
doi: 10.1049/pel2.70067
ABSTRACT Inertia, or the rotor stored energy of large rotating machines, plays an essential role in power systems' flexibility, resilience and stability. According to the generation process based on renewable energy and the proximity of generation and consumption, bulky synchronous generators (SGs) are replaced with low or no inertia resources. With this new approach, the stability of power systems in the microgrids concept is threatened. In order to overcome this problem, the scheme of grid forming converters (GFMCs) has been presented and the converters’ control is done through the characteristics of energy transfer of SGs. In DC microgrids (DCMGs), the SGs equations are inefficient. Therefore, in this article, the equations of a separately excited DC machine are used to control the GFMC. These equations are placed in the control scheme of a dual active bridge converter as a battery interface with the DCMG. The proposed GFMC small signal model is analysed to evaluate the stability. The effectiveness of the proposed scheme has been confirmed in the MATLAB/Simulink environment in a DCMG under different scenarios. Therefore, it is possible to control the inertial parameters of the DCMG and increase stability using the GFMC provided.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
