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Abstract

Maintaining thermal comfort within an occupied building requires energy; thus, optimized solution methods for balancing energy use with indoor environmental quality (adequate thermal comfort, lighting, etc.) are needed. Current building temperature control systems do not adequately take in account the adaptive capability of the occupants, but this concept can be used advantageously during implementation of demand response. Demand response programs can affect both the occupants’ thermal comfort from temporary adjustments to space temperature settings. This paper describes ongoing research and field testing of methods to optimize building energy consumption for heating, ventilation and air conditioning applications accounting for human factors such as the thermal comfort by the occupants. Model predictive controllers could serve as powerful tools to optimize the operation of smart buildings and improve human comfort perceptions while helping to better integrate renewable energy systems with increased grid stability.

Practical application: This work outlines how the operation of cooling systems can be optimized with respect to reducing peak demand while still maintaining thermal comfort within acceptable ranges.

Keywords

Demand side management HVAC systems human comfort

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Optimizing thermal comfort considerations with electrical demand response program implementation

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