Paths and processes in complex electricity markets
The chapter explains the potential of complexity paradigm in describing the dynamics of contemporary electricity markets in their evolution from the traditional centralized form to a more dispersed structure. Current electric power systems, in fact, can be understood as complex adaptive systems in that they are composed by interrelated, heterogeneous interacting elements (social and technical). Demand and supply transactions emerge from the interaction among these elements and self-organized emergent behaviors arise, without the necessary presence of an autonomous control over the whole system. In order to grasp and handle this complexity, models based on equilibrium have been losing explanatory and predictive power while complex systems thinking and modeling seem able to provide useful insights. On the one hand, complexity studies help in conceptualizing how processes which are different in nature and domain (i.e. physical, social, and political) interact and influence each other leading to the emergence of a regular behavior at system level; on the other hand, complexity methods can add value over other modeling methods in addressing questions at the technology-policy-behavior interface by incorporating social and institutional elements. Among these methods, agent-based modeling is the most promising as it allows to describe many heterogeneous agents acting and interacting in an evolving multi-level environment following evolutionary rules of behaviors based on their learning processes. As examples of the explanatory power of agent-based models (ABMs) in the electricity market field, three applications are presented, which are respectively aimed at analyzing the influence of social networks on the adoption of domestic energy technologies; gaining policy- and industry-relevant insights into the smart grid concept; and analyzing how local behavior of elements of an electrical grid influences the resilience of the grid as a whole. In order to further strengthen ABMs, the focus of the modeling exercise should be extended to consumer behavior as the liberalization of electricity markets is driving the electricity production in being determined by the distributed decisions of numerous actors to invest in and deploy (distributed) generation technologies.