arXiv subjects

Géza Joós

Publications and source records attributed to Géza Joós.

3 recordsLinked to original sources

arXiv2026

Pre-Fault Voltage Discrimination and Time-Domain Protection for Distribution Networks with Inverter-Based Resources

The increasing proliferation of inverter-based resources (IBRs) in distribution networks is presenting a major challenge for phasor-based overcurrent protection. This challenge stems from IBRs' lack of short-circuit current sourcing capacity. As a result, traditional overcurrent protection functions (e.g., ANSI 51) are inadequate in such scenarios, and warrant alternative approaches. Time-domain protection, for example, shows promise in overcoming this challenge. In this paper we propose a pre-fault voltage discrimination (PVD) strategy whose role is to detect faults and discriminate normal switching and transformer inrush disturbances from actual faults. The use of PVD allows for the design of a simple, yet effective fault detection algorithm by using time-domain protection principles for distribution networks containing IBRs. The introduction of PVD provides for faster fault detection without reducing security and dependability. Offline simulation experiments and controller hardware-in-the-loop real-time simulation validate the effectiveness of the proposed algorithm against various fault and normal switching events.

eess.SP↗

arXiv2024

Local Cold Load Pick-up Estimation Using Customer Energy Consumption Measurements

Thermostatically-controlled loads have a significant impact on electricity demand after service is restored following an outage, a phenomenon known as cold load pick-up (CLPU). Active management of CLPU is becoming an essential tool for distribution system operators who seek to defer network upgrades and speed up post-outage customer restoration. One key functionality needed for actively managing CLPU is its forecast at various scales. The widespread deployment of smart metering devices is also opening up new opportunities for data-driven load modeling and forecast. In this paper, we propose an approach for customer-side estimation of CLPU using time-stamped local load measurements. The proposed method uses Auto-Regressive Integrated Moving Average (ARIMA) modeling for short-term foregone energy consumption forecast during an outage. Forecasts are made on an hourly basis to estimate the energy to potentially recover after outages lasting up to several hours. Moreover, to account for changing customer behavior and weather, the model order is adjusted dynamically. Simulation results based on actual smart meter measurements are presented for 50 residential customers over the duration of one year. These results are validated using physical modeling of residential loads and are shown to match well the ARIMA-based forecasts. Additionally, accuracy and execution speed has been compared with other state-of-the-art approaches for time-series forecasting including Long Short Term Memory Network (LSTM) and Holt-Winters Exponential Smoothing (HWES). ARIMA-based forecast is found to offer superior performance both in terms of accuracy and computation speed.

eess.SY↗

arXiv2014

From Co- Toward Multi-Simulation of Smart Grids based on HLA and FMI Standards

In this article, a multi-simulation model is proposed to measure the performance of all Smart Grid perspectives as defined in the IEEE P2030 standard. As a preliminary implementation, a novel information technology (IT) and communication multi-simulator is developed following an High Level Architecture (HLA). To illustrate the usefulness of such a multi-simulator, a case study of a distribution network operation application is presented using real-world topology configurations with realistic communication traffic based on IEC 61850. The multi-simulator allows to quantify, in terms of communication delay and system reliability, the impacts of aggregating all traffic on a low-capacity wireless link based on Digital Mobile Radio (DMR) when a Long Term Evolution (LTE) network failure occurs. The case study illustrates that such a multi-simulator can be used to experiment new smart grid mechanisms and verify their impacts on all smart grid perspectives in an automated manner. Even more importantly, multi-simulation can prevent problems before modifying/upgrading a smart grid and thus potentially reduce utility costs.

cs.NI↗