Related papers: A Novel Data Segmentation Method for Data-driven P…
Accurate labeling of phase connectivity in electrical distribution systems is important for maintenance and operations but is often erroneous or missing. In this paper, we present a process to identify which smart meters must be in the same…
This paper presents a novel power-band-based data segmentation (PBDS) method to enhance the identification of meter phase and meter-transformer pairing. Meters that share the same transformer or are on the same phase typically exhibit…
The increased deployment of distributed energy generation and the integration of new, large electric loads such as electric vehicles and heat pumps challenge the correct and reliable operation of low voltage distribution systems. To tackle…
To address the challenges and exploit the opportunities that the decarbonization of the energy sector is bringing about, advanced distribution network management and operation strategies are being developed. Many of these require accurate…
This paper proposes a novel phase identification method for distribution networks where phases can be severely unbalanced and insufficiently labeled. The analysis approach draws on data from high-precision phasor measurement units…
The mitigation of distribution network (DN) unbalance and the use of single-phase flexibility for congestion mitigation requires accurate phase connection information, which is often not available. For a large DN, the naive phase…
Smart meters provide relevant information for impedance identification, but they lack global phase alignment and internal network nodes are often unobserved. A few methods for this setting were developed, but they have requirements on data…
In recent years, developing unsupervised machine learning for identifying phase transition is a research direction. In this paper, we introduce a two-times clustering method that can help select perfect configurations from a set of…
In this paper, a new Smartphone sensor based algorithm is proposed to detect accurate distance estimation. The algorithm consists of two phases, the first phase is for detecting the peaks from the Smartphone accelerometer sensor. The other…
Consumers with low demand, like households, are generally supplied single-phase power by connecting their service mains to one of the phases of a distribution transformer. The distribution companies face the problem of keeping a record of…
The widespread adoption of smart meters for monitoring energy consumption has generated vast quantities of high-resolution time series data which remains underutilised. While clustering has emerged as a fundamental tool for mining smart…
In order to improve the efficiency and sustainability of electricity systems, most countries worldwide are deploying advanced metering infrastructures, and in particular household smart meters, in the residential sector. This technology is…
The problem of state estimations for electric distribution system is considered. A collaborative filtering approach is proposed in this paper to integrate the slow time-scale smart meter measurements in the distribution system state…
This paper considers the problem of Phase Identification in power distribution systems. In particular, it focuses on improving supervised learning accuracies by focusing on exploiting some of the problem's information theoretic properties.…
Investigations have been performed into using clustering methods in data mining time-series data from smart meters. The problem is to identify patterns and trends in energy usage profiles of commercial and industrial customers over 24-hour…
This manuscript presents novel techniques for identifying the switch states, phase identification, and estimation of equipment parameters in multi-phase low voltage electrical grids, which is a major challenge in long-standing German low…
Radar sensors provide a unique method for executing environmental perception tasks towards autonomous driving. Especially their capability to perform well in adverse weather conditions often makes them superior to other sensors such as…
Accurate phase connectivity information is essential for advanced monitoring and control applications in power distribution systems. The existing data-driven approaches for phase identification lack precise physical interpretation and…
The prompt and accurate detection of faults and abnormalities in electric transmission lines is a critical challenge in smart grid systems. Existing methods mostly rely on model-based approaches, which may not capture all the aspects of…
Privacy concerns are considered one of the main challenges in smart cities as sharing sensitive data brings threatening problems to people's lives. Federated learning has emerged as an effective technique to avoid privacy infringement as…