Improvement of active distribution systems with high penetration capacities of shunt reactive compensators and distributed generators using Bald Eagle Search

This work proposes an intelligent allocation of distributed generation (DG) units and shunt reactive compensators (SRC) with high penetration capacities into distribution systems for power loss mitigation using the Bald Eagle Search (BES) optimization algorithm. The intelligent allocation causes a reduction in voltage variations and enhances the voltage stability of the systems. The SRC units include shunt capacitors (SC), Static Var Compensators (SVC), and Distribution Static Compensators (DSTATCOM), which are determined according to their capacities. The optimization study includes the 33-bus and the 118-bus distribution systems as medium to large systems. Performance parameters, including the reactive power loss, Total Voltage Deviation (TVD), and Stability Index (SI), besides the power loss, are recorded for each optimization case study. When the BES algorithm optimizes 1, 2, and 3 DG units operating at optimal power factor (OPF) into the 33-bus systems, percentage reductions of power loss reach 67.84%, 86.49%, and 94.44%, respectively. Reductions of 28.26%, 34.47%, 35.24%, and 35.44% are achieved in power loss while optimizing 1, 3, 5, and 7 SRC units. With a combination of DG/SRC units, the power loss reductions achieve 72.30%, 93.89%, and 97.49%, optimizing 1, 3, and 5 pairs of them. Similar reductions are achieved for the rest of the performance parameters. With high penetration of compensators into the 118-bus system, the percentage reductions of power loss are 29.14%, 73.27%, 83.72%, 90.14%, and 93.41% for optimal allocations of 1, 3, 5, 7, and 9 DG units operating at OPF. The reduction reaches 11.15%, 39.08% with 1 and 21 devices when optimizing the SRC. When DG SRC units are optimized together, power loss turns out to be 32.83%, 73.31%, 83.32%, 88.52%, and 91.29% with 1, 3, 5, 7, and 9 pairs of them. The approach leads to an enhanced voltage profile near an acceptable range of bus voltages, reduces the voltage fluctuation substantially, and enhances the system stability. The study also ensures the BES algorithm’s capability to solve these nonlinear optimization problems with high decision-variable numbers

Smart Home IoT System by Using RF Energy Harvesting

IoT system becomes a hot topic nowadays for smart home. IoT helps devices to communicate together without human intervention inside home, so it is offering many challenges. A new smart home IoT platform powered using electromagnetic energy harvesting is proposed in this paper. It contains a high gain transmitted antenna array and efficient circularly polarized array rectenna system to harvest enough power from any direction to increase lifetime of the batteries used in the IoT system. Optimized energy consumption, the software with adopting the Zigbee protocol of the sensor node, and a low-power microcontroller are used to operate in lower power modes. The proposed system has an 84.6-day lifetime which is approximately 10 times the lifetime for a similar system. On the other hand, the proposed power management circuit is operated at 0.3 V DC to boost the voltage to ~3.7 V from radio frequency energy harvesting and manage battery level to increase the battery lifetime. A predictive indoor environment monitoring system is designed based on a novel hybrid system to provide a nonstatic plan, approve energy consumption, and avoid failure of sensor nodes in a smart home

Muscle Sonography in Inclusion Body Myositis: A Systematic Review and Meta-Analysis of 944 Measurements

Inclusion body myositis (IBM) is a slowly progressive muscle weakness of distal and proximal muscles, which is diagnosed by clinical and histopathological criteria. Imaging biomarkers are inconsistently used and do not follow international standardized criteria. We conducted a systematic review and meta-analysis to investigate the diagnostic value of muscle ultrasound (US) in IBM compared to healthy controls. A systematic search of PubMed/MEDLINE, Scopus and Web of Science was performed. Articles reporting the use of muscle ultrasound in IBM, and published in peer-reviewed journals until 11 September 2021, were included in our study. Seven studies were included, with a total of 108 IBM and 171 healthy controls. Echogenicity between IBM and healthy controls, which was assessed by three studies, demonstrated a significant mean difference in the flexor digitorum profundus (FDP) muscle, which had a grey scale value (GSV) of 36.55 (95% CI, 28.65–44.45, p < 0.001), and in the gastrocnemius (GC), which had a GSV of 27.90 (95% CI 16.32–39.48, p < 0.001). Muscle thickness in the FDP showed no significant difference between the groups. The pooled sensitivity and specificity of US in the differentiation between IBM and the controls were 82% and 98%, respectively, and the area under the curve was 0.612. IBM is a rare disease, which is reflected in the low numbers of patients included in each of the studies and thus there was high heterogeneity in the results. Nevertheless, the selected studies conclusively demonstrated significant differences in echogenicity of the FDP and GC in IBM, compared to controls. Further high-quality studies, using standardized operating procedures, are needed to implement muscle ultrasound in the diagnostic criteria