Abstract

Energy Management Systems (EMSs) play a vital role in managing energy consumption for both utilities and consumers. By using EMSs, utilities can influence on energy usage and ensure a more reliable and efficient grid operation, while consumers can make informed decisions about their energy consumption, leading to significant cost savings and reduced environmental impact. In this paper, a real-time rolling-horizon model is developed for managing energy consumption in public laundries aiming at minimizing energy costs, peak demand, and CO2 emission under the traditional Energy-Based Tariff (EBT) and the Power-Based Tariff (PBT). The developed model can not only reduce energy costs, peak demand, and CO2 emission by optimal task scheduling for washing machines and tumble dryers but also ensure users' preferences for a comfortable lifestyle. To demonstrate the effectiveness of the proposed EMS, several simulations were performed under different scenarios using real data and by a realistic case study in HSB living lab demonstration site. The simulation results reveal that implementing the proposed EMS can significantly decrease energy costs and peak demand in public laundries by 13.59% and 39.40%, respectively, when using the PBT tariff. However, the reduction in energy costs and peak demand is negligible when using the EBT tariff. Likewise, the results indicate that using the EMS and changing tariffs have a minimal impact on CO2 emissions reduction.

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