IoT-Based Smart Energy Management and Load Shifting for Residential Consumption Optimization

Abstract

The increasing energy demand and rising electricity costs have intensified the need for efficient energy management in residential buildings. Load imbalances in power grids and cost surges during peak demand periods are pushing consumers toward more strategic and conscious consumption models. This study focuses on optimizing household electricity consumption through load shifting strategies. To achieve this, a low-cost, Internet of Things (IoT)-based Smart Energy Management System (SEMS) was developed and implemented in a real household. Its performance was then compared with a commercial reference device, revealing an impressive accuracy rate of 99.98%. Electricity consumption data recorded over a one-year period using SEMS was analyzed to assess voltage fluctuations, frequency variations, and energy usage patterns. Daily, weekly, and seasonal consumption trends were identified. Moreover, classifying shiftable and non-shiftable loads enabled a comprehensive evaluation of the load-shifting potential. Scenario-based analyses demonstrated that shifting 25%, 50%, and 75% of shiftable loads to lower-cost tariff periods could result in 9.8%, 17.6%, and 26.1% cost savings, respectively. These findings indicate that SEMS enhances energy efficiency and reduces electricity costs. With its user-friendly interface and low installation cost, SEMS is well-suited for widespread adoption and presents an effective solution for time-based load shifting. Additionally, by encouraging users to adopt more efficient consumption habits, SEMS is expected to contribute to sustainable energy management.

Keywords

• Energy saving
• energy management
• power quality
• load shifting
• internet of things

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