Predictive Model for History Matching of Social Acceptance in Geothermal Energy Projects

One of the biggest challenges in developing renewable energy, such as geothermal energy, is understand-ing how to be accepted by the community impacted by the development. However, very few studies attempted to numerically express the time-dependent process of social acceptance in renewable energy projects. We quantify how social acceptance for a geothermal energy project is acquired from the involved communities. First, we present a compartment model for simulating how the numbers of sup-porters and opponents of developing geothermal energy change over several decades. We then introduce a time-varying index, an effective susceptibility number (Re), similar to the effective reproduction num-ber used in modeling epidemiologic phenomena. Second, we share our findings about the history of the number of supporters and opponents of the geothermal power plant construction project in Japan based on the articles published in local and national newspapers between 1970 and 2020. Our simulation results show that the proposed compartment model could predict documented changes in the numbers of supporters and opponents. Also, the effective susceptibility number (Re) could represent the frequency of interactions among the community members. We suggest that an effort should be made to avoid hav-ing Re < 1 in the community, to maintain a steady increase in the number of supporters to eventually acquire the social acceptance of a geothermal energy project. Our simple but novel approach using the compartment model will help better understand the dynamics and predict the community acceptance process in geothermal and other renewable energy projects. & COPY; 2023 Elsevier Ltd. All rights reserved.