特殊运行方式与保护装置的配合

结合城网、农网改造过程中设备运行方式发生的特殊变化,叙述了如何根据现场实际接线及设备工况进行设备运行方式调整;并在非正常运行方式下如何变更继电保护的动作时限,以及电力系统安全稳定自动装置的投入方式,从而为同行业工作者提供借鉴.     

Sheet carrier density dependent Rashba spin splitting in the Alo.sGao.sN/GaN/ Alo.sGao.sN quantum well＊

The Rashba coefficient and Rashba spin splitting for the first subband of the Alo.5Gao.5N/GaN/ Alo.5Gao.5N quantum well （QW） with various sheet carrier densities （Ns） are calculated by solving Schr6dinger and Poisson equations self-consistently. The Rashba spin splitting for the first subband at the Fermi level is considerable and increases evidently with Ns, since the Rashba coefficient, especially the Fermi wave vector increase rapidly. With increasing Ns, the peak of the wave function for the first subband moves towards the left heterointerface, and the average electric field in the well increases, so the two dominant contributions coming from the well and the heterointerface increase. Therefore, the strong polarization electric field and high density of 2DEG in III-nitrides heterostructures are of great importance to a and make the Rashba spin splitting in A1GaN/GaN QWs comparable to that of narrow-gap III-V materials. The results indicate that the sheet carrier density is an important parameter affecting the Rashba coefficient and Rashba spin splitting in A1GaN/GaN QWs, showing the possible application of this material system in spintronic devices.     

一种简单可靠的电压互感器三次回路检测新方法

在220 kV系统电网中广泛应用着零序功率方向保护.对于由电压互感器三次回路3U0构成的零序方向元件,用常规方法不易检测出其3U0的两根导线混淆的错误接线,致使零序方向保护误动作的情况时有发生.分析了常用的两种检测方法的弊端,提出了一种简单可靠的电压互感器三次回路检测新方法.理论分析和实践经验表明,该方法可以明确地检测出3U0的两根导线混淆的错误接线.     

基于遗传优化神经网络的电力系统短期负荷预测

电力系统短期负荷预测是电力系统运行管理和实时控制所必须的基本内容,预测结果的准确性对电力系统的安全、优质,经济运行具有重要意义。通过非参数预测法建立电力系统短期负荷预测模型,以此作为Elman神经网络训练的样本集,实现网络样本设计、结构设计与网络训练,充分发挥Elman神经网络动态特性,将改进的遗传算法和Elman神经网络相结合,通过选择,交叉、变异等遗传操作,实现了神经网络权值优化。采用基于遗传优化神经网络的电力系统短期负荷预测新算法,提高了负荷预报精度,具体算例证明了算法的可行性和有效性。