Renewable energy-based smart grids are famous nowadays due to their high intellectual properties. The world is starting new inventions in renewable energy-based electrical power generation systems to reduce global warming. However, a single renewable energy source cannot maintain a proper energy management system and reliability of power towards loads. Hence, integrating two or more systems is very important and can form a smart grid with an appropriate energy management system. Effective energy management system for a 4-wire 1-MW smart grid system is proposed in this paper. The system is composed of three solar plants and three wind farms with a battery bank. The battery energy management system can operate the complete system as a smart grid with the proper design of the controllers. The maximum power points of PV plants are tracked using a hybrid algorithm that merges the merits of Modified Invasive Weed Optimization and Perturb and Observe (P&O). Thus, the maximum power is obtained under partial shading conditions. The P&O algorithm is also developed to track the maximum power of wind farms. All the loads and generation units are connected in a ring-configuration distribution with a centralized battery energy management system. The loads are selected to be unbalanced, nonlinear and reactive to simulate practical cases. TS-Fuzzy based common inverter controller is implemented to maintain acceptable power quality, which is linked to the battery. The proposed inverter controller can work as a reactive power compensator, active power filter, voltage regulator under unbalanced load, and power balancing device between generation and load. Extensive Hardware-in-Loop (HIL) results are presented to validate the effectiveness of the proposed system.

Smart inverters are pivotal in modern renewable energy systems, enabling efficient grid integration, stability, and advanced control of distributed energy resources. While existing literature addresses their technical functionalities, significant research gaps persist in areas such as interoperability, cybersecurity, standardization, and the integration of artificial intelligence for adaptive control. This article provides a comprehensive review of smart inverter technologies, emphasizing their role in renewable energy applications, advanced control strategies, and unresolved challenges. By systematically analyzing recent advancements and case studies, the paper identifies critical limitations in current practices, including economic barriers, regulatory misalignments, and fault tolerance under dynamic grid conditions. The review contributes to the field by synthesizing dispersed knowledge, highlighting under-researched areas, and proposing actionable pathways for future innovation. The main findings reveal the transformative potential of AI-driven grid-forming inverters for enhancing grid stability and resilience. However, their widespread adoption is hindered by the absence of harmonized standards and misaligned policy frameworks. Consequently, this review underscores the urgent need for policymakers to develop and implement supportive regulatory structures that facilitate the deployment of AI-enabled smart inverters and establish unified standards to ensure interoperability and cybersecurity. This work serves as a foundational reference for researchers and policymakers aiming to address technical and systemic bottlenecks in smart inverter deployment.

Wireless charging systems for electric vehicles (EVs) have emerged as a key enabler for sustainable transportation, offering enhanced convenience, safety, and system integration compared to traditional plug-in charging methods. This paper presents a comprehensive review of wireless power transfer (WPT) technologies, highlighting their operating principles, system architecture, and recent advancements in both static and dynamic charging applications. Various WPT techniques, including inductive, capacitive, magnetic gear, and resonant inductive methods, are analyzed with respect to frequency range, efficiency, electromagnetic interference, and suitability for electric vehicle wireless charging systems (EVWCS). Emphasis is placed on compensation topologies such as series–series (SS), series–parallel (SP), parallel–parallel (PP), and hybrid LCC/LCL networks, which are instrumental in mitigating power fluctuations and improving efficiency under coil misalignment conditions. Moreover, control strategies—ranging from proportional–integral and passivity-based approaches to model predictive and sliding-mode control—are reviewed for their role in enhancing system stability and dynamic response. The integration of artificial intelligence, edge computing, and dual-side control architectures is also discussed as a pathway toward adaptive and intelligent power management in dynamic wireless charging systems (DWCS). Finally, the paper examines environmental, economic, and grid-integration considerations, concluding that the continued evolution of hybrid compensation networks and intelligent control algorithms will pave the way for efficient, scalable, and autonomous wireless charging infrastructure for next-generation EVs.

The static series compensator (SSC) has shown a significant capability to mitigate voltage dips, which are the most severe problem to sensitive loads. Also, it has been declared that the function of the SSC can be extended to work as a series active filter. This work proposes a moving-average filter to detect the fundamental component of the measured voltages and currents (needed to control the SSC) while using a double vector control algorithm to improve the transient performance of the SSC. This is made in order to accurately control the fundamental voltage component at the load terminals in the case of distorted grid voltage. Furthermore, a selective harmonic compensation strategy is applied to filter out the grid harmonics. The operation of the SSC under distorted utility conditions and voltage dips is discussed. The validity of the proposed controller is verified by experiments, carried out on a 10-kV SSC laboratory setup. Experimental results have shown the ability of the SSC to mitigate voltage dips and harmonics. It is also shown that the proposed controller has improved the transient performance of the SSC even under distorted utility conditions.