Sivagama Sundari Meenakshi Sundaram

Even though water covers the surface of the Earth in three quarters, many nations face shortages of drinkable water due to rapid global population and industrial growth. Solar power emerges as an efficient solution, particularly in hot climates with water and energy scarcity. This research focuses on a practical solar solution known as a solar still, a basic apparatus designed to convert available salty water into potable water. In this study, a single-slope solar still using acrylic material is experimentally analysed, predicting daily distillate production under varying climatic conditions. Using heat and solar radiation, solar distillation offers a simple, affordable, and small-scale approach to clean water production. The solar still, utilizing acrylic sheets as a basin material, minimizes heat losses and enhances water evaporation rates, making it a promising technology for addressing water scarcity issues. The experimental analysis results revealed a distillate output of 420 ml per 0.49 m² per day.

Today’s critical goals in sensor network research are extending the lifetime of wireless sensor networks (WSNs) and lowering power consumption. A WSN necessitates the use of energy-efficient communication networks. Clustering, storage, communication capacity, high configuration complexity, low communication speed, and limited computation are also some of the energy limitations of WSNs. Moreover, cluster head selection remains problematic for WSN energy minimization. Sensor nodes (SNs) are clustered in this work using the Adaptive Sailfish Optimization (ASFO) algorithm with K-medoids. The primary purpose of research is to optimize the selection of cluster heads through energy stabilization, distance reduction, and latency minimization between nodes. Because of these constraints, achieving optimal energy resource utilization is an essential problem in WSNs. An energy-efficient cross-layer-based expedient routing protocol (E-CERP) is used to determine the shortest route, dynamically minimizing network overhead. The proposed method is used to evaluate the packet delivery ratio (PDR), packet delay, throughput, power consumption, network lifetime, packet loss rate, and error estimation, and the results were superior to existing methods. PDR (100%), packet delay (0.05 s), throughput (0.99 Mbps), power consumption (1.97 mJ), network lifespan (5908 rounds), and PLR (0.5%) for 100 nodes are the performance results for quality-of-service parameters.

This paper proposes a new Pulse Width Modulation technique for single phase cascaded H-bridge multilevel inverter for maintaining the output voltage across the load side with reduction in Total Harmonic Distortion (THD). The novelty of this paper is to equalize the area under the multilevel output voltage with that of area under the pure sine wave in discrete time periods. The main objective of this design is to maintain the desired output voltage with minimization of THD at the dynamic load conditions. The comparison between the proposed PWM technique with conventional Optimized Harmonic Stepped Waveform PWM is also shown and the results are proven that the proposed method is comparatively better. Particle Swarm Optimization algorithm is employed for solving the non-linear objective function and finding out the optimal switching angles for the MLM switches. MATLAB software is used to simulate the proposed design. The detailed mathematical modeling on the area equalization techniques with the advantage of using the proposed method than OHSW PWM technique is also presented in this paper.

A Single phase Cascaded H-bridge multilevel inverter topology fed by Photovoltaic source for the reduction of harmonics is proposed in this paper. Selective Harmonic Elimination technique is employed for elimination of 5th, 7th, 11th and 13th lower order harmonics and the particle swarm optimization algorithm is employed for estimating the switching angles. As a novelty, in order to maintain the power balance among the various sources, a cyclic selection procedure is adopted that over a period of operation also the sources equally contribute for the output power. MATLAB software is used for optimization and the results show the effectiveness of the proposed algorithm. The performance of the Particle Swarm Optimization Algorithm has been compared against the performance of the Genetic Algorithm.