{'fraction_non_alphanumeric': 0.022794117647058822, 'fraction_numerical': 0.0, 'mean_word_length': 5.737623762376238, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Simulation-based Optimization of Energy Consumption and Discomfort in Multi-Occupied Offices Considering Occupants Locations and Preferences

Among the factors affecting the energy consumption of buildings, occupancy-related factors are the least understood due to the uncertainty and complexity associated with them. As a result, there is a rise in this area of research focusing on the effect of occupants (e.g., their location, behaviour, etc.) on buildings’ energy consumption. Focusing on office buildings, researchers have suggested several occupancy monitoring techniques in order to minimize the energy usage of existing office buildings. However, a limited number of studies have been conducted to consider proper sensing techniques to distinguish between different occupants in multioccupied offices and to apply local control to adjust the lighting and HVAC systems based on the occupancy information. This research proposes a simulation-based multi-objective optimization of the energy consumption in office buildings considering occupants’ locations and preferences. The objective functions are minimizing the energy consumption and the occupants’ discomfort hours simultaneously by applying local control of the Heating, Cooling, and Air Conditioning (HVAC) system. A case study is presented to demonstrate the feasibility of the proposed method.