期刊文献+
共找到2篇文章
< 1 >
每页显示 20 50 100
Identification and novel adaptive fuzzy control of nonlinear system for PEMFC stack
1
作者 卫东 许宏 朱新坚 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2006年第2期186-192,共7页
The operating temperature of a proton exchange membrane fuel cell stack is a very important control parameter. It should be controlled within a specific range, however, most of existing PEMFC mathematical models are t... The operating temperature of a proton exchange membrane fuel cell stack is a very important control parameter. It should be controlled within a specific range, however, most of existing PEMFC mathematical models are too complicated to be effectively applied to on-line control. In this paper, input-output data and operating experiences will be used to establish PEMFC stack model and operating temperature control system. An adaptive learning algorithm and a nearest-neighbor clustering algorithm are applied to regulate the parameters and fuzzy rules so that the model and the control system are able to obtain higher accuracy. In the end, the simulation and the experimental results are presented and compared with traditional PID and fuzzy control algorithms. 展开更多
关键词 proton exchange membrane fuel cell (PEMFC) adaptive neural-networks fuzzy infer system ANFIS) adaptive neural-network learning algorithm (ANA) nearest-neighbor clustering algorithm (NCA)
下载PDF
Optimal power flow calculation in AC/DC hybrid power system based on adaptive simplified human learning optimization algorithm 被引量:3
2
作者 Jia CAO Zheng YAN +2 位作者 Xiaoyuan XU Guangyu HE Shaowei HUANG 《Journal of Modern Power Systems and Clean Energy》 SCIE EI 2016年第4期690-701,共12页
This paper employs an efficacious analytical tool,adaptive simplified human learning optimization(ASHLO)algorithm,to solve optimal power flow(OPF)problem in AC/DC hybrid power system,considering valve-point loading ef... This paper employs an efficacious analytical tool,adaptive simplified human learning optimization(ASHLO)algorithm,to solve optimal power flow(OPF)problem in AC/DC hybrid power system,considering valve-point loading effects of generators,carbon tax,and prohibited operating zones of generators,respectively.ASHLO algorithm,involves random learning operator,individual learning operator,social learning operator and adaptive strategies.To compare and analyze the computation performance of the ASHLO method,the proposed ASHLO method and other heuristic intelligent optimization methods are employed to solve OPF problem on the modified IEEE 30-bus and 118-bus AC/DC hybrid test system.Numerical results indicate that the ASHLO method has good convergent property and robustness.Meanwhile,the impacts of wind speeds and locations of HVDC transmission line integrated into the AC network on the OPF results are systematically analyzed. 展开更多
关键词 adaptive simplified human learning optimization algorithm Optimal power flow AC/DC hybrid power system Valve-point loading effects of generators Carbon tax Prohibited operating zones
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部