@article{PAN2026, 
author = {Sen PAN and Xudong WANG and Lin WANG and Yang WANG and Aihua ZHOU and Junfeng QIAO},
title = {Microgrid Scheduling and Optimization Considering Carbon Assets},
year = {2026},
journal = {Distributed Energy},
volume = {11},
number = {4},
pages = {117-126},
keywords = {microgrid, carbon trading, demand response, joint optimization, genetic algorithm},
url = {https://www.sciopen.com/article/10.16513/j.2096-2185.DE.25100370},
doi = {10.16513/j.2096-2185.DE.25100370},
abstract = {The proposal of the national “dual carbon” strategic goals and the improvement of the carbon trading market have placed higher demands on the dispatch and operation strategies of microgrids. Aiming at emission reduction and cost lowering, this paper develops a dual-layer optimization model for low-carbon and economic operation of microgrids, which includes photovoltaic, wind power, diesel generator sets, and energy storage modules, while considering load constraints, charging/discharging constraints of storage devices, and carbon quota constraints. The outer-layer planning model introduces a carbon asset operation mechanism and uses an improved genetic algorithm to optimize microgrid operation strategies, improving economic benefits while ensuring low-carbon system operation. The inner-layer demand response model improves user electricity consumption behavior through incentive measures, optimizes the load curve, and feeds back the user response after implementing demand response to the outer-layer model. The inner and outer layers interact iteratively until both equipment configurations and load curves reach optimum, thereby achieving a bidirectional interaction between load and carbon emissions. Simulation results under multiple scenarios demonstrate that the proposed dual-layer optimization model can significantly reduce microgrid operation costs and carbon emissions. Sensitivity analysis results show that carbon trading prices have a significant impact on operation strategies and costs.}
}