Method for modelling fluctuating energy generation plants for the assessment of their impact on medium and low voltage grids

被引：1

作者：

Meinerzhagen, Ann-Kathrin ^{[1
]}

Sowa, Torsten ^{[1
]}

Koopmann, Simon ^{[1
]}

Schnettler, Armin ^{[1
]}

Gutschmidt, Eduard ^{[2
]}

机构：

[1] Rhein Westfal TH Aachen, Inst High Voltage Technol, Aachen, Germany

[2] Allgauer Uberlandwerke GmbH, Kempten, Germany

来源：

COMPUTER SCIENCE-RESEARCH AND DEVELOPMENT | 2016年 / 31卷 / 1-2期

关键词：

ARMAX; Artificial neural networks; Photovoltaic plants; Probabilistic modelling; Renewable energy; Uncertainty;

D O I：

10.1007/s00450-014-0275-7

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper describes a method for taking the forecasting uncertainty into account when assessing the impact of volatile generation on power grids. To this end the generation of feed-in scenarios for generation plants that include the uncertainty of the weather forecast is described. With a three-step model that firstly forecasts local weather parameters and, secondly, generates scenarios for these parameters, thirdly, a reduced number of resulting feed-in profile scenarios for each plant is computed. With these scenarios the assessment of the grid-impact of the plants can be calculated taking into account the uncertainty of the prognosis. In a case study, feed-in profiles for the plants in an exemplary region are generated which can be used for an assessment of the grid impact in this region using probabilistic load flow calculation.

引用

页码：3 / 7

页数：5