In the paper, an innovative and easy-to-implement approach for improvement of conventional under-frequency load shedding (UFLS) is presented, where frequency thresholds are adjusted locally in real-time. The proposed method that would be implemented locally in each UFLS relay estimates the forthcoming frequency evolution and adjusts the predefined frequency thresholds values according to the estimated frequency nadir. As a result, significantly improved frequency response by reducing overshoots can be observed. The concept is verified by means of performing dynamic simulations in Slovenian power-system model, where the comparison with conventional setting showed high level of efficiency.
COBISS.SI-ID: 12367956
Conventional under-frequency load shedding exhibits an important deficiency: it is not capable of adjusting its intervention to seriousness of the root disturbance. This is mainly due to the number of stages that can be implemented in practice, having for consequence high probability of equally undesired frequency overshoots. For the protection of such importance, the robustness of wide-area monitoring solutions is questionable due to required communications. Therefore, improvements in local methods are expected for increasing situational awareness of under-frequency relays. In this paper, locally measured rate of change of frequency is applied in innovative yet transparent manner in order to introduce additional shedding criterion in each relay. The results indicate a significantly increased efficiency of under-frequency protection in many ways. Among most important are more favorable frequency response and decreased amount of disconnections. The simplicity of the suggested improvement makes it suitable for practical implementations with minor interventions into existing settings.
COBISS.SI-ID: 12578900
In order to guarantee certain level and performance of wireless services, in the case of WAMS particularly in terms of high reliability and low latency, it is necessary to better understand spectrum usage and hence utilization of radio resources. In this paper we propose, implement and evaluate a framework for automatic detection of wireless transmissions in an unlicensed or shared frequency band. It includes a manual component which has a paramount impact on tuning and maintaining good performance of an automatic transmission detection system. We discuss and evaluate challenges in generating labeled datasets that can be used as ground truth for evaluating and possibly training automatic transmission detection systems. We also propose two methods for automatic transmission detection that are not based on machine learning and therefore do not need training data and evaluate their performance against each other and manually labeled data.
COBISS.SI-ID: 33138983