电网技术2016，Vol.40Issue(4)：1224-1230,7.DOI:10.13335/j.1000-3673.pst.2016.04.036
基于神经网络的分布式电源统一等效建模及其在PSASP中的应用
Unified Equivalent Modeling of Distributed Generation Using Artificial Neural Network and Its Application in PSASP
摘要
Abstract
With increasing penetration in power grid, distributed generation (DG) unified equivalent modeling becomes basic research in field of power system simulation. Artificial neural network (ANN) features strong nonlinear mapping ability and self-learning ability, providing an effective access to problem research. This paper overviews application of various neural network models in power system load modeling, and compares their merits and defects. Feedback branch of Elman neural network is improved to meet needs of unified equivalent modeling of distributed generation. Combination ideas between improved Elman neural network and power system analysis software package (PSASP) are proposed. Simulation examples show that improved Elman neural network can effectively describe external characteristics of variety of distributed generations and meet needs of engineering simulation.关键词
神经网络/分布式电源/等效建模/PSASPKey words
neural network/distributed generation/equivalent model/PSASP分类
信息技术与安全科学引用本文复制引用
李培强,曾小军,李欣然,胡泽,柯飞,谭庄熙..基于神经网络的分布式电源统一等效建模及其在PSASP中的应用[J].电网技术,2016,40(4):1224-1230,7.基金项目
国家自然科学基金项目(51277055)。Project Supported by National Natural Science Foundation of China (51277055) （51277055）
