Techno-economic analysis, optimization, and dispatch strategy development for renewable energy systems equipped with Internet of Things technology

Abstract

This study examines the benefits of incorporating Internet of Things (IoT) technology in hybrid renewable energy systems. This technology can improve the monitoring of energy storage and consumption as well as remote management capabilities. Employing an IoT controller helps cut down on electricity usage during the electricity grid peak times, ultimately lowering the total cost of distributed energy systems. To determine the optimal size of the residential energy system, a Grey Wolf Optimizer algorithm is conducted and the optimal solution for a total consumption of 225.36 kWh/d is 17 kW of Photovoltaic panels, 49 kWh of battery, and 47 kW of inverter with an overall cost of 90,134 $. The developed predicting dispatch strategy can reduce consumption during the peak of the electricity grid by 91% and prevent blackouts for the investigated area. Furthermore, two different sensitivity analyses are conducted to investigate the effects of changing sell-to-grid price and electrical demand profiles on the optimum solution. The sensitivity analyses for the sale price to the grid from 0.05 $ to 0.15 $ are fully investigated. Also, peak shaving above 90% is repeated for different electrical loads and the optimality of the presented method is confirmed in different load profiles with 225.1 kWh/day, 212.2 kWh/day, and 225.5 kWh/day consumption.