Optimising the scheduled operation of window blinds to enhance occupant comfort

Artificial lighting can increase a energy consumption. On the other hand, the availability of daylight in occupied spaces can reduce energy consumption while positively contributing to occupant wellbeing. However, daylight entering the space through windows needs to be reconciled with heat loss during winter and heat gain during summer, which may affect thermal comfort. In this research, a genetic algorithm is used to optimize the operation schedules of window blinds in a school classroom to enhance occupant visual comfort level. The objective of the optimization study was to reduce the energy consumption while maintaining the daylighting illuminance within the range of 100 lux to 2000 lux. EnergyPlus simulation software was employed as the daylighting and thermal performance calculation engine. The findings evidenced that the proposed genetic algorithm based schedule optimization reduced the HVAC and lighting energy consumption while giving preference to The results showed that the performance of the discussed method could also depend on different seasons. The genetic algorithm reduced the negative impact of solar gains on energy consumption in summer by closin

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