Strategies for agent-based decision optimization for smart energy solutions adoption

Chauca M. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2020) · DOI: 10.18687/laccei2020.1.1.509

Resumen

Agent-based simulation of the decision-making process for the adoption of smart energy solutions can provide evidence for smart energy solution providers to decide on a business strategy that results in the best adoption rate. The adoption rate of smart energy solutions is important to achieving climate goals, such as the Danish goal of 100% renewable electricity production by 2030. This document shows how agent-based simulation can be used to investigate the process of decision-making for the adoption of smart energy solutions. The study investigates a case of the adoption of a demand response program by Danish commercial greenhouse producers. The simulation developed in AnyLogic generates an adoption and information curve for the producer. The results provide the maximum monetary cost to achieve a 50% adoption rate in 5 years.

Instituciones: Universidad Ricardo Palma