Multi-Objective Control of Residential HVAC Loads for Balancing the User's Comfort with the Frequency Regulation Performance

In this paper, a comprehensive solution is proposed for the optimal scheduling of Heating, Ventilation, and Air-Conditioning (HVAC) loads to balance the user's comfort with the frequency regulation performance. The asynchronous model, which engages several HVAC loads, uses grid frequency measurement devices for primary frequency regulation (PFR). The time when each load detects the frequency disturbance, and its triggering time for frequency response, are asynchronous which could mitigate impulses caused by simultaneous sudden applications or removals of considerably similar loads. The implementation of the proposed strategy provides decision-makers with optimal combinations of frequency deviation thresholds and monitoring periods, in which the monitoring period is denoted as a working period for HVAC load controller. The proposed optimal solution considers the maximum frequency deviation, duration of abnormal frequency, and temperature deviation from the user's set temperature. The Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) algorithm and a fuzzy-decision selection method are developed to obtain the optimal compromise as a Pareto solution of the multi-objective optimization problem for implementing the proposed PFR strategy. The simulation results are presented and discussed for a given system in which 0.2Hz and 5.5s represent the respective typical settings for the optimal frequency deviation threshold and the monitoring period.