Research on a Differentiated Task Scheduling Model for Embedded Operating Systems in the Energy Industry

With the increasing application of embedded systems in the energy industry, the task scheduling problem has become increasingly complex. Traditional scheduling methods, while ensuring task real-time performance, struggle to balance energy efficiency and resource utilization. Against this backdrop, this paper proposes a multi-channel scheduling model based on differentiated scheduling, which achieves dynamic priority calculation mechanisms by considering multiple factors such as task real-time performance, energy consumption, and dependencies. The study collects extensive task execution data based on typical energy industry devices, such as grid terminal devices and wind power controllers, and designs scheduling strategies tailored to these scenarios. Through a multi-dimensional weight-driven priority mechanism and a three-channel differentiated scheduling strategy, the model effectively improves system scheduling efficiency, resource utilization, and energy efficiency control. Simulation results show that the proposed model outperforms traditional scheduling algorithms in key metrics such as task completion rate, response time, and energy efficiency, especially under high load and abnormal conditions. This model provides a flexible and efficient scheduling solution for embedded systems in the energy industry.