Embracing the Complexity of Cities: Agent-Based Modelling for Energy Planning and Policy

The narrative of energy consumption in cities of developing nations is complex, yet pivotal in the pursuit of a sustainable future. On the one hand, there is excessive energy demand for catalysing socio-economic development, and on the other, there is heightened environmental turmoil due to high emissions and resource consumption. Various approaches and policy interventions have been attempted to address these shifting imbalances, the bulk of which proved to be underperforming and ill-suited, primarily because of a lack of comprehensive understanding of the complexity of these issues. This study proposes an agent-based computational model for simulating household electricity consumption in cities, developed using NetLogo 6.2.0. The model helps identify the complex interplay of different variables and processes, and their significance in determining household electricity consumption as an emergent urban phenomenon. Through model simulation of four Indian cities—Delhi, Mumbai, Bangalore and Bhopal—it was identified that the two most significant urban processes determining their household electricity consumption patterns are growth in population and growth in air-conditioner ownership. Further, it was identified that widely practised domestic solar panel installation policies in various states of India are a short-sighted approach towards containing future household electricity demand. The capacities of the model in conducting various sophisticated experiments and generating ‘what-if’ scenarios can aid users in conceiving fitting and lucrative solutions to address the underlying issues of electricity consumption in cities of developing nations. The model is original and unique, developed in a user-friendly and flexible manner to ensure that it can serve as a theoretical and methodological base for developing future models.