Analyzing Optimal Battery Sizing in Microgrids

The dataset is generated using the mixed integer linear programming (MILP). The MILP is a linear optimization problem extensively used while solving optimal sizing and selection problems of Distributed Energy Resources (DERs) and energy storage in microgrids. The problem is solved by the power balance of different DERs and energy storage as compared to the total load. Random sizes are entered into respective matrices to form a generation mix and each generation mix is then compared to fully satisfy the load demand. The data set for a residential microgrid with 24255 samples and 40 parameters is extracted using a MILP- based microgrid model. The extracted parameters and their description is enclosed as “Dataset generation techniques factors and external factors.pdf”. The dataset is enclosed as "Analyzing_optimal_battery_sizing_in_microgrids_Dataset.xlsx". to use this dataset please cite this article: Hajra Khan, Imran Fareed Nizami, Saeed Mian Qaisar, Asad Waqar, Moez Krichen and Abdulaziz Turki Almaktoom, Analyzing optimal battery sizing in microgrids based on the feature selection and machine learning approaches, Energies, MDPI, 2022, * This paper is accepted for publication on the 13th of October 2022. It will appear soon online.

本数据集基于混合整数线性规划（mixed integer linear programming, MILP）生成。混合整数线性规划是一类被广泛应用于微电网场景下分布式能源（Distributed Energy Resources, DER）与储能装置优化选型及容量配置问题的线性优化方法。该优化问题通过对比不同分布式能源、储能装置的功率平衡状态与系统总负载的匹配关系完成求解。将随机生成的容量参数填入对应矩阵以构建发电组合，随后逐一验证各发电组合能否完全满足系统负载需求。基于混合整数线性规划的微电网模型，提取得到包含24255个样本、40个参数的居民微电网数据集。所提取参数及其说明已收录于文件"Dataset generation techniques factors and external factors.pdf"，数据集本体则以"Analyzing_optimal_battery_sizing_in_microgrids_Dataset.xlsx"文件形式提供。若使用本数据集，请引用以下文献：Hajra Khan、Imran Fareed Nizami、Saeed Mian Qaisar、Asad Waqar、Moez Krichen及Abdulaziz Turki Almaktoom，论文题为《基于特征选择与机器学习方法的微电网蓄电池优化容量分析》，发表于期刊Energies，MDPI出版社，2022年。本文于2022年10月13日获录用，即将在线发表。

搜集汇总

背景与挑战

背景概述

该数据集通过混合整数线性规划（MILP）方法生成，包含24255个样本和40个参数，用于研究微电网中电池优化配置问题。数据集适用于电气工程、机器学习和多目标优化等领域的研究。