Data for: Parallelized Multi-level Optimization Model with Continuous Search Domain for Selection of Run-of-river Hydropower Projects

This folder contains the code for the Run-of-River Project Optimization (RoRPO) model described in the manuscript. The RoRPO model is coded in MatLab and is designed to be used on high-performance computing (HPC) facilities. The code that is provided here applies the RoRPO model to the Guder River case study. Flow data for Guder River is in the file "GuderRiverFlow.mat". The profile of Guder River is in the file "GuderRiverProfile.mat". The RoRPO model selects turbines from a predefined set. Characteristics of turbines defined for the Guder River case study are given I the file "turbineData.mat".
To run the model on an HPC, execute "ror_main.m" with "ror_0.mat" as an input file. The model should automatically run in parallel and generate new instances on the HPC. Results are written to the file "ror_out.mat". After running the code, you can use this command to open the output file "dlmread('ror_out.mat')".

本文件夹包含论文所述的径流式电站优化（Run-of-River Project Optimization, RoRPO）模型的代码。该模型采用MatLab编写，专为高性能计算（High-Performance Computing, HPC）集群环境设计。本次提供的代码将RoRPO模型应用于古德尔河（Guder River）案例研究。古德尔河的流量数据存储于文件"GuderRiverFlow.mat"中，河道剖面数据存储于文件"GuderRiverProfile.mat"中。RoRPO模型可从预设的涡轮机选型集合中选取机组，为古德尔河案例研究定义的涡轮机特性详见文件"turbineData.mat"。

若需在高性能计算集群上运行该模型，请以"ror_0.mat"作为输入文件执行"ror_main.m"。模型将自动以并行模式运行，并在集群上生成新的计算实例。计算结果将写入文件"ror_out.mat"。代码运行完成后，可通过命令`dlmread('ror_out.mat')`读取该输出文件。