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.


Future Smart Energy Systems

The future smart energy systems includes both local smart distribution grids (characterized by numerous independent participants like prosumers, retailers, distributed-generators, energy storage, electric vehicles as well as technologies still to be invented) and transnational super grids (e.g. connecting large-scale time-varying renewable sources to national power grids and markets).The main characteristics of these systems are:

  • pervasive deployment of information and communication technologies (ICT);
  • integration of renewable generation in support of energy, environmental and other policies;
  • bidirectional communication and power exchange between suppliers and consumers/prosumers;
  • multiplicity of interacting players operating with, and within, a defined architecture/market;
  • enhanced network flexibility and reliability in a future smart energy system;
  • newly required approaches for the monitoring, control and protection/defense of power systems in both space and time.

Smart grid design and implementation needs to embed broader social and cultural considerations in order for smart grids to be successful. Not only smart grids need to be understood as complex techno-socio-economic systems with multiple physical, cyber, social, policy, and decision making layers; also the interaction of those layers with changing external conditions (economic cycles, technological innovation, and prevailing and changing weather and climatic conditions) need to be properly studied. 

The complexity of the smart grid system rests on the multiplicity of interacting players that operate with, and within, a defined environment as independent decision-makers, with autonomous behaviours, goals and attitudes. The actors perform actions via distributed decision making processes which impact the physically constrained network via diverse electronic means (from control and command systems to smart meters).


Complex Systems and Complexity Science

Why complexity sciences? Complexity of the future smart energy systems arises from the multiplicity of interacting players operating as independent decision makers with autonomous behaviours, goals and attitudes. Furthermore technical power systems will operate under varying environmental conditions, exchanging transactions in the power markets. A key concept in complexity science is ‘emergence’. 

At this early stage in the development of  future smart energy systems some emergent properties can already be anticipated. However, noting the complexity of the field we expect that important emergent properties remain unforeseen. Research resting on a robust complexity science foundation will allow stakeholders to rapidly identify and interpret emergent phenomena.
The hypothesis is that complexity sciences can help in identifying tools and techniques for optimal decision making encompassing policy and regulatory design, planning and investment, as well as real time operations. Future smart energy systems research incorporating complexity sciences can provide models and guidelines for future developments, and for recognizing emerging behaviors and challenges.

While much research has looked at the purpose and functionality of smart grid systems, smart grids themselves are merely one system in a ‘‘system of systems’’. As such, complexity is not just an attribute of the smart grid alone, but also of the systems interacting with it. For example, the increasing complexity of weather and climate, the increased complexity of social behaviour and the interaction of individuals guided by narrow economic rationality, the complexities of crisis management and emergency response, and the overall organisational structure needed to manage all those complexities, must all be studied and modelled to adequately meet the emerging challenges to modern society.


Research agenda and initiatives

In this context, in order to understand the complexity of future smart grids, there is the need to move focus and attention from a component-oriented to an interaction-oriented view of the electric power system. The goal of this systemic understanding is to identify tools and techniques for optimal decision-making that will enable society to achieve its energy, environmental, economic and social goals. The framework that should be developed will enable the identification of emerging problems and will provide new solutions and approaches.

    Some of the research questions we aim at addressing are:

    • Can complexity sciences help in understanding, modelling and simulating the emerging smart grid environment within a broader sustainability context including changes in economies, consumer and social behaviour, and climate variability and adaptation?
    • Can sound policy decision making be based on theoretical models and simulation tools derived in the framework of dynamic multi-layer interacting complex systems?
    • How can the multi-layered, multi-actor energy system satisfy economic, environmental, security and social requirements? 
    • How can complexity science help in better addressing those threats and risks affecting future energy systems?
    • How can future technological and social changes be anticipated, managed and integrated in policy and decision making?
    • How can complexity science help in addressing these socio-technical challenges?
    • What is the role played by ‘‘contextual’’ complexity due to the social environment, climate scenarios etc.? How can we properly to address such complexity?



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

    • 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?


    For additional information on related activities, you can check:

    • a kick-off event co-organised by us in 2012 on Smart Energy Grids and Complexity Science
    • the full Report of the aforementioned event with a proposed research agenda