research agenda

  • Unified and unifying approach to future smart energy systems studies based on a complex systems view and methods. We propose an approach that will embrace the technological, social, business and environmental complexity of smart grids in a unified view, aiming at promoting sustainability and resilience through model based problem solving. While much of current research concentrates on the technical functionality of smart grids, these should be treated as "system of systems" with many self-governing components that respond to different economic and environmental issues beyond the pure operational ones. Modeling needs to take the broader techno-socio-economic context into account.
  • Complexities in and around  future smart energy systems. The electricity system infrastructure and its evolution are strictly intertwined with a wider set of contexts (social, technical, economic, environmental). These contexts interact with  future smart energy systems and each other through patterns that are difficult to represent through traditional approaches. Differently from some current research exploring complexity within future smart electricity systems, our approach will also include the complexity of the interactions with the context. As such we take our consideration to the level of "system of systems within systems". We are interested in the complexity that will surround the future smart electricity system as the means towards a full understanding of its overall sustainability.
  • Multi-scale modeling. The challenges coming from the multiscale phenomena in technology, society, business and environment have to be properly addressed with multiscale modeling. The system behaviour needs to be modelled using information or models from different levels. In the end, the approach should include the growing set of links and correlations in, and around, the  future smart energy systems: how society and technology co-evolves, how new business and social models will enable new patterns for the generation, distribution and consumption of electricity, how huge investments can be affordable confronting rapid technical shifts, etc. The availability and relevant use of data is crucial in this step.
  • Evolutionary scenarios for societies: towards sustainability and resilience. Complex systems are simultaneously robust and fragile. The future smart energy systems will possess abilities to self-heal and adjust so as to cope with shocks that would cause a traditional distribution system to fail. These benefits, however, will come at the expense of new vulnerabilities and the risk that relatively small proximate triggers could cause, through a cascade or combination of factors, severe disruptions to operations. The timescales of change are interesting and relevant. Sudden shocks are not the only concern, slow-burning trends and shifts can generate challenges. Will cities be able to cope with such complexities and potentially disruptive scenarios? What will be the social and energetic model be in the next 50 years? We need to fit  future smart energy systems in the foreseeable future anticipating lifestyles and adaptation. Finally future smart energy systems brings benefits and vulnerabilities in the related areas of system safety and security with concern for the protection of individuals but also for systems themselves.
  • Complexity vs. simplicity. The challenge of our approach is to suggest, by means of a complexity science strategy, ways of simplifying the representation and understanding of the system (e.g.: consumers are ready to pay more for simpler solutions). We promote a complexity science approach that strives for simplicity. Through understanding the heterogeneous characteristics in future smart energy systems with complexity science and theories, simple rules and strategies can be designed and tested for a set of representative phenomena and scenarios. Complex global system behaviors can be related to the responsibilities and capabilities of individual system participants, which would be clearly recognized and characterized through models. This type of analysis can influence standardization and regulation at all stages of system evolution.
  • Empowering stakeholders. The objective is the empowerment of stakeholders, such as: consumers, governments and other institutions. Co-dependency of individuals will promote the creation of communities that will share benefits, while receiving and paying fair tariffs for the electricity generated and consumed. There is a need to better understand the energy consumers and anticipate lifestyles in light of their adaptation to new social and economic settings. How long might it take for a fully functional ‘‘smart powered’’ society? In addition, one can foresee that emerging behaviors of prosumers/consumers will require and force the development of new mindsets, which could parallel the emergence of social networks around the Internet. Some key questions could then be posed to society, e.g. How to change environmentally important behaviours?