Low-cost photovoltaic-powered elevators (PVPEs) have gained ever-increasing attention in the last few years for their advantages in terms of renewable energy and low maintenance costs after installation. In this paper, four high-step-up DC-DC converters for low-voltage sources such as solar photovoltaic, fuel cells, and battery banks are proposed. Their performances are evaluated in terms of optimal capability and high reliability. Among the four proposed architectures, the bootstrap converter is selected for its ability to restrict losses and other redundant parameters. The proposed converter drives the inverter-driven switched reluctance motor (SRM) assembly through a directly coupled method, which eliminates the need for battery banks while aiding in cost reduction. The prototype model is implemented, and results are validated, showing promising performance and thus being very efficacious for application to low-cost PVPEs.
The world depends heavily on electrical energy for accessing technologies. For the generation of electricity, technology can utilize renewable energy sources like solar energy and wind energy. Solar photovoltaic (PV) systems occupy space among consumers due to their feasibility, flexibility, cost, and simple implementation procedures. The solar PV system experiences many factors causing power loss like partial shading, hotspots, and diode failure. In this work, a new static PV array configuration, named Renzoku puzzle pattern-based array configuration, is proposed. This proposed configuration technique was designed to overcome the drawbacks of the previously proposed array configurations in terms of power generation, fewer mismatch losses, a high shade-dispersion rate, and consistent performance under any level of partial shading. The proposed array configuration has been validated using both simulation and hardware. The simulation is carried out in a 9 × 9 PV array in MATLAB/Simulink®. The performance analysis, results, and corresponding characteristic curves are presented in this manuscript.
The power quality (PQ) has been significantly affected by the integration of intermittent non-conventional sources (NCS) into the local distribution system in addition to the adoption of power electronic technologies to regulate non-linear loads. This article combines the H-bridge cascade five-level unified power quality conditioner (5L-UPQC) with the wind power generation system (WPGS), solar photovoltaic power generation system (SPVGS), and battery storage system (BSS) as an effective approach to address PQ problems. The utilization of the Levenberg–Marquardt backpropagation (LMBP)-trained Artificial neural network controller (ANNC) in the UPQC is recommended for generating appropriate reference signals for the converters. This eliminates the requirement for conventional complex conversions, such as abc, dq0, and αβ. Moreover, the artificial neuro-fuzzy interface system (ANFIS) is recommended for achieving a DC-link balance. Football game optimization (FBGO) is utilized to determine the optimal shunt and series filter characteristics. The major objectives of the proposed system are to reduce the current waveform irregularities, resulting in a decrease in the total harmonic distortion (THD), an enhancement in the power factor (PF), the mitigation of supply voltage imbalances and disturbances, and the maintenance of a steady direct-current link capacitor voltage (DLCV), despite the variations in the load, solar irradiation, and wind velocity. The efficiency of the suggested strategy is assessed using four case studies that involve different loads, variable wind velocities, and source voltage balancing conditions. Based on the simulation studies and obtained results, the suggested method significantly decreases the THD to values of 2.91%, 3.63%, 3.75%, and 3.50%. Additionally, it achieves a power factor of unity, which is considerably lower compared to other multilevel schemes that use the traditional symmetrical reference frame (SRF) and instantaneous reactive power (pq) methods. This design has been executed using the MATLAB/Simulink program.
Frontiers in Physiology
Ligand recognition and regulation of ion channel proteins