Michael Pertl

The Pan-European reference grid developed in ELECTRA for deriving innovative observability concepts in the Web-of-Cells framework

In the ELECTRA EU project, an innovative approach for frequency and voltage control is investigated, with reference to future power system scenarios characterized by massive amounts of distributed energy resources. A control architecture based on dividing the power system into a web of subsystems, the so-called cells, is proposed. Cells are individual control entities but also need to be coordinated together at system-wide level, in order to ensure secure and reliable overall operation (at Pan-European level). Task 5.4 in the ELECTRA project focuses on deriving novel observability concepts at system-wide scale. The methodology proposed in the task analyzes the system performance by investigating typical phenomena peculiar to each stability type and by developing observables necessary for the novel Web-of-Cells based control methods to operate properly at cell- and inter-cell level. Crucial aspects of angle, frequency and voltage stability are considered, according to the stability classification by CIGRÉ. In order to carry out the evaluations, a suitable test multi-cell grid model is developed. The paper aims at describing this reference model and at presenting the approach used in the task for assessing system stability in the developed WoC framework.

Voltage estimation in active distribution grids using neural networks

The power flow in distribution grids is becoming more complicated as reverse power flows and undesired voltage rises might occur under particular circumstances due to integration of renewable energy sources, increasing the occurrence of critical bus voltages. To identify these critical feeders the observability of distribution systems has to be improved. To increase the situational awareness of the power system operator data driven methods can be employed. These methods benefit from newly available data sources such as smart meters. This paper presents a voltage estimation method based on neural networks which is robust under complex load and in-feeder generation situations. A major advantage of the proposed method is that the power system does not have to be explicitly modeled.

Grid frequency support by single-phase electric vehicles employing an innovative virtual inertia controller

The displacement of conventional generation by converter connected resources reduces the available rotational inertia in the power system, which leads to faster frequency dynamics and consequently a less stable frequency behavior. Virtual inertia, employing energy storage systems, could be used to limit the rate of change of frequency of power systems, thus, improving frequency dynamics. Electric vehicles (EVs) can represent a reliable solution to enhance frequency stability due to their fast response and capability to provide a large amount of aggregated power. On one hand, EVs are capable of adjusting the battery charging process (i.e., power flow) according to pre-defined algorithms. On the other hand, in case of islanded operation (i.e., low inertia), some of the EVs technical constraints might cause oscillations. This study presents two control algorithms which show that the EVs are capable of providing virtual inertia support. The first controller employs a traditional droop control, while the second one is equipped with an innovative control algorithm to eliminate likely oscillations. It is shown that, the proposed innovative control algorithm compared to the traditional droop control, assures same effects in terms of frequency but reducing significantly the number of variation of the EVs current set-point.