Experimental Analysis of Power Quality in a Power Substation Used in a Residential and Educational Sector

The article describes the experimental measurements made at a low-voltage residential and educational power substation, in a point of common coupling. Two groups of experiments were carried out, in normal conditions and during the COVID-19 pandemic. Measurements were made using a power quality analyzer and include phase RMS voltages and line currents, total harmonic distortion and unbalance of phase voltages and line currents, neutral current, active, reactive and apparent powers, power factors and displacement power factors, Fresnel diagrams, and harmonic spectra. Measurements indicate significant differences of power quality indicators between the two measurement groups. © 2023 IEEE.

Assessment of effective reactive power reserve in power system networks under uncertainty applying coronavirus herd immunity optimizer (CHIO) for operation simulation

The Reactive Power Reserve (RPR) is a very important indicator for voltage stability and is sensitive to the operating conditions of power systems. Thorough understanding of RPR, specifically Effective Reactive Reserve (ERR) under intermittent Wind Power (WP) and uncertain demand is essential and key focus of this research. Hence, a stochastic multivariate ERR assessment and optimization problem is introduced here. The proposed problem is solved in three stages: modeling of multivariate uncertainty, studying the stochastic behavior of ERR and optimizing ERR. The volatilities associated with WP generation and consumer demand are modeled explicitly, and their probability distribution function is discretized to accommodate structural uncertainty. A combined load modeling approach is introduced and extended further to accommodate multi-variability. The impact of these uncertainties on ERR is assessed thoroughly on modified IEEE 30 and modified Indian 62 bus system. A non-linear dynamic stochastic optimization problem is formulated to maximize the expected value of ERR and is solved using ‘Coronavirus Herd Immunity Optimizer (CHIO)'. The impact of the proposed strategy on stability indices like the L-index, Proximity Indicator (PI) are analyzed through various case studies. Further, the effectiveness of the proposed approach is also compared with the existing mean value approach. Additionally, the performance of CHIO is confirmed through exhaustive case studies and comparisons. © 2023 Elsevier B.V.

Analysis of Pre- and during COVID-19 Mixed Load Models on Unbalanced Radial Distribution System Using a New Metaphor-Less Rao Optimization

An unbalanced electrical distribution system (DS) with radial construction and passive nature suffers from significant power loss. The unstable load demand and poor voltage profile resulted from insufficient reactive power in the DS. This research implements a unique Rao algorithm without metaphors for the optimal allocation of multiple distributed generation (DG) and distribution static compensators (DSTATCOM). For the appropriate sizing and placement of the device, the active power loss, reactive power loss, minimum value of voltage, and voltage stability index are evaluated as a multiobjective optimization to assess the device's impact on the 25-bus unbalanced radial distribution system. Various load models, including residential, commercial, industrial, battery charging, and other dispersed loads, were integrated to develop a mixed load model for examining electrical distribution systems. The impact of unpredictable loading conditions resulting from the COVID-19 pandemic lockdown on DS is examined. The investigation studied the role of DG and DSTATCOM (DGDST) penetration in the electrical distribution system for variations in different load types and demand oscillations under the critical emergency conditions of COVID-19. The simulation results produced for the mixed load model during the COVID-19 scenario demonstrate the proposed method's efficacy with distinct cases of DG and DSTATCOM allocation by lowering power loss with an enhanced voltage profile to create a robust and flexible distribution network. Copyright © 2023 Jitendra Singh Bhadoriya et al.

Emergency Distribution Network Design & Analysis for Consecrated COVID 19 Hospital Zone

A power distribution network is always a key topic in a grid system because of more complexity. Rapidly or sudden load increasing to a particular one or two feeders can arise uncertainty and unbalance conditions in the system. Voltage fluctuations, Deviations, THD (total harmonic distortion), Reactive power imbalances can seriously unstable the grid for load increasing situations. In recent days due to COVID 19 condition, dedicated hospitals are connected to the distribution network. Because of its urgency and usefulness, a new type of distribution network called loop plus parallel has been presented in this paper. Finally, the simulation studies show better performance when comparing the traditional types of networks. New distribution network shows promising values in THD, Voltage deviation and also for reactive power imbalance. © 2022 Authors. All rights reserved.

Maximization of Reactive Power Reserve in wind integrated power system using CHIO approach

The Reactive Power Reserve (RPR) is an important indicator to plan stable and secure power system operations. The evaluation of RPR is very important to analyze the performance of wind integrated power systems. The RPR should be kept as high as possible for a stable and secure operation of a power system. However, it is difficult to maintain adequate RPR in wind integrated power systems owing to the uncertainty associated with it. A scenario-based nonlinear, complex RPR maximization problem is proposed in this work to ensure the voltage stability of the wind integrated power systems. A newly developed 'Coronavirus Herd Immunity Optimizer (CHIO)' is utilized to solve the proposed problem. Programs are developed in MATLAB and tested on IEEE 30 bus system. The voltage controllers present in the power system are adjusted continuously during the optimization for optimality. Further, the free parameters of CHIO are also tuned through sensitivity analysis. The proficiency of CHIO is verified through various case studies and comparisons with other methods. Copyright (C) 2022 The Authors.