The well-scheduled operation of heating and cooling in detached residential houses in Japan means both the thermal insulation performance and the thermal capacity of the house affect energy consumption. Many previous studies have shown energy consumption differences between houses with different thermal insulation performance. On the other hand, other studies have shown heat load differences between houses with different thermal capacities, although few have examined the energy consumption differences between such houses. Therefore, this research uses a simulation to show the impact on energy consumption of various thermal capacities. The house simulation focuses on a representative detached house used for the national energy saving model of TRNSYS. The air conditioner simulation uses the COP model, which is also used for the national energy saving model. The simulation is carried out for a year with 5 minutes intervals. The room temperature settings are 20 degrees Celsius for heating and 27 degrees Celsius for cooling. To evaluate the effect of thermal capacity differences on energy consumption, six thermal capacity patterns are considered. One is taken from standard building construction and the others are introduced from ISO13790. Based on the simulation results, it was found that the annual total energy consumption for heating and cooling decreases as the thermal capacity of the house increases. In case of “very heavy” thermal capacity, which has the highest thermal capacity, the annual energy consumption was reduced by 11% for cooling and by 15% for heating. These results show that a higher thermal capacity decreases energy consumption for heating and cooling even though their thermal insulation performance is same. To evaluate the effect of thermal capacity differences on energy consumption under various scenarios, six levels of thermal insulation performance are considered, taken from the Japanese energy saving law. Based on the simulation results, the annual total energy consumption for heating and cooling decreases as the thermal insulation performance increases. In addition, energy consumption decreases as thermal capacity increases under the same thermal insulation performance. For the standard construction, which has the lowest thermal capacity, the reduction rate from increasing the thermal capacity tends to be larger in case of higher thermal insulation performance.

Few studies have been conducted on smart business continuity management (SBCM) for buildings/facilities in near-future cities. It is thus important to clarify how the environment can improved for future business continuity management and what risks are entailed by investigating actual approaches currently practiced as the foundations of business continuity in the near-future. In this study, SBCM for buildings/facilities in near-future cities is examined. In this context, the current situation in Tokyo, the capital city of Japan, is analyzed from the viewpoint of disaster prevention and safety to determine what is required for future SBCM. Here we refer to two recent public bulletins, “Tokyo Disaster Prevention Plan (Earthquake)” and “New Tokyo Made with the Metropolitan First - The Action Plan for 2020”. The Tokyo metropolis by 2050 is envisaged and the risks related to buildings/facilities are examined. The findings of this study are as follows. (1)Through an extensive examination of SBCM in near-future cities, existing and long emergent risk factors are recognized. In other words, as long as existing BCM measures continue to be carried out, new challenges and existing difficulties must be considered. Thus, the necessity for additional research on this subject is confirmed, and important points and procedures of prior studies are clarified. (2)It is difficult to determine whether a particular SBCM risk factor is eliminated at a given time because they may be evaluated differently depending on relevant local characteristics and corresponding technologies both current and future. Risks are classified according to ①whether they are being grasped at the moment, ② whether countermeasures exist, ③ whether effective measures will be implemented by 2050, and ④ whether new measures are currently available and prioritized. Then, they are arranged into patterns. (3)“It requires a long time for disaster restoration after an earthquake because ICT, IoT, and efficient automatic operation, which are used regularly for lifeline, transportation, and logistics are not available and no experts are around. This describes a critical situation assuming that risks are not and will remain unsolved by 2030. Issues like this should be examined intensively and treated as new risk factors,which become more evident during emergencies as technology advances. (4)For example, it is desirable in terms of workability, efficiency, reliability, and cost performance to integrate the seismic disaster recovery assistance system with advanced real-time monitoring systems for buildings/facilities and people to ensure their security. In this manner, the systematic integration of smart technology into SBCM should be promoted.

Real-time pricing is a feature of demand response schemes for future smart grids. From the demand side, the coordination of load management conforming to rapid power price changes is necessary. Studies on building multi-type air-conditioners are finding ways to predictively suppress power during high-priced time zones based on advance charge information. Thus far, methods of suppressing the operation or the pre-cooling operation in outdoor unit blocks have been proposed based on the comfort priority of each air-conditioning area. Here, we propose a new area priority prediction control that can define a complex area priority over multiple outdoor unit blocks, and show the degree of improvement by experiment and simulation. This study attempts to optimize a number of multi-unit-type air-conditioning facilities installed in an office building using a complex evaluation function that incorporates the power cost, room temperature comfort, and total power consumption. Because an experiment lacks reproducibility, simulation experiments with different electricity pricing patterns are carried out. An original air-conditioner emulation model is developed and used to conduct the simulation experiments.