Voltage Stability Analysis in Medium-Voltage Distribution Networks Using a Second-Order Cone Approximation

This paper addresses the voltage stability margin calculation in medium-voltage distribution networks in the context of exact mathematical modeling. This margin calculation is performed with a second-order cone (SOCP) reformulation of the classical nonlinear non-convex optimal power flow problems. The main idea around the SOCP approximation is to guarantee the global optimal solution via convex optimization, considering as the objective function the λ-coefficient associated with the maximum possible increment of the load consumption at all the nodes. Different simulation cases are considered in one test feeder, described as follows: (i) the distribution network without penetration of distributed generation; (ii) the distribution network with penetration of distributed generation; and (iii) the distribution grid with capacitive compensation. Numerical results in the test system demonstrated the effectiveness of the proposed SOCP approximation to determine the λ-coefficient. In addition, the proposed approximation is compared with nonlinear tools available in the literature. All the simulations are carried out in the MATLAB software with the CVX package and the Gurobi solver

Optimal selection and location of fixed-step capacitor banks in distribution networks using a discrete version of the vortex search algorithm

This paper deals with the problem of the optimal selection of capacitor banks in electrical AC distribution systems for minimizing the costs of energy losses during a year of operation through a discrete version of the vortex search algorithm (DVSA). This algorithm works with a hypersphere with a variable radius defined by an exponential function where a Gaussian distribution is used to generate a set of candidate solutions uniformly distributed around the center of this hypersphere. This center corresponds to the best solution obtained at the iteration t, which is initialized at the center of the solution space at the iterative search beginning. The main advantage of combining the exponential function with the Gaussian distribution is the correct balance between the exploration and exploitation of the solution space, which allows reaching the global optimal solution of the optimization problem with a low standard deviation, i.e., guaranteeing repeatability at each simulation. Two classical distribution networks composed of 33 and 69 nodes were used to validate the proposed DVSA algorithm. They demonstrated that the DVSA improves numerical reports found in specialized literature regarding the optimal selection and location of fixed-step capacitor banks with a low computational burden. All the simulations were carried out in MATLAB software

Humoral response to viral vector COVID-19 vaccine in hemodialysis patients

Background The coronavirus disease 2019 (COVID-19) vaccine is not readily available in many countries where dosing interval is spaced more than ideal. Patients with chronic kidney disease, especially those on maintenance hemodialysis, have a tendency for a reduced immune response. This study was undertaken to demonstrate the distinct humoral immune response to the viral vector COVID-19 vaccine in patients with kidney failure receiving maintenance hemodialysis. Methods The study was carried out with two cohorts: 1) patients receiving maintenance hemodialysis and 2) healthcare workers from the same dialysis center as controls, each group with 72 subjects. Participants received a dose of Covishield ChAdOx1 nCoV-19 coronavirus vaccine. The humoral immunological response was determined using electrochemiluminescence immunoassay which quantitatively measures antibodies to the severe acute respiratory syndrome coronavirus 2 spike protein receptor-binding domain. Results All study subjects in the control group developed a humoral response (antibody titer of ≥0.8 U/mL), while only 64 of 72 in the dialysis group (88.9%) were responders. Age (ρ = –0.234, p = 0.04) and sodium level (ρ = 0.237, p = 0.04) correlated with low antibody titer in bivariate analysis. In multivariate analysis, only age (odds ratio, 1.10; 95% confidence interval, 1.01–1.22; p = 0.045)was associated with nonresponders. Conclusion Our study demonstrated a weak antibody response of hemodialysis patients to the viral vector COVID-19 vaccine. Older age was associated with nonresponders. Evaluation of both humoral and cellular immunity after the second vaccine dose and serial antibody titers can help determine the need for booster shots

Fixed Points on Covariant and Contravariant Maps with an Application

Fixed-point results on covariant maps and contravariant maps in a (Formula presented.) -algebra-valued bipolar metric space are proved. Our results generalize and extend some recently obtained results in the existing literature. Our theoretical results in this paper are supported with suitable examples. We have also provided an application to find an analytical solution to the integral equation and the electrical circuit differential equation. © 2022 by the authors

Fixed point theorem on an orthogonal extended interpolative ψF-contraction

In this paper, we establish the fixed point results for an orthogonal extended interpolative Ciric Reich-Rus type $\psi\mathcal{F}$-contraction mapping on an orthogonal complete $\mathfrak{b}$-metric spaces and give an example to strengthen our main results. Furthermore, we present an application to fixed point results to find analytical solutions for functional equation

Multi-Objective Golden Flower Optimization Algorithm for Sustainable Reconfiguration of Power Distribution Network with Decentralized Generation

This paper provides a meta-heuristic hybridized version called multi-objective golden flower pollination algorithm (MOGFPA) as the best method for choosing the optimal reconfiguration for distribution networks (DNs) in order to reduce power losses (PLs). Aside from PLs, another parameter is considered: the load balance index (LBI). The expression for the LBI is stated using real and reactive indices. It makes the optimal distributed generation (DG) placement and DN routing of the multi-objective (MO) problem have PLs and the LBI as the main parameters that need to be optimized. For that purpose, the MOGFPA is proposed in this paper. The MOGFPA consists of a golden search (GS) and tangent flight with Pareto distribution that only needs a few tuning parameters. Therefore, it is simple to alter these parameters to reach the best values compared to other existing methodologies. Its performance is predicted using different case studies on multiple test bus systems, namely the IEEE systems such as 33, 69, 119, and Indian 52 bus. Through simulation outcomes, the MOGFPA computes the optimum distribution of DG units and reconfigures the DNs with the aim of minimal PLs and LBI. Furthermore, another state-of-the-art technology and comparing convergence charts provide optimal outputs in less time, with minimum iterations

Optimized Network Reconfiguration with Integrated Generation Using Tangent Golden Flower Algorithm

The importance of integrating distributed generation (DG) units into the distribution network (DN) recently developed. To decrease power losses (PL), this article presents a meta-heuristic population-based tangent golden flower pollination algorithm (TGFPA) as an optimization technique for selecting the ideal site for DG. Furthermore, the proposed algorithm also finds the optimal routing configuration for power flow. TGFPA requires very few tuning parameters and is comprised of a golden section and a tangent flight algorithm (TFA). Hence, it is easy to update these parameters to obtain the best values, which provide highly reliable results compared to other existing techniques. In different case studies, the TGFPA’s performance was assessed on four test bus systems: IEEE 33-bus, IEEE 69-bus, IEEE 119-bus, and Indian-52 bus. According to simulation results, TGFPA computes the optimal reconfigured DN embedded along with DG, achieving the goal of minimal power loss