An Optimal Load Scheduling Approach for Residential Energy Consumers of Bangladesh based on Time of Use Tariff Scheme

The rapid growth of urbanization and increasing energy demand in Bangladesh have posed significant challenges for maintaining a reliable and sustainable power supply. This study contributes to the development of a practical and efficient load scheduling approach for residential energy consumers in Bangladesh. In order to reduce electricity costs and flatten the load curve, appliances are categorized and shifted from busy hours to off-peak hours through the process of load scheduling. Time-varying tariff schemes are uncommon in our country, but by charging more during peak hours and encouraging users to alter their consumption patterns, they help to lower demand. For our work, Time of Use (TOU) tariff rate was chosen. The objective was to develop an efficient scheduling algorithm that minimizes electricity costs while considering consumer comfort and the constraints imposed by the TOU pricing structure. Firstly, a load profile was created by gathering data from residential areas. Then an objective function was developed to minimize electricity costs and find optimal scheduling that maintains user comfort as well as reduces Peak-to-Average Ratio (PAR). The Particle Swarm Optimization (PSO) algorithm was then applied to solve the optimization problem, aiming to minimize the total electricity cost while satisfying comfort and convenience constraints. MATLAB was used to simulate the PSO algorithm and evaluate its performance in generating optimal load schedules for residential energy consumers. The simulation results demonstrate the effectiveness of the proposed approach in reducing electricity costs by 14% for consumers while considering their comfort requirements and keeping the schedule within two hours of the original consumption time. Also, a reduction in loads during peak hours by shifting them to off-peak hours is also observed.