Agent-based Decision Making for Adoption of Smart Energy Solutions

Abstract

Agent-based simulation of the decision-making process for adoption of smart energy solutions can provide evidence for smart energy solutions' providers to decide for a business strategy which results in the best adoption rate. The adoption rate of smart energy solutions is important in achieving climate goals, such as the Danish goal to have 100% renewable electricity production by 2030. This paper shows how agent-based simulation can be used to investigate the decision-making process for adoption of smart energy solutions. The study investigates a case about Danish commercial greenhouse growers' adoption of a demand response program. The simulation outputs an adoption curve and grower information. The results provide the maximum monetary cost for achieving an adoption rate of 50% in 5 years.