Safe Transitions in Complex Systems

Abstract

Complex systems, including energy and transportation systems, constitute a crucial part of modern societies’ critical infrastructure. It is imperative to ensure their stability even during periods of crisis or fundamental transformation, such as sustainability transformation. It is difficult to anticipate how individuals will respond to policy interventions aimed at preserving stability, for example, by banning cars from congested roads, or to policy interventions aimed at fundamentally altering the system, for instance, by promoting renewable energies. A conflict of interest may occur at both an individual and institutional level if sustainability measures, such as increasing the number of electric vehicles or photovoltaic systems, jeopardize the stability of the system, for example, by increasing grid volatility. Furthermore, research into complex systems has demonstrated that they tend to develop nonlinearly rather than linearly, making them difficult to predict. Agent-based modeling (ABM) has emerged as a valuable method to comprehend the dynamics of complex socio-technical systems. Moreover, ABM enables us to anticipate future outcomes and evaluate the effectiveness of different policy measures aimed at enhancing safety or promoting sustainability (or both). The chapter briefly introduces the ABM concept and the SimCo simulation framework, developed at TU Dortmund University. SimCo is grounded in analytical sociology, focusing on people’s everyday practices, bounded-rational decision-making and on governance concerns. Additionally, this chapter will present the outcomes of several simulation experiments to address the question of how to achieve safe transformations of complex systems.