COORDINATED MULTI-OBJECTIVE OPTIMIZATION FOR GREEN POWER SYSTEM SCHEDULING AND CONSUMPTION WITH DIVERSE DEVICES

This study proposes a coordinated multi-objective optimization framework for scheduling and managing power consumption in green power systems with diverse energy devices. The system incorporates renewable sources, energy storage units, and controllable loads to enhance energy efficiency, reduce costs, and minimize environmental impact. A multi-objective evolutionary algorithm is employed to balance conflicting goals such as operational cost, emission reduction, and user comfort. Device-level coordination, including electric vehicles, HVAC systems, and smart appliances, is integrated to enable demand-side flexibility. Simulation results demonstrate the effectiveness of the proposed strategy in achieving optimal scheduling under dynamic load and generation conditions, contributing to the realization of intelligent, low-carbon energy systems.