Optimization Function to Integrate the User’s Comfort Perception into a Smart Home Controller

What is it about?

This paper proposes the modeling of a comfort function that takes into account the user’s perceptions using fuzzy logic. The proposed function is integrated into an Smart Home Controller (SHC) that uses PSO for scheduling residential loads, and aims at economy and user comfort as multiple objectives. The analysis and validation of the proposed function includes different scenarios related to economy–comfort, load shifting, consideration of energy tariffs, user preferences, and user perceptions. The results show that it is more beneficial to use the proposed comfort function method only when the user requires SHC to prioritize comfort at the expense of financial savings. Otherwise, it is more beneficial to use a comfort function that only considers the user’s comfort preferences and not their perceptions.

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Why is it important?

This paper presents the following contributions to the state-of-the-art with respect to residential comfort analysis: - Introduction of a novel residential comfort function capable of integrating parameters associated with the human perceptions of temperature and humidity. - A multi-objective SHC model that relies on PSO for scheduling the residential loads and integrates the proposed comfort function by means of fuzzy logic. - Improvement of thermal comfort indices, the computational burden of the SHC, the efficiency of the PSO algorithm, and economic savings when compared with [5,6]. - Supplemental materials are available at GitHub® through https://github.com/jonathacosta/SmartGrid/tree/main/SCC-SHC accessed on 15 February 2023, including our source codes, allowing prompt reproduction of our results.

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