Grid-connected sustainable systems are increasingly susceptible to power quality (PQ) issues due to advancements in power electronics technology. Electric Vehicle Charging Stations (EVCS) experience significant distortions in two scenarios: (1) when connected to the grid, and (2) when operating independently on battery energy storage devices (BESD) and solar energy. Addressing these distortions is crucial for improving the system's Power Quality. To achieve this, a hybrid control approach is proposed, combining a Fractional Order Proportional Integral Controller (FOPIDC) for the shunt filter of the unified PQ conditioner (UPQC) with an Adaptive Neuro-Fuzzy Inference System (ANFIS). The primary goal of the UPQC is to maintain steady voltage across the DC capacitor (SVDC) during variations in load (such as EVCS, and non-linear balanced/unbalanced loads) and solar irradiation. Additional objectives include mitigating disturbances, voltage swell/sag, and grid voltage imbalances. The performance of the developed model is evaluated in both grid-connected and islanding scenarios across four distinct test cases. To demonstrate its effectiveness, the proposed system is compared to industry-standard controllers such as Sliding Mode Controllers (SMC) and Proportional Integral Controllers (PIC). While the methodology reduces THD to 2.40%, 2.23%, and 2.44%, it is slightly less effective than some existing methods highlighted in the literature.

The management and utilization of sustainable resources have undergone a significant transformation as a result of the integration of Internet of Things (IoT) technology into the renewable energy sector. IoT has simplified the optimization of renewable energy sources, including solar, wind, and hydropower, by leveraging sensor technology, data analytics, and connectivity. This optimization has resulted in major advances in energy production efficiency, equipment maintenance procedures, and the smooth integration of renewable energy into established power grids. Operators can optimize energy output while reducing waste by adjusting operations in real time through continuous monitoring and analysis of data gathered from IoT-enabled sensors. Moreover, by predicting and fixing possible problems before they arise, predictive maintenance algorithms significantly contribute to increased equipment reliability by lowering downtime and operating expenses. Furthermore, IoT systems allow for dynamic modifications to energy flow, guaranteeing the stability and dependability of the integration of renewable energy sources into the current power networks. This research investigates the use of IoT technology in the renewable energy sector in detail, exploring its several uses and assessing how it affects industry standards, sustainability goals, and the overall energy environment.

Solar photovoltaic technology has experienced significant growth and development in recent years, making it a significant figure in the field of renewable energy. The basic principle of solar PV technology involves the conversion of sunlight into electricity using semiconductor materials. Silicon has consistently been the predominant material used in solar PV cells, but there is ongoing research and development into alternative materials. The choice of material for solar PV cells is crucial as it directly impacts the efficiency, cost, and environmental impact of the technology. Silicon-based solar cells have achieved high levels of efficiency and reliability, but they can be expensive to produce. On the other hand, emerging materials such as perovskites show great promise in terms of cost-effectiveness and efficiency, but they still face challenges related to stability and scalability. In addition to the semiconductor material, other components such as conductive metals, transparent conductive oxides, and encapsulation materials also play a crucial role in the performance and longevity of solar PV systems. Understanding the material properties, fabrication processes, and environmental impact of solar PV materials is essential for making informed decisions in the design and implementation of solar PV systems.

The integration of renewable power sources into the grid presents a complex challenge, as the grid operates at AC voltage, while photovoltaic (PV) arrays generate DC power. A 3-phase inverter synchronizes with the grid’s voltage and frequency for efficient energy integration. In conventional technique, a 3-ph 6-switch (B6) inverter is used for sharing the power to the grid. In this paper reduced switch count 3-ph 4-switch (B4) inverter topology is introduced with reduced power losses. This topology has 4 insulated gate bipolar transistor (IGBT) switches and two capacitors replacing the other 2 switches positioned in one leg of the inverter, which connects to a grid connected PV system. A grid synchronization method called synchronous reference frame (SRF) based proportional integral (PI) is used to track the phase angle of the grid and subsequently inject current into the grid. A B4 inverter is operated by a novel space vector pulse width modulation (SVPWM) control technique which operates in 4 possible switching states. A comparative analysis is carried out with the PV array grid integration connected through B4 and B6 inverter topologies with SRF control. The modeling and design are carried out in a MATLAB/Simulink environment with graphs plotted according to the conditions. The comparative analysis validates the importance of SRF controllers for the grid integration of any renewable source.

A novel 3-ph 4-switch inverter (TPFSI) is described in this study to reduce the inverter's size, complexity, cost, and losses during the conduction and switching process. This TPFS inverter is based on the principle of similarity of a 3-ph 6-switch inverter (TPSSI) where αβ plane is separated into six sectors to form the required reference voltage space vector. It has been demonstrated that TPFS inverters are more efficient than TPSS inverters while operating with different loads. A mathematical concept for the space vector pulse width modulation (SVPWM) technique has been developed for TPFSI by using Clarke's transformation. In this paper, a TPFS inverter model is designed to reduce the harmonic content in the output voltage and current responses when connected to different loads. The suggested modulation method enhances the output voltage/current response, resulting in usually balanced waveforms and reduced harmonic distortion. MATLAB/Simulink software is utilized to analyze the output response of both inverters.