Modelling of home energy management system using heuristic optimization for sustainable energy utilization - Most Khadija Parvin, Ms. (2023)
The continuous increase in home energy tariffs has led to the effort by homeowners to search for solutions to their increasing electricity bills. In the same context, minimizing power consumption can contribute to the sustainability of energy and the environment. Therefore, the proper management of energy in the domestic sector is a vital element for creating a sustainable environment and cost reduction. The emersion of smart grids and the rising electricity demand have introduced new advantages for home energy management system (HEMS) for the objective of decreasing electricity usage. Prior works in scheduling domestic appliances focused on saving power consumption and decreasing energy cost without considering user comfort. Moreover, HEMS energy consumption management attainment is not balanced between energy cost, consumption, and wellbeing. Therefore, there is a need to build up an intelligent HEMS that considers demand response (DR) enabled domestic loads, user comfort, and the use of a suitable optimization technique to determine the optimal scheduling of residential loads. This research aims to develop an intelligent HEMS considering the Malaysian environment, electricity tariff, and home occupancy. In this study, the commonly used domestic household appliances such as heating ventilation and air conditioning (HVAC), electric water heater (EWH), dimmable lamp, TV, and PC, were modeled and analyzed using Simulink/Matlab. The developed models analyzed the energy consumption of appliances and cost scenarios during peak, off-peak, and both peak and off-peak hours. A fuzzy logic controller (FLC) was developed for the HEMS to perform energy utilization estimation and cost analysis. Three home appliances namely, HVAC, EWH, and dimmable lamp for HEMS were modelled using FLC taking the peak and off-peak tariff of the Malaysian grid into consideration. The simulation results show that the developed models can manage power consumption and cost reduction efficiently. Using the developed FLC controller, the cost and energy savings of the peak period are 19.72% and 20.34%, 26.71% and 26.67%, 37.5% and 33.33% for the HVAC, EWH, and dimmable lamps, respectively. In summary, the FLC shows good performance to reduce the cost and power consumption toward efficient HEMS. However, the performance of FLC is based on the suitable selection of the membership functions (MFs). To solve the MF constraint of FLC, an improved particle search optimization (PSO) algorithm is proposed for HEMS to determine the optimal schedule operation of home devices at specific times of the day. The developed FLC-based PSO provides an optimal controller output for predicting optimal schedules of the HEMS. To validate the optimal performance, FLC and optimized fuzzy results were compared where it shows that the FLC-based PSO can control the home appliances more significantly compared to FLC only. The obtained results also showed that the FLC-based PSO scheduled controller achieved higher energy saving compared to fuzzy only. Therefore, the fuzzy-based PSO optimum scheduled controller for the HEMS minimized power by 36.17% per day for HVAC, 54.54% per day for EWH, and 62.5% per day for a dimmable lamp, respectively. The results also demonstrated that the energy cost-saving at the peak period for the three appliances are 36.54%, 55.76%, and 58% per day for HVAC, EWH, and dimmable lamp consumption and cost upon maintaining the customer's high comfort level. In sum, the fuzzy-based PSO shows a better performance to reduce the cost and power consumption toward efficient HEMS. Thus, the developed fuzzy-based heuristic optimized controller of the home energy management system is useful for sustainable energy utilization.