A seasonal analysis of a long-term dataset produced by an off-grid classroom facility showcasing several solar orientated renewable technologies is presented. The performance of the building's BIPV and battery storage system is characterised and optimisation strategies are discussed. The building experiences a typical oceanic climate defined by a relatively narrow annual temperature range and a high level of annual precipitation, resulting in significant fluctuation in PV performance throughout the year. On clear days, the battery system reaches capacity quickly and PV power output drops to the base load of the building. This curtailment of solar generation highlights the importance of developing control strategies to optimise system performance. Maximising the performance of the building requires accurate methodologies for predicting PV generation and detailed knowledge of building demand profiles. Significant correlation is observed between the solar irradiance, battery state of charge and PV power output, demonstrating the importance of these variables in any solar forecasting model. Demand profiles are deterministic and follow classroom routine. A baseline accounts for persistent systems such as the building management system that are active throughout the day, with demand peaking during occupancy. This information could be incorporated into scheduling algorithms to optimise performance. Consumption is more aligned with the solar generation profile than typical residential buildings that peak in the evening as levels of solar generation fall. The synergistic effect of buildings with different demand profiles could be a mitigation method to minimise the temporal mismatch between solar generation and consumption.
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