Following the Paris Agreement adopted in 2015, Japan has set a goal of reducing greenhouse gas emissions by 26% from 2013 by 2030. In this context, the business sector is required to reduce greenhouse gas emissions by 40%. The government has been promoting energy saving by some measures. Predicting the effects of each energy-saving policies will make it possible to consider a more effective combination of policies, and it will be useful for studying future policy making. In this study, we developed a simulation that modeled the behavior of tenants and building owners and we used the simulation to predict the effect of energy saving policies on buildings. We also examined changes in energy consumption when tenants prefer energy-efficient buildings. Chapter 2 explained a model in detail. This is a Multi-Agent Simulation model that simulates the behavior of building owners and tenants, who are stakeholders of office buildings. One thousand building owners and about 10,000 tenants act in order to satisfy their own profits. In particular, building owners change their rent, reconstruct and renovate so that they can get more their lifecycle profits. If they think that energy-efficient building is profitable, they change their buildings to the green ones. On the other side, tenants often move to a new office in order to satisfy their utility. If tenants prefer the energy-efficient office, their intention affect the owners’ decision making indirectly. Parameters of utility are estimated so that calculated rental value of buildings simulates the actual value. Using this simulation, we predicted the policy effects of energy saving in building sector from 2020 to 2050 in Chapter 4. The considered policy is “energy-efficiency standard compliance”, “subsidy for new buildings” and “subsidy for renovation”. As a result, we knew some important findings. For example, making energy-efficiency standard compliance severe is effective. It was also found that subsidies for new buildings require a large amount of subsidies to achieve an effect because building a new office requires a lot of money and little amount of subsidies cannot distribute properly to new buildings. Furthermore, we found that subsidies for renovation can be effective at an early stage, but the effects will not continue over the long term because renovated buildings are often reconstructed to the new buildings and the effects of subsidy will end at that time. In addition to those policies, we studied the scenario the tenant's intension increases to save energy consumption in Chapter 5. As a result, tenants’ intension to energy-efficiency makes energy consumption greatly reduced in the end, but it takes time for the effect to appear. We also studied the combination between tenants’ intention and the policies in Chapter 4. The combination with the standard compliance is not very effective. Otherwise, there were the synergistic effect with subsidies for new buildings. It was also clarified that there is a possibility that energy conservation will continue to progress if properly combined with subsidies for renovation. As a future task, it is conceivable to consider specific measures for tenants to intend energy-saving when selecting a building. However, since this simulation is constructed with limited information and includes assumptions and simplifications, there remains a problem in its prediction accuracy. It is also necessary to consider a method for verifying the prediction accuracy while aiming for a more detailed model construction.
