Potential Assessment and Scheduling Method of TCLs Based on Human Body Exergy Analysis

Given the intermittency and fluctuations issues generated by large-scale deployment of clean energy in the power grid, demand-side resources like the temperature control loads (TCLs) to smooth power grid fluctuations is beneficial to ensuring the power grid's stability. Exergy analysis can use human, interior, and outdoor parameters to assess the ideal level of thermal comfort for humans. The human body's ideal temperature range is displayed by an energy analysis, followed by TCLs' peak load capacity range. In this paper, a bottom-up optimization technique for TCLs' potential assessment and scheduling method is presented. Because the user side simply needs to give the bidding curve, it promotes user privacy and security while fully respecting the user's own desire. User's bidding curve is displayed through the utility function of the user. Decentralized TCLs are organized in the form of load aggregator (LA). LA gathers bidding curves from all users to assess the total potential and controls TCLs to attend demand response. A numerical example was used to investigate the mentioned method, which is based on the human body exergy model. The example analysis shows that the TCLs adjustment temperature obtained by exergy analysis is similar to the predicted mean vote (PMV) index, but because the parameters are more comprehensive, it is conducive to the fine description of the control potential. And the TCLs control mode based on bidding curve will not affect the user comfort.