High Resolution Modeling of the Impacts of Exogenous Factors on Power Systems—Case Study of Germany

Energies

Antriksh Singh²  Patrick Eser²  Ndaona Chokani¹  Reza Abhari² 

[1] Laboratory for Energy Conversion, Swiss Federal Institute of Technology, Sonneggstrasse 3, Zurich CH-8092, Switzerland

关键词: energy systems modeling;    renewables;    energy policy;   

DOI  :  10.3390/en81212424

来源: mdpi

【 摘 要 】

In order to reliably design the planning and operation of large interconnected power systems that can incorporate a high penetration of renewables, it is necessary to have a detailed knowledge of the potential impacts of exogenous factors on individual components within the systems. Previously, the assessment has often been conducted with nodes that are aggregated at the country or regional scale; this makes it impossible to reliably extrapolate the impact of higher penetration of renewables on individual transmission lines and/or power plants within an aggregated node. In order to be able to develop robust power systems this study demonstrates an integrated framework that employs high resolution spatial and temporal, physical modeling of power generation, electricity transmission and electricity demand, across the scale of a continent or country. Using Germany as a test case, an assessment of the impacts of exogenous factors, including local changes in ambient weather conditions, effect of timely implementation of policy, and contingency for scenarios in 2020 are demonstrated. It is shown that with the increased penetration of renewables, while the power production opportunities of conventional power plants are reduced, these power plants are required during periods of low renewables production due to the inherent variability of renewables. While the planned reinforcements in Germany, including high voltage direct current lines, reduce congestion on the grid and alleviate the differentials in power price across the country, on the other hand the reinforcements make the interconnected transmission system more vulnerable as local perturbations have a more widespread impact.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.