Cost optimization of electrical usage with customizable comfort considerations

摘要

Optimized control of the environment features such as temperature is often generalized for the majority of people; however, a specific user might not find the controlled results are optimal for him/her. Based on the popular Predicted Mean Vote (PMV) as an indoor thermal comfort index and real-time human feedback, this work presents a cyber-physical system with user-optimized control strategy that trades off between power consumption and user-specific comfort. First the range of PMV values is dynamically revised according to an individual's preference. Then particle swarm optimization (PSO) is used to find a thermal setting for air-conditioners such that within the user acceptable range of thermal comfort a user-given tradeoff between the power consumption and thermal comfort is achieved. Compared with fixed PMV settings, the proposed control method can more effectively maintain the PMV value within the occupant comfort range. If the user likes a warmer thermal comfort environment, the system can save over 25% of power consumption. If the user likes a cooler thermal comfort environment, the system will spend more than 15% of power consumption, but gain more than 68.3% of comfort.