The incorporation of energy from renewable sources into the power grid is crucial for achieving sustainable and environmentally friendly power generation. This study proposes an artificial intelligence (AI)-enabled methodology for the analysis & optimization of “grid-tied solar photovoltaic (PV)-fuel cell hybrid power systems.” The research aims to demonstrate how AI techniques can assist in decision-making, improve system performance, and achieve higher levels of energy efficiency and financial viability. The study presents the results of a project focusing on a renewable energy system that feeds into the grid and powers a university building. The hybrid power system’s performance and cost were evaluated using unified approaches to modeling, simulation, optimization, and control. The findings indicate that the AI-optimized “solar PV-fuel cell hybrid system connected to the grid” offers excellent performance, meeting 74% of the building’s energy needs through renewable sources. The system also achieved a low levelled price for energy and minimise CO2 emissions, further enhancing its environmental sustainability. The proposed AI-enabled approach proves to be a promising solution for creating grid-connected renewable energy systems with significant benefits for energy efficiency, cost-effectiveness, and environmental impact.

Power quality has become an important factor in power systems, for consumer and household appliances with proliferation of various electric/ electronic equipment and computer systems. The main causes of a poor power quality are harmonic currents, poor power factor, supply voltage variations, etc. In recent years the demand for the quality of electric power has been increased rapidly. Power quality problems have received a great attention nowadays because of their impacts on both utilities and customers. Voltage sag, swell, momentary interruption, under voltages, over voltages, noise and harmonics are the most common power quality disturbances. This paper proposes a new connection for a unified power quality conditioner (UPQC) to improve the power quality of two feeders in a distribution system. This paper illustrates how UPQC can improve the power quality by mitigating all these PQ disturbances. The proposed configuration of the UPQC is developed and verified for various Power Quality disturbances by simulating the model using PSCAD/EMTDC. The disturbances considered here are according to IEC Electromagnetic Compatibility Standards.

The aging of PV cells reduces their electrical performance i.e., the parasitic parameters are introduced in the solar panel. The shunt resistance (R_Sh), series resistance (R_S), photo current (I_Ph), diode current (I_d), and diffusion constant (a₁) are known as parasitic or extraction parameters. Cracks and hotspots reduce the performance of PV cells and result in poor V–I characteristics. Certain tests are carried out over a long period of time to determine the quality of solar cells; for example, 1000 h of testing is comparable to 20 years of operation. The extraction of solar parameters is important for PV modules. The Tabu Search Optimization (TSO) algorithm is a robust meta-heuristic algorithm that was employed in this study for the extraction of parasitic parameters. Particle Swarm Optimization (PSO) and a Genetic lgorithm (GA), as well as other well-known optimization methods, were used to test the proposed method’s correctness. The other approaches included the lightning search algorithm (LSA), gravitational search algorithm (GSA), and pattern search (PS). It can be concluded that the TSO approach extracts all six parameters in a reasonably short period of time. The work presented in this paper was developed and analyzed using a MATLAB-Simulink software environment.

UPQC, Unified Power Quality Conditioner is multifunctional device in FACTS family which can provide independent or combined functions of shunt compensator, series compensator, voltage regulator and phase angle regulator. UPQC can compensate not only harmonic currents and unbalances of a non-linear load but also voltage harmonics and unbalances of the power supply which improves the power quality offered for other harmonic sensitive loads. The proposed work is to develop a power quality conditioner with a simple and robust controller to compensate for the voltage sag, voltage unbalance, harmonics, sag with unbalance, unbalance with harmonics. In traditional proportional-integral (PI) or proportional-integral derivative (PID) feedback controllers, careful tuning is required and the residual tracking error due to hysteresis and dynamic effects persists from one cycle to the next. The proposed controller will drive the tracking error asymptotically to zero as the number of operating cycles increases. Since control circuit relies on the availability and quality of sensor measurement, a circuit development for detecting faulty sensors and to restore the missing sensors using ANN and PSO is also proposed. The proposed work is to develop an ANN based fault tolerant control system for controlling of UPQC connected to a 440 V radial distribution network.

Nowadays protection with transformers in DG units embedded to utility has been topic of research, transformers not only transfers power with constant frequency; it also plays a remarkable role in protection as well. The integration of “Distributed generation” units (DG)into distribution system can be complete through power conditioning units (PCU), transformers and protective devices. Though protection devices are essential to give protection andalter their capacity as per the high penetrationof DG's. This paper discussed aboutdistributed generation units interfaced to utility with different transformer connectionslike Delta/Delta, Delta/Star grounded, Star grounded/Delta, Star grounded/Star grounded. It investigates how this transformer connections shows impact on protection. For this different DG units are designed, interfaced and tested with different transformer connections. In proposed approachStar grounded/Star grounded configuration describe optimalpower variations during the faultsand it is recommended to protection applications of cogeneration integration to utility. Simulations have been performed in MATLAB Simulink Software.