Akademik Veri Yönetim Sistemi
JOURNAL OF BUILDING ENGINEERING, cilt.116, ss.1-45, 2025 (SCI-Expanded, Scopus)
Demand side management (DSM) applications such as identification of electrical appliances based on electricity measurements, demand response and load scheduling have made significant progress in recent years. However, load profiling studies in the existing literature are usually limited to a small number of appliances, and harmonic characteristics are ignored. The primary objective of this study is to fill this gap by developing detailed load profiles that include harmonic characteristics based on real-time measurements. In this context, 1-s real-time data from 26 appliances used in a residential building in Trabzon were collected to create detailed and realistic load profiles. In this pioneering residential-scale study, the harmonic behavior of the appliances, including total harmonic distortion (THD) and individual harmonic currents, was comprehensively analyzed. Additionally, the Mayfly Algorithm (MA) and Artificial Rabbit Optimizer (ARO), which are multi-objective metaheuristic optimization algorithms, were used to evaluate the applicability and effectiveness of DSM strategies. These algorithms were configured to operate with 1-s resolution data and 1-min time steps, and 24-h real-time measurements were conducted for each scenario. The resulting load schedules were comparatively evaluated in terms of energy consumption, peak-to-average ratio (PAR), billing cost, and harmonic distortion. The findings demonstrate that the proposed load planning strategies significantly reduce both energy costs and PAR values, while also revealing the harmonic mitigation effect of DSM on harmonic components. This study provides valuable insights for future research and practical applications by offering a novel, high-resolution dataset and a comprehensive approach for evaluating DSM strategies under real-world conditions. (The link to the raw data: https://doi.org/10.5281/zenodo.17634026).