基于云计算的全球可再生能源资源精细化评估方法  

A Refi ne Assessment Method of Global Renewable Energy Resources Based on Cloud Computing

作　　者：胡菊[1] 靳双龙[1] 宋宗朋[1] 冯双磊[1] 王勃[1] 

机构地区：[1]中国电力科学研究院,北京100192

出　　处：《电力信息与通信技术》2016年第3期25-29,共5页Electric Power Information and Communication Technology

基　　金：国家电网公司项目"全球可再生能源综合评估与深化研究";国家电网公司项目"基于超级云计算的数值天气预报一体化平台构架研究"

摘　　要：全球可再生能源资源的总储量及其时空分布对于其开发极为重要,目前一般使用气候模式进行全球可再生能源资源评估。然而,精细化的全球可再生能源资源评估面临计算量大、计算资源有限带来的计算时间过长的问题。文章提出了一种基于云计算的全球可再生能源资源评估方法,通过远程交互并行网格嵌套计算、作业优化和控制方案,在云中心和云平台的子节点间合理地分配了WRF(Weather Research and Forecast)气候模式的计算任务,并实现了节点间计算文件的高效传输和管理,提高了可再生能源资源评估的计算效率,显著缩短了计算时间,有利于全球能源互联网的开发布局研究。The information of global renewable energy total reserves and its space-time distribution are very important to its development. Current global renewable energy assessment method is using climate model. However, the refine assessment task will be a long time consuming work due to heavy computing burden and limited computing resources. This paper presents a refine assessment method using cloud computing, which utilizes the remote interactive parallel nested grid computing, operation optimization and control scheme to reasonably allocate weather research and forecast（WRF） climate model task to the master node in terminals and slavery nodes in the cloud platform, and achieve high effi ciency transmission of computing fi les between nodes. This method improves the computing efficiency of global renewable energy assessment, reduces the computing time significantly, and benefi ts the research of global energy interconnection development.

关 键 词：全球能源互联网 云计算 新能源资源评估 WRF 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]