The ability to identify asymptotic scattering is critical for the continuous operation of modern combat systems. In the active sonar equation, acoustic target strength is crucial. The plane-wave propagation target strength equation predicts far-field reradiated intensity. Submarines defend themselves by being invisible. Sonar can be used to detect submarines. Saltwater readily absorbs radio waves. Commercial fishing and scientific ocean exploration both make use of sonar technology. Acoustic wave reflection reduces the area requirements of ocean depth sections, therefore submarine designers take this into consideration. The Target Strength (TS) of a sonar target is used to assess its size. The Pressure Acoustic-Boundary Element Model (PA-BEM) of the High-Frequency Boundary Model (HFB) illuminates and simplifies the TS analysis of the Benchmark Target Echo Strength Simulation (BeTTSi) benchmark submarine. We explore how subsea shape, material qualities, and operation frequency affect acoustic target strength using comprehensive models. The findings underline the need of correctly characterising the structural sections of the submarine and their impact on dispersion. They also help with research into the submarine’s acoustic signature, detectability, and potential detection mitigation measures.

A smart energy management controller is required for effective source coordination and load demand management. This work proposes a novel instantaneous current reference technique for use in power management of hybrid power systems (HPS), both autonomous and interconnected with the grid. A grid integrated hybrid power system (GI-HPS) includes both the AC grid and additional sources used in industrial and commercial environments. Solar photovoltaic (SPV) panels, wind turbine generators, proton exchange membrane fuel cells, and batteries are all part of the test system. The suggested energy management system (SEMS) manages power from the hybrid power source and the energy storage components to meet the load needs. The recommended SEMS can transit between 12 different modes of operation to fulfil the load demand requirements. The SEMS employs a scaling factor N to accelerate the rate at which the measured current approaches the reference current. The proposed scaling factor significantly improves the SEMSs dynamic performance since it can quickly respond to the changes in the source and load characteristics. The dependability of an HPS powered by a variety of renewable energy sources can also be improved.

In this paper, a combined approach of Principal Component Analysis (PCA)-based Extreme Learning Machine (ELM) for boiler output forecasting in a thermal power plant is presented. The input used for this prediction model is taken from the boiler unit of the Yermarus Thermal Power Station (YTPS), India. Calculation of the accurate electrical output of a boiler in an operating system requires the knowledge of hundreds of operating parameters. The dimensionality of the input dataset is reduced by applying principal component analysis using IBM@SPSS Software. In the process of principal component analysis, a dataset of 232 parameters is standardized into 16 principal components. The total dataset collected is divided into training and testing datasets. The extreme learning machine is designed for various activation functions and the number of neurons. Sigmoid and hyperbolic tangent activation functions are studied here. Its generalization performance is examined in terms of the Mean Square Error (MSE), Mean Absolute Error (MAE), Root Mean Square (RMSE), and Mean Absolute Percentage Error (MAPE). ELM and PCA–ELM are compared. In both the ELM and PCA–ELM models, when the extreme learning machine was designed with a sigmoid activation function with 100 nodes in the hidden layer, RMSE was 5.026 and 4.730, respectively. Therefore, the developed combined approach of PCA–ELM proved as a promising technique in forecasting with reduced errors and reduced time.

In light of the constant need for more energy, modern society is characterized by constant technical development, especially in the field of electricity. Due to the limitations of the voltage at which it may be given, it has a finite value. Energy providers and consumers are both subject to consumption restrictions. Multiphase systems are a viable option for dealing with this issue. Multiphase systems are currently being used to tackle the issue, and progress in this area of study is swift. The importance of multiphase supply cannot be overstated in the realm of drives and other necessities. The Five Phase Induction Motor (FPIM) construction and performance analysis are discussed in this study. MATLAB/SIMULINK is used to evaluate FPIM’s performance. The experimental findings of the developed FPIM are presented in this work.

Introduction. In this world of technical advancement, conventional resources are at the stage of destruction. To avoid such problems, we are going to use an alternative energy source namely solar by photovoltaic effect. The demand for multilevel inverters increased as they are used for different dynamic (high) voltage and dynamic (high) power appliances as they are capable of producing the output wave shape with low total harmonic distortion. Novelty. A new multilevel inverter is used in adding a (bidirectional) two way switch in between the capacitor and a traditional H-bridge module. This produces a better sine wave. By series connection of these two H-bridge modules, nine levels output voltage including zero is possible. The purpose of the proposed topology is reduction in the number of switches and it gives the good result with comparatively less power loss when it is compared with the other normal basic traditional inverters of the same output quality. Methods. In this paper, sinusoidal pulse width modulation technique is used for the working of the switches in the multilevel inverter. The results are verified by using simulation and also experimental setup is done. From the results it is observed that the proposed topology with reduced number of switches gives lower electromagnetic interference, lower harmonic distortion. Practical value. The total harmonic distortion value in the simulation is 14.4 % and practically it is 13.8 %.

Nowadays the utilization of Electric Vehicles (EVs) has greatly increased. They are attaining greater attention due to their impacts on the grid at the distribution level. However, due to the increased need for electricity, EVs are also used to serve the load in the instance of electrical failure in the distribution systems. This paper presents a new approach to a service restoration method for a low-voltage distribution network at the time of a power outage using existing EVs available in a parking place. The objective function formulated here was a constrained linear optimization model. It aimed to develop priority-based scheduling of the residential user appliances while meeting all the operational constraints if the EV’s power was in a deficit at the hour of the outage. Weight factors were assigned to various residential appliances to decide their priority while scheduling. To substantiate the proposed methodology, a day load profile of a 20 kVA distribution transformer feeding eight residential users is considered. This was tested during an hour-long power outage scenario in the MATLAB and LINGO platforms, with four EVs available during the outage period. This method restored the maximum power to the residential appliances.