Microgrid Optimal Energy Scheduling with Battery Degradation

The uploaded package includes 3 parts: 1. Dataset and Matlab Simulator for Battery Aging Tests 2. Learning-ready Dataset and Python Codes for Training a Battery Degradation Neural Network Model 3. Microgrid Optimal Energy Scheduling with Battery Degradation Neural Network in Python <br> <br> If you use these codes for your work, please cite the following paper: Cunzhi Zhao and Xingpeng Li, “Microgrid Optimal Energy Scheduling Considering Neural Network based Battery Degradation”, <em>IEEE Transactions on Power Systems</em>, early access, Jan. 2023. Paper website: https://rpglab.github.io/papers/CunzhiZhao-NNBD-MDS/

上传的压缩包包含三部分内容：1. 面向电池老化测试的数据集与Matlab模拟器（Matlab Simulator）；2. 可直接用于模型训练的电池退化神经网络数据集及配套Python代码；3. 基于电池退化神经网络的微电网最优能量调度Python实现代码。

若您在研究工作中使用本代码，请引用以下论文：赵存志（Cunzhi Zhao）与李兴鹏（Xingpeng Li），《考虑基于神经网络的电池退化模型的微电网最优能量调度》，《IEEE电力系统汇刊（IEEE Transactions on Power Systems）》，2023年1月提前在线出版。论文链接：https://rpglab.github.io/papers/CunzhiZhao-NNBD-MDS/