Globally, the demand for energy from renewable sources is growing due to the increasing electricity consumption and the pollution of fossil fuels. The government has framed various policies to facilitate green energy generation, encouraging renewable energy source usage through PV installations in multiple sectors, including educational institutions. The primary objective of this paper is to propose a methodological approach for analysing the performance of the installed PV system on the rooftop of a university building in Tamil Nadu, India. The site selected is favourable for electricity generation from PV systems with an average global solar radiation of 5.82 kWh/m²day. Solar energy changes periodically with annual and daily variations and is not steady due to seasonal changes. The step-by-step performance assessment and the annual performance of the 100-kW solar PV system, which was instituted in 2019, with the forecasted parameters, are presented in this paper. Therefore, the assessment analysis is carried out in four phases: feasibility assessment, Energy yield assessment, Life cycle assessment, and Power quality assessment. To improve the solar PV output and efficiency, considering the solar irradiation, temperature, wind velocity, etc., PV yield is measured to evaluate the PV system's energy metrics. This paper also considers the carbon credits earned, solar power generated in the location, and the payback period. The power quality assessment is carried out in this paper to test the PV plant's compliance with effective grid integration.

This study investigates the long-term performance of a 52-kW on-grid solar PV plant in the Mechanical ‘C’ block, SRM Institute of Science and Technology (SRMIST). This article delivers a simple approach that would act as a pivot for PV system assessment. Therefore, methodologies like Energy yield analysis, Energy distribution, and Life cycle costing are implemented. This empowers the methods to facilitate pre-auditing, energy conservation, and economic analysis. The performance ratio and a capacity factor of the 52-kW PV plant in 2020 are determined as 60 % and 12.8 %, respectively. The study offers that the plant has a less simple payback period and energy pack time for 2020. From this study, the issues identified in the plant are highlighted with the solution. It also paves the way for the researchers to suggest the solutions for the underutilization of the plant, especially in the situations like fault occurrence, pandemic conditions, etc.

In this paper, a standalone permanent magnet synchronous generator (PMSG) system is designed to generate power at maximum power point (MPP). The variable speed operation of wind energy conversion system consists of PMSG, controlled rectifier and voltage source inverter co to the load. Proportional integral (PI), sliding mode (SM), and feed forward neural network (FFNN) control strategies are applied in field oriented control (FOC) at generator side converter. A comparative study on power generated at maximum power point (MPP) is done with these controllers using simulation. Hill climb search (HCS) method is applied to attain MPP. Load side inverter control strategy involves the PI and SM controllers in order to maintain the unity power factor and to control the active and reactive power for nonlinear load. The control strategies are modelled and simulated with MATLAB/Simulink. The effectiveness of proposed control method is demonstrated using simulation results.

This paper presents the development of novel models that integrate induction machines with HVAC equipment, such as pumps, heat pumps, and chillers, to analyze the impact of electrical parameters on the operational performance of thermo-fluid systems. The proposed model employs a coupling technique that captures the dynamic interactions between induction machines and HVAC systems. By integrating electrical, thermal, and mechanical dynamics, the models provide a comprehensive framework for simulating real-world scenarios, including interactions with the electrical grid. This achievement was made possible through the development of a Computationally Efficient and Accurate Induction Machine (CEAIM) model. Implemented using the equation-based Modelica language, the CEAIM model has been validated against experimental results, manufacturer data sheets, and various operating conditions. Its performance has been compared with existing induction machine models in the Modelica Standard Library (MSL), demonstrating superior accuracy and computational efficiency. The CEAIM model predicts torque, speed, and power consumption with a coefficient of determination (R²) ranging from 0.98 to 1 and a coefficient of variation of root mean square error (CVRMSE) between 0.27% and 6.67%. Additionally, CEAIM scales more efficiently than conventional MSL models, with a slower computational growth rate in large-scale simulations. After thorough validation of the CEAIM model, it was coupled with HVAC equipment as this approach provides a detailed multi-dimensional view of capturing electrical transients and mechanical performance. To support this, a case study was conducted to showcase its capabilities.

A scientific instrument which measures the magnetic field strength and its direction is known as Magnetometer. In this article a three axis Fluxgate Magnetometer is constructed by using simple ring core and simple drive circuits instead of specialized components like Hall Effect sensors. This type of Fluxgate magnetometers is working on the principle of magnetic flux linking a coil depends on the orientation of the coil with respect to the earth’s magnetic field lines. Here the three single axis fluxgate magnetometers are designed and placed perpendicular to each other on a board. The circuit is designed to produce 100 KHz frequency and to measure the Magnetic field in the range up to 7 Tesla. The sensitivity is tested through an external electromagnet. The readings are obtained in LAB-VIEW platform and the three-axis data is displayed.