High penetration of power electronic interfaced generation, like wind power, has an essential impact on the inertia of the interconnected power system. It can pose a significant threat to the frequency stability. This paper introduces the notion of the key performance indicator (KPI) and illustrates its application on large scale power systems, including Fast Frequency Response (FFR) and a high share of wind power, to measure the possible distance to the frequency stability limit. The proposed KPI estimates the change of frequency performance (e,g., ROCOF, NADIR) in the frequency containment period. The effect of FFR is analyzed by introducing a droop based controller for wind power plants. The FFR controller responds to a drop in grid frequency with a temporary increase of the wind active power. The proposed KPI maps a change in key system variables (e.g., system kinetic energy, aggregated generation output) onto the change of frequency performance. A comprehensive analysis using DIgSILENT, Matlab, and Python is performed for GB reduced size system. According to the obtained results, the FFR capability of wind generator leads to improvements of NADIR especially in cases with high penetration levels of wind power. The proposed KPI is a valuable tool for the frequency stability assessment in power system planning studies. It can be determined based on off-line simulations, and it can assist the system operators for frequency stability assessment in intra-day operational planning.

The electric power sector is one of the later sectors in adopting digital twins and models in the loop for its operations. This article firstly reviews the history, the fundamental properties, and the variants of such digital twins and how they relate to the power system. Secondly, first applications of the digital twin concept in the power and energy business are explained. It is shown that the trans-disciplinarity, the different time scales, and the heterogeneity of the required models are the main challenges in this process and that co-simulation and co-modeling can help. This article will help power system professionals to enter the field of digital twins and to learn how they can be used in their business.

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The evolved smart grid has become a cyber physical energy system that could be exposed to a massive amount of cyber threats. Vulnerabilities within the cyber part can be used to launch multiple types of attacks that corrupt the physical system. The complexity of cyber physical energy system, the existing of different kinds of attacks, require an appropriate tool to aid in modeling and simulation for cyber security analysis. In this paper, we introduce a modeling language -Modelica to the security community of cyber physical system. We show the capability of Modelica in modeling complex systems and attacks by building up a power grid model with frequency control loop (i.e., automatic generation control), as well as data integrity attack and data availability attack models. The simulation results show how different types of attacks or even combined attacks can affect the system frequency stability.

The electric power sector is one of the later sectors in adopting digital twins and models in the loop for its operations. This article firstly reviews the history, the fundamental properties, and the variants of such digital twins and how they relate to the power system. Secondly, first applications of the digital twin concept in the power and energy business are explained. It is shown that the trans-disciplinarity, the different time scales, and the heterogeneity of the required models are the main challenges in this process and that co-simulation and co-modeling can help. This article will help power system professionals to enter the field of digital twins and to learn how they can be used in their business.