Techno-economic simulation modelling to forecast customer PV-battery economic incentives

The hourly insolation data was obtained from the PVWatts Calculator for the Perth metropolitan region.
The customer demand data was obtained via sampling of the demand profiles from the first figure at https://www.solarchoice.net.au/blog/how-to-get-most-solar-pv-system-pt-2-electricity-usage-patterns .
The R source code is used to perform of techno-economic forecast of the economics of customer PV and battery adoption.
Output figures and summary files for each case study and scenario of the analysis.

.R and .RDS files will require:
R , version 3.4.4
R studio, version 1.1.422

逐时太阳辐照数据（hourly insolation data）源自PVWatts计算器（PVWatts Calculator），采集区域为珀斯都会区。
用户用电需求数据通过采样该链接首图中的用电负荷曲线获取，链接为https://www.solarchoice.net.au/blog/how-to-get-most-solar-pv-system-pt-2-electricity-usage-patterns。
本数据集所附R语言源代码用于开展用户光伏（PV）与储能电池部署的技术经济预测分析。
本数据集包含本次分析各案例研究与对应场景的输出图表及汇总文件。
.R及.RDS格式文件的运行需依赖以下环境：
R语言（版本3.4.4）
R Studio（版本1.1.422）