We have developed an energy-saving operations system featuring remote operation of central monitoring equipment installed in a building. This system applies robotic process automation to remote operation to automatically perform energy-saving operations on behalf of the operations manager. Furthermore, as another feature, the system requires only a local area network to connect to the central monitoring equipment enabling automatic operation to be performed regardless of the specifications of the central monitoring equipment. The items targeted for energy-saving operation by this system are the optimal operation of a heat source system, setting of the supply water temperature of heat source equipment, setting of room temperature, and setting of outside-air intake volume. At present, the operations manager has the role of performing these energy-saving operations, but finding the optimal value for each of these operations is a difficult task. An operations manager, moreover, is responsible for tasks other than facility operations such as maintenance management, so changing optimal settings accurately at regular intervals on an ongoing basis can be quite a burden. This system uses robotic process automation technology, so it is capable of performing all energy-saving operations that can be executed by the central monitoring equipment. We installed this system in a large-scale shopping mall and performed energy-saving operations on outside-air processing units. In this trial, we achieved a 44% reduction in the amount of energy required for outside-air processing and a 47% reduction in CO₂ emissions.

Comfort temperature is important to investigate because the chosen office indoor temperatures affect the energy used in a building, and a thermally comfortable environment makes the occupants be more productive. The effects of temperature on comfort are broadly recognized for thermal comfort. Japanese office buildings are well equipped with air-conditioning systems to improve the thermal comfort of the occupants. The main objectives of this research were to compare the winter comfort temperature in mixed mode (MM) and heating, ventilation and air-conditioning (HVAC) office buildings and to investigate the relationship between the comfort temperature and the indoor air temperature. This study measured the thermal environmental conditions of the office buildings and surveyed the thermal comfort of the occupants. The field survey was conducted during winter in seven office buildings located in the Aichi prefecture of Japan. In total, 4466 subjective votes were collected from 46 occupants. The result suggested that the occupants were found to be more satisfied with the thermal environment of MM buildings than that of HVAC office buildings. Overall, 95% of comfort temperatures were in the range 22~28 °C in MM and HVAC buildings, which were higher than the indoor temperature of 20 °C recommended by the Japanese government. The comfort temperature was highly correlated to the indoor air temperature of the MM buildings than to that of HVAC buildings. This indicated that the occupants were more adapted towards the given thermal environment of MM buildings.

A field survey of indoor environmental measurements and questionnaires on thermal sensation, overall comfort, and behaviors was conducted in four office buildings in Japan by visiting each office every month over a duration of more than a year during the coronavirus disease 2019 (COVID-19) pandemic. The indoor environment was measured concurrently. We obtained 1047 votes from office workers in their 20s to 60s. The regression and Griffiths’ methods were used to calculate the indoor comfort temperature. A logistic regression analysis was used to develop the occupant behavior model. Over 70% of the occupants found the indoor environment comfortable at a mean comfort temperature of 23.2 to 25.9 °C. Gender differences were observed in thermal sensation and overall comfort, but a gender difference was observed only in the cooling mode for the indoor comfort temperature. An adaptive model was developed for the office buildings in Nagasaki city to predict the indoor comfort temperature from the outdoor air temperature. The proportions of heating, cooling, and fan usage can be predicted from the outdoor air temperature using a logistic regression analysis. The adaptive model and occupant behavior model are useful for the indoor temperature control of the existing buildings and thermal simulation of the new building design.