This work focuses on the design and analysis of wind flow modifier (WFM) modeling of a vertical axis wind turbine (VAWT) for low wind profile urban areas. A simulation is carried out to examine the performance of an efficient low aspect ratio C-shaped rotor and a proposed involute-type rotor. Further, the WFM model is adapted with a stack of decreased diameter tubes from wind inlet to outlet. It accelerates the wind velocity, and its effectiveness is examined on the involute turbine. Numerical analysis is performed with a realizable K-ε model to monitor the rotor blade performance in the computational fluid dynamics (CFD) ANSYS Fluent software tool. This viscous model with an optimal three-blade rotor with 0.96 m² rotor swept area is simulated between the turbine rotational speeds ranging from 50 to 250 rpm. The parameters, such as lift–drag coefficient, lift–drag forces, torque, power coefficient, and power at various turbine speeds, are observed. It results in a maximum power coefficient of 0.071 for the drag force rotor and 0.22 for the lift force involute rotor. Moreover, the proposed WFM with an involute rotor extensively improves the maximum power coefficient to an appreciable value of 0.397 at 5 m/s wind speed, and this facilitates efficient design in the low wind profile area.

This work describes an optimum utilization of hybrid photovoltaic (PV)—wind energy for residential buildings on its occurrence with a newly proposed autonomous fuzzy controller (AuFuCo). In this regard, a virtual model of a vertical axis wind turbine (VAWT) and PV system (each rated at 2 kW) are constructed in a MATLAB Simulink environment. An autonomous fuzzy inference system is applied to model primary units of the controller such as load forecasting (LF), grid power selection (GPS) switch, renewable energy management system (REMS), and fuzzy load switch (FLS). The residential load consumption pattern (4 kW of connected load) is allowed to consume energy from the grid and hybrid resources located at the demand side and classified as base, priority, short-term, and schedulable loads. The simulation results identify that the proposed controller manages the demand side management (DSM) techniques for peak load shifting and valley filling effectively with renewable sources. Also, energy costs and savings for the home environment are evaluated using the proposed controller. Further, the energy conservation technique is studied by increasing renewable conversion efficiency (18% to 23% for PV and 35% to 45% for the VAWT model), which reduces the spending of 0.5% in energy cost and a 1.25% reduction in grid demand for 24-time units/day of the simulation study. Additionally, the proposed controller is adapted for computing energy cost (considering the same load pattern) for future demand, and it is exposed that the PV-wind energy cost reduced to 6.9% but 30.6% increase of coal energy cost due to its rise in the Indian energy market by 2030.

The measurement and control of humidity is a major challenge that affects the sensing properties of sensors used in high-precision equipment manufacturing industries. Graphene Oxide(GO)-based materials have been extensively explored in humidity sensing applications because of their high surface area and functional groups. However, there is a lack of effective bulk-manufacturing processes for the synthesis of 2D-based nanocomposites with comb electrodes. Moreover, water intercalation within the layers of 2D materials increases recovery time. This work demonstrates the enhanced sensing characteristics of a capacitive/resistive GO-MnZnO nanocomposite humidity sensor produced using a cost-effective single-pot synthesis process. The in-plane sensing layer consistently improves sensitivity and reduces response time for a wide range of relative humidity measurements (10% to 90%). Interdigitated gold electrodes with varying numbers of fingers and spacing were fabricated using photolithography on a Si/SiO₂ for a consistent sensor device platform. The choice of nanomaterials, dimension of the sensor, and fabrication method influence the performance of the humidity sensor in a controlled environment. GO nanocomposites show significant improvement in response time (82.67 times greater at 40% RH) and sensitivity (95.7 times more at 60% RH). The response time of 4.5 s and recovery time of 21 s was significantly better for a wider range of relative humidity compared to the reduced GO-sensing layer and ZnMnO. An optimized 6 mm × 3 mm dimension sensor with a 28-fingers comb was fabricated with a metal-etching process. This is one of the most effective methods for bulk manufacturing. The performance of the sensing layer is comparable to established sensing nanomaterials that are currently used in humidity sensors, and hence can be extended for optimal bulk manufacturing with minimum electrochemical treatments.

Gas insulated substation generates very fast transient overvoltages (VFTOs) in power systems because of disconnector switching operations. The present design of metal–oxide arrester may not be effective against these VFTs and so the arrester fails to operate under VFTO. At this point, it becomes essential to improve the electrical behaviour of arrester. Some of the possible measures for improving the electrical behaviour of arrester blocks are the procurement of higher‐voltage gradient, reduction of arrester capacitive effect and reduction in the time lag between residual voltage and current surge. With this background, the microstructural and electrical parameters of arrester block are modified by doping scandium trioxide with basic composition and the samples are prepared using different sintering processes. Subsequently, the voltage gradient, capacitance and the time lag are found for the prepared samples. The performance of new arrester blocks are investigated against VFTO and the results are compared with conventional arrester blocks. From that, it is perceived that the new arrester samples have improved parameters and might be used for protection of power system against VFTO.