Point estimate method for voltage unbalance evaluation in residential distribution networks with high penetration of small wind turbines

Voltage unbalance (VU) in residential distribution networks (RDNs) is mainly caused by load unbalance in three phases, resulting from network configuration and load-variations. The increasing penetration of distributed generation devices, such as small wind turbines (SWTs), and their uneven distribution over the three phases have introduced difficulties in evaluating possible VU. This paper aims to provide a three-phase probabilistic power flow method, point estimate method to evaluate the VU. This method, considering the randomness of load switching in customers’ homes and time-variation in wind speed, is shown to be capable of providing a global picture of a network’s VU degree so that it can be used for fast evaluation. Applying the 2m + 1 scheme of the proposed method to a generic UK distribution network shows that a balanced SWT penetration over three phases reduces the VU of a RDN. Greater unbalance in SWT penetration results in higher voltage unbalance factor (VUF), and cause VUF in excess of the UK statutory limit of 1.3%

BEHAVIOUR OF HIGH STRENGTH CONCRETE COMPOSITE SLABS WITH DIFFERENT END ANCHORAGES

This study is performed to investigate experimentally the behaviour of steel deck composite slabs with different end anchorages. End anchorage as a type of shear connection for composite slabs plays an important role to prevent relative slip between concrete and steel deck. The presented composite slab specimens are made of high strength concrete and loaded at a specific shear span. Objectives of this study is to evaluate experimentally load carrying capacity, end slip, mode of failure, shear bond capacity, and the end anchorage contribution to the whole composite slab behaviour. Research also presents a comparison between the experimental results and the theoretical results derived according to m-k and partial shear connection methods included in these standards (BS 5950-4:1994, CSSBI S3-2003, and EC4 EN 1994-1-1:2004)

Volumetric study of the olfactory bulb in patients with chronic rhinonasal sinusitis using MRI

AbstractObjectiveOlfaction plays an important role in human daily life. The olfactory bulb size is dependent on stimulation. Smell loss is one of the main symptoms in chronic rhinonasal sinusitis. MRI has been indicated to evaluate the size of the olfactory bulb in such patients.The aim of this study was to assess the volumetric changes of the olfactory bulb in patients with sinonasal polyposis before and after treatment using MRI.Patients and methodsFifteen control subjects and 30 patients were included in the study, 24 of them patients underwent endoscopic sinus surgery. Volumetric analysis of their olfactory bulb volume was done using MRI and specialized software.ResultsIt was found that the olfactory bulb volume was significantly smaller in patients (19.98±5.88mm3) when compared to control mean (39.6±13.8mm3) and there was a significant increase in the olfactory bulb volumes in patients who underwent surgery 6months postoperatively (24.79±5.11mm3).ConclusionsMRI with volumetric analysis is a useful tool in assessment of the olfactory bulb volume in patients with olfactory loss and appears to be of help in assessment of the degree of recovery in patients after sinus surgery

Fault detection and localisation in LV distribution networks using a smart meter data-driven digital twin

Modern solutions for precise fault localization in Low Voltage (LV) Distribution Networks (DNS) often rely on costly tools such as micro-Phasor Measurement Unit (μPMU), potentially impractical for the large number of nodes in LVDNs. This paper introduces a novel fault detection technique using a distribution network digital twin without the use of μPMUs. The Digital Twin (DT) integrates data from Smart Meters (SMs) and network topology to create an accurate replica. Using SM voltage-magnitude readings, the pre-built twin compiles a database of fault scenarios and matches them with their unique voltage fingerprints. However, this SM-based voltage-only approach shows only 70.7% accuracy in classifying fault type and location. Therefore, this research suggests using the cables' Currents Symmetrical Component (CSC). Since SMS do not provide direct current data, a Machine Learning (ML)-based regression method is proposed to estimate cables' currents in the DT. Validation is performed on a 41-node LV distribution feeder in the Scottish network provided by industry partner Scottish Power Energy Networks (SPEN). Results show that the current estimation regressor significantly improves fault localization and identification accuracy to 95.77%. This validates the crucial role of a DT in distribution networks, enabling highly accurate fault detection using SM voltage-only data, with further refinement through estimation of CSC. The proposed DT offers automated fault detection, enhancing customer connectivity and maintenance team dispatch efficiency without the need for additional expensive μPMU on the densely-noded distribution network

Efficient Catalytic Production Of Biodiesel Using Nano-sized Sugar Beet Agro-industrial Waste

This paper addresses the use of agro-industrial residue as a promising heterogeneous catalyst for the efficient production of biodiesel. That is, CaO-rich Sugarbeet agro-industrial waste (smashed down to nano-size) shows superb catalytic activity for biodiesel production via transesterification process employing sunflower oil and methanol. Physicochemical properties of the proposed catalyst are probed by TGA–DTG, XRF, XRD, FT-IR, SEM, BET, and CO2-TPD techniques. Biodiesel conversion (%) of Ca. 93% is achieved under the optimal conditions (catalyst loading of 1 wt%, methanol/oil molar ratio of 4.5:1, refluxed at 75 °C for 60 min). The relatively short reaction time indicates the enhanced kinetics of the process using the proposed agro-industrial residue which imparts its economic feasibility. Also, the proposed CaO-rich residue can be reused twice while retaining its catalytic activity. The thus-produced biodiesel fuel compiles the ASTM D6751 and EN-14214 specifications