Optimal Power Flow for Integrated Primary-Secondary Distribution Networks with Service Transformers

Secondary distribution networks (SDNets) play an increasingly important role in smart grids due to a high proliferation of distributed energy resources (DERs) in SDNets. However, most existing optimal power flow (OPF) problems do not take into account SDNets with service transformers. Handling the nonlinear and nonconvex SDNet power flow constraints is still an outstanding problem. To meet this gap, we first utilize the second-order cone programming relaxation and linearization to make service transformer constraints convex, respectively. Then, the linearized triplex service line power flow model, including its compact matrix-vector form, is further developed to compose the SDNet OPF model with our proposed service transformer model. This proposed SDNet OPF model can be easily embedded into existing primary distribution network (PDNet) OPF models, resulting in a holistic power system decision-making solution for integrated primary-secondary distribution networks. A case study is presented for an integrated primary-secondary distribution network that demonstrates the practical effectiveness of this model

Automatic Self-Adaptive Local Voltage Control Under Limited Reactive Power

The increasing proliferation of distributed energy resources has posed new challenges to Volt/VAr control problems in distribution networks. To this end, this paper proposes an automatic self-adaptive local voltage control (ASALVC) by locally controlling VAr outputs of distributed energy resources. In this ASALVC strategy, each bus agent can locally and dynamically adjust its voltage droop function in accordance with time-varying system changes. The voltage droop function is associated with the bus-specific time-varying slope and intercept, which can be locally updated, merely based on local voltage measurements, without requiring communication. Stability, convergence, and optimality properties of this local voltage control are analytically established. In addition, the online implementation of ASALVC is further proposed to address the real-time system changes by adjusting VAr outputs of DERs online. Numerical test cases are performed to validate and demonstrate the effectiveness and superiority of ASALVC

Spectrophotometric detection of uric acid with enzyme-like reaction mediated 3,3′,5,5′-tetramethylbenzidine oxidation

ABSTRACT. WO3 nanosheets (NSs) were prepared and characterized by X-ray photoelectron spectrometer (XPS), X-ray diffractometer (XRD), scanning electron microscope (SEM) and transmission electron microscope (TEM). The obtained WO3 NSs exhibited peroxidase-like catalytic activity, which can catalyze H2O2 to oxidize       3,3 ',5,5 '-tetramethylbenzidine (TMB) to generate oxidized TMB (oxTMB) with an absorption peak centered at 652 nm. Based on this, a facile method for the spectrophotometric determination of H2O2 was established. Under the selected conditions, the increase in absorbance of oxTMB enabled the detection of H2O2 ranging from 2.0 to 180 μM. Considering the fact that H2O2 is one of the products of urate oxidase (UAO)-catalyzed uric acid (UA) oxidation, a convenient method for the selective determination of UA was further developed with the help of UV–vis spectrophotometer. The increase of absorbance at 652 nm showed a linear response to UA concentration over the range of 2.0–180 μM. The limit of detection for UA was as low as 1.25 μM. More importantly, the proposed method was applied to the determination of UA in serum samples with satisfactory results.   KEY WORDS: Spectrophotometric, WO3 nanosheets, Uric acid, Determination   Bull. Chem. Soc. Ethiop. 2023, 37(1), 11-21.                                                             DOI: https://dx.doi.org/10.4314/bcse.v37i1.2&nbsp

Optical biopsy identification and grading of gliomas using label-free visible resonance Raman spectroscopy.

Glioma is one of the most refractory types of brain tumor. Accurate tumor boundary identification and complete resection of the tumor are essential for glioma removal during brain surgery. We present a method based on visible resonance Raman (VRR) spectroscopy to identify glioma margins and grades. A set of diagnostic spectral biomarkers features are presented based on tissue composition changes revealed by VRR. The Raman spectra include molecular vibrational fingerprints of carotenoids, tryptophan, amide I/II/III, proteins, and lipids. These basic in situ spectral biomarkers are used to identify the tissue from the interface between brain cancer and normal tissue and to evaluate glioma grades. The VRR spectra are also analyzed using principal component analysis for dimension reduction and feature detection and support vector machine for classification. The cross-validated sensitivity, specificity, and accuracy are found to be 100%, 96.3%, and 99.6% to distinguish glioma tissues from normal brain tissues, respectively. The area under the receiver operating characteristic curve for the classification is about 1.0. The accuracies to distinguish normal, low grade (grades I and II), and high grade (grades III and IV) gliomas are found to be 96.3%, 53.7%, and 84.1% for the three groups, respectively, along with a total accuracy of 75.1%. A set of criteria for differentiating normal human brain tissues from normal control tissues is proposed and used to identify brain cancer margins, yielding a diagnostic sensitivity of 100% and specificity of 71%. Our study demonstrates the potential of VRR as a label-free optical molecular histopathology method used for in situ boundary line judgment for brain surgery in the margins

Uncertainty Quantification and Sensitivity Analysis for the Electrical Impedance Spectroscopy of Changes to Intercellular Junctions Induced by Cold Atmospheric Plasma

The influence of pertinent parameters of a Cole-Cole model in the impedimetric assessment of cell-monolayers was investigated with respect to the significance of their individual contribution. The analysis enables conclusions on characteristics, such as intercellular junctions. Especially cold atmospheric plasma (CAP) has been proven to influence intercellular junctions which may become a key factor in CAP-related biological effects. Therefore, the response of rat liver epithelial cells (WB-F344) and their malignant counterpart (WB-ras) was studied by electrical impedance spectroscopy (EIS). Cell monolayers before and after CAP treatment were analyzed. An uncertainty quantification (UQ) of Cole parameters revealed the frequency cut-off point between low and high frequency resistances. A sensitivity analysis (SA) showed that the Cole parameters, R0 and α were the most sensitive, while Rinf and τ were the least sensitive. The temporal development of major Cole parameters indicates that CAP induced reversible changes in intercellular junctions, but not significant changes in membrane permeability. Sustained changes of τ suggested that long-lived ROS, such as H2O2, might play an important role. The proposed analysis confirms that an inherent advantage of EIS is the real time observation for CAP-induced changes on intercellular junctions, with a label-free and in situ method manner