Neural networks applied to preventive control measures for the dynamic security of isolated power systems with renewables

被引：25

作者：

Fidalgo, JN ^{[1
]}

Lopes, JAP ^{[1
]}

Miranda, V ^{[1
]}

机构：

[1] UNIV PORTO, FAC ENGN, FEUP, DEEC, P-4000 OPORTO, PORTUGAL

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 1996年 / 11卷 / 04期

关键词：

D O I：

10.1109/59.544647

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents an artificial neural network (ANN) based approach for the definition of preventive control strategies of autonomous power systems with a large renewable power penetration. For a given operating point, a fast dynamic security evaluation for a specified wind perturbation is performed using an ANN. If insecurity is detected, new alternative stable operating points are suggested, using a hybrid ANN-optimization approach that checks several feasible possibilities, resulting from changes in power produced by diesel and wind generators, and other combinations of diesel units in operation, Results obtained from computer simulations of the real power system of Lemnos (Greece) support the validity of the developed approach.

引用

页码：1811 / 1816

页数：6