JAILCD2026-020: A Prototype Digital Twin Model for Simulating Community Energy Behaviour: A Case Study of Lhong Him Kao, Chiang Mai

Abstract

Creative craft villages in Thailand exhibit distinct energy consumption patterns shaped by variable craft production activities, traditional architecture, and seasonal tourism dynamics. The continued growth of these villages further increases energy demand and poses challenges to long-term energy sustainability. Despite the high potential for solar energy in Thailand, such communities often lack analytical methods for assessing renewable-energy integration or understanding how built-form morphology influences energy behaviour. This study develops a Prototype Digital Twin (PDT) for simulating hourly load profiles, solar photovoltaic (PV) generation, and shading conditions in Lhong Him Kao, a creative craft village in Chiang Mai. The Digital Twin integrates (1) architectural morphology modelling based on simplified 3D geometry and sun-path-based shading assessment, (2) synthetic load generation for residential, craft workshop, and café typologies, and (3) a numerical simulation engine for PV–load interaction and scenario analysis. Two PV adoption scenarios were evaluated, involving PV installation on five buildings and ten buildings within the community. The results indicate that daytime craft workshops provide the strongest PV–load matching, while traditional roof geometries offer favourable tilt angles and solar exposure. Scenario simulations demonstrate approximately 13–28% reductions in annual energy consumption, around 1.25–2.69% reductions in peak electrical demand, and corresponding reductions in carbon emissions proportional to the decrease in grid electricity use. Overall, the prototype demonstrates that a low-data, architecture-integrated Digital Twin can effectively support early-stage community-energy planning in rural creative villages. This PDT forms a foundation for future Digital Twin models incorporating passive cooling, demand-side management, and multi-scenario optimisation.