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International audience ; The global consequences of climate change calls for adoption of new technologies across all sectors of society. However, it is important to know how fast new technologies are adopted to reach the political climate goals. This paper presents a method for designing agent-based simulations for studying technology adoption. The method includes the design of simulation population, agent adoption logic, and external factors influencing agents' adoption decisions. A case study of the Danish commercial greenhouses' adoption of a smart energy solution is investigated. The result is presented with Roger's technology adoption curve which can be used to demonstrate the desired adoption rate by regulating different simulation parameters. The adoption rate of 50% with the return on the investment of 3 and 5 years is investigated. The greenhouse segment of growing pot plants with an area of more than 20,000 m2 is found to be the innovators. The simulation result shows that the population categories of the 'innovators', 'early adopters', and 'early majority' don't change between the return on investment time of 3 and 5 years. Furthermore, the relation of the return on investment time and the initial cost is close to linear. Hence, a lower/higher initial cost will result in a shorter/longer return on investment time.

International audience ; The global consequences of climate change calls for adoption of new technologies across all sectors of society. However, it is important to know how fast new technologies are adopted to reach the political climate goals. This paper presents a method for designing agent-based simulations for studying technology adoption. The method includes the design of simulation population, agent adoption logic, and external factors influencing agents' adoption decisions. A case study of the Danish commercial greenhouses' adoption of a smart energy solution is investigated. The result is presented with Roger's technology adoption curve which can be used to demonstrate the desired adoption rate by regulating different simulation parameters. The adoption rate of 50% with the return on the investment of 3 and 5 years is investigated. The greenhouse segment of growing pot plants with an area of more than 20,000 m2 is found to be the innovators. The simulation result shows that the population categories of the 'innovators', 'early adopters', and 'early majority' don't change between the return on investment time of 3 and 5 years. Furthermore, the relation of the return on investment time and the initial cost is close to linear. Hence, a lower/higher initial cost will result in a shorter/longer return on investment time.

International audience ; The global consequences of climate change calls for adoption of new technologies across all sectors of society. However, it is important to know how fast new technologies are adopted to reach the political climate goals. This paper presents a method for designing agent-based simulations for studying technology adoption. The method includes the design of simulation population, agent adoption logic, and external factors influencing agents' adoption decisions. A case study of the Danish commercial greenhouses' adoption of a smart energy solution is investigated. The result is presented with Roger's technology adoption curve which can be used to demonstrate the desired adoption rate by regulating different simulation parameters. The adoption rate of 50% with the return on the investment of 3 and 5 years is investigated. The greenhouse segment of growing pot plants with an area of more than 20,000 m2 is found to be the innovators. The simulation result shows that the population categories of the 'innovators', 'early adopters', and 'early majority' don't change between the return on investment time of 3 and 5 years. Furthermore, the relation of the return on investment time and the initial cost is close to linear. Hence, a lower/higher initial cost will result in a shorter/longer return on investment time.