Hongvityakorn, B.; Jaruwasupant, N.; Khongphinitbunjong, K.; Aggarangsi, P. Achieving Nearly Zero-Energy Buildings through Renewable Energy Production-Storage Optimization. Preprints2024, 2024090088. https://doi.org/10.20944/preprints202409.0088.v1
APA Style
Hongvityakorn, B., Jaruwasupant, N., Khongphinitbunjong, K., & Aggarangsi, P. (2024). Achieving Nearly Zero-Energy Buildings through Renewable Energy Production-Storage Optimization. Preprints. https://doi.org/10.20944/preprints202409.0088.v1
Chicago/Turabian Style
Hongvityakorn, B., Kitiphong Khongphinitbunjong and Pruk Aggarangsi. 2024 "Achieving Nearly Zero-Energy Buildings through Renewable Energy Production-Storage Optimization" Preprints. https://doi.org/10.20944/preprints202409.0088.v1
Abstract
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.
Keywords
Nearly Zero-Energy Buildings (NZEBs); Energy optimization; Behavioral Energy Consumption
Subject
Engineering, Energy and Fuel Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
