Sharma Vanika, Haque Mohammed H, Aziz Syed Mahfuzul
School of Engineering, University of South Australia, Mawson Lakes, SA 5095, Australia.
Data Brief. 2019 Jul 8;25:104235. doi: 10.1016/j.dib.2019.104235. eCollection 2019 Aug.
This paper presents the hourly Photovoltaic (PV) generation and residential load profiles of a typical South Australian Net Zero Energy (NZE) home. These data are used in the research article entitled "Energy Cost Minimization for Net Zero Energy Homes through Optimal Sizing of Battery Storage System" Sharma et al., 2019. The PV generation data is derived using the publicly accessible renewable ninja web platform by feeding information such as the region of interest, PV system capacity, losses and tilt angle. The raw load profile data is sourced from the Australian Energy Market Operator (AEMO) website, which is further processed and filtered to match the household load requirement. The processing of data has been carried out using Microsoft Excel and MATLAB software. The experimental method used to obtain the required data from the downloaded raw dataset is described in this paper. While the data is generated for the state of South Australia (SA), the method described here can be used to produce datasets for any other Australian state.
本文展示了南澳大利亚州一座典型的净零能耗(NZE)住宅的每小时光伏发电量和居民用电负荷曲线。这些数据用于研究论文《通过电池储能系统的优化选型实现净零能耗住宅的能源成本最小化》(夏尔马等人,2019年)。光伏发电数据是通过在可再生忍者公共网络平台上输入诸如感兴趣区域、光伏系统容量、损耗和倾斜角度等信息得出的。原始负荷曲线数据来自澳大利亚能源市场运营商(AEMO)网站,该数据经过进一步处理和筛选,以符合家庭用电负荷需求。数据处理是使用微软Excel和MATLAB软件进行的。本文描述了从下载的原始数据集中获取所需数据所采用的实验方法。虽然这些数据是为南澳大利亚州(SA)生成的,但此处描述的方法可用于生成澳大利亚其他任何州的数据集。