This research focuses on optimizing renewable energy systems to achieve Nearly Zero-Energy Building (nZEB) Level 1 status, defined as reducing energy consumption by 87.5% to 100%. The major objectives are to explore the impact factors in the optimization of energy storage systems (ESSs), solar PV and ESS capacities, as well as energy consumption patterns. This study is based on monitoring data from an office building in Thailand with a 120 kW peak load and a 40 kW average load, equipped with a 160 kW photovoltaic (PV) system and 45 kWh from ESS. This study is based on comparing a simulation of a renewable energy system, particularly from unutilized solar energy, with building load demand to optimize the best system suitability for achieving nZEB Level 1 status. The results indicate that a 200 kW PV system combined with a 275 kWh ESS and a 250 kW PV system with an ESS capacity of 175 kWh can adequately supply the required clean energy demand. These findings provide insights on optimizing factors of renewable energy systems for buildings aiming to achieve sustainability targets. This work has summarized a framework including optimization impact factors with financial aspects which can be applied to similar cases. In addition, an analysis of working-day load profiles and appliance usage patterns has been performed to provide broader consumption insights. This approach identifies trends in HVAC, lighting, and electronics consumption, enabling the optimization scheme to be adapted to buildings with varying load patterns. Additionally, this study examines the effects of building operation hours on energy consumption. By adjusting operational schedules based on these insights, different renewable energy system capacities can be re-estimated to ensure achievement of the desired nZEB Level.

This research focuses on optimization of coupled solar production and battery storage system to achieve Nearly Zero-Energy Building (nZEBs) based on building load behavior patterns. Moni-toring data from an office building with 120kW peak and 40kW average load consumption equipped with a 160kW solar photovoltaic (PV) system and a 50kW-45kWh energy storage system (ESS). The primary objective is to the primary objective is to analyze collected data from existing system and setup guideline to optimize ESS capacity to maximize clean energy consumption and thus minimize excess production losses, progressing the building toward Nearly ZEB Level 1 status (87.5%-100% energy usage). The study outcome has identified parameter impacts and demonstrates additional optimized cases with various PV and ESS installed capacity. Further analysis is performed based on working day load profile and appliance patterns. This ap-proach aims to learn the usage HVAC, lighting, and electronics, enabling the optimization scheme to be applied to buildings with different load patterns. Additionally, the analysis predicts other building behavior patterns and optimized clean energy system. The findings are then validated against actual data and the results demonstrate good model accuracy, especially daytime predic-tion. These insights also provide guidelines and strategies for further interventions on HVAC operations and adjusting concerned schedules to achieve desired ZEB level.