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A cloud computing-based power optimization system (CC-POS) is an important enabler for hybrid renewable-based power systems with higher output, optimal solutions to extend battery storage life, and remotely flexible power distribution control. Recent advancements in cloud computing have begun to deliver critical insights, resulting in adaptive-based control of storage systems with improved performance. This study aims to review the recently published literature on the topic of power management systems and battery charging control. The role of intelligent based cloud computing is to improve the battery life and manage the battery state of charge (SoC). To achieve this purpose, publishers’ databases and search engines were used to obtain the studies reviewed in this paper. We identify and review the purpose, achievements, tools/algorithm, and recommendations for each survey work, and thus outline a number of key findings and future directions. Furthermore, the review includes a listing of novels and recently used algorithms. Additionally, a critical review of 174 research articles were analyzed as per Web of Science (WoS) and Scopus database. The key findings of this study are discussed in two key conceptual frameworks that contain a power optimization system and an optimal battery management system. The power transmission, distribution, and charge and discharge processes are controlled and stored on cloud computing using the power mix between hybrid renewable energy and other power sources.

Smart grid system is evident with control technologies and digital communications systems. The cyber–physical system is a critical infrastructure connected with complex drives and devices. The modern smart grid’s prominent communication standard adopts high scalability, supports numerous communication devices’ input/outputs, and has multi-vendor interoperability. Cyber-attack leads to an unstable power grid system and enormous economic loss. Throughout different cyber-attack, distributed denial of service attack is mostly destructive to smart grid infrastructure. This paper investigates smart grid cyber security systems and the communication vulnerabilities of other communication protocols. A comprehensive study on distributed denial of service attack techniques and detection approaches is present. Finally, examine a new hybrid machine learning-based distributed denial of service attack detection technique for a sustainable smart grid system.

Smart grid networks face several cyber-attacks, where distributed denial-of-service (DDoS) attacks distract the grid network. The synchrophasor technique protects the wide-area measurement system (WAMS) from the complex problem and addresses different issues in a grid. The DDoS attack detection strategy is complicated due to attack complexities, vendor specifications, and communication standard protocols. Attacker target phasor measurement unit (PMU) data on the phasor data concentrator (PDC) database in WAMS. However, during the cyber-attack, the framework ensures the end application uses the normal PDC datastream. The proposed attack detection technique efficiently verifies PMU-generated data in WAMS. However, numerous machine learning algorithms are used to detect DDoS attacks, but the best detection model is still given open choices. The motivation of this study: (a) which machine learning algorithm will be suitable for DDoS attack detection and (b) what would be the accuracy of training algorithms. This study presents a machine learning-based hybrid technique that achieves 83.23% accuracy. Python compiler is used to execute the proposed model, and the result shows that the proposed detection approach efficiently improves the DDoS attack detection accuracy.

In this paper, an active equalization circuit based on resonant converter is presented. This equalization circuit has been proposed to equalize the direct cell-to-cell voltage in a string. All electrochemical energy storage devices are connected in series. Using this equalization circuit energy transfer from higher energy and charge capacitive cell to lower energy and charge cell in the string. All MOSFET switches are operated by complementary Pulse-Width Modulation (PWM) signal. The working principle of this equalization circuit like that of a switches-capacitor equalization circuit. In this circuit, a single Inductor (L) capacitor (C) energy carrier and bidirectional low voltage MOSFET switches are used so that it can recover maximum energy, reduce conduction loss, and improve the switching loss drawback, reduce the equalization time duration between two cells and achieved zero voltage gap. This equalization circuit is bidirectional and operates under the three modes, namely, charging, discharging, and relaxation mode. The proposed circuit details, the working principle, and the mathematical analyzes are presented. The simulation results are validated by the demonstration of an experimental prototype hardware testbed. The experimental results based on lithium-ion, lead–acid, and super-capacitor are presented. This equalization circuit is low cost and occupies little space with efficiencies of 96%, 94.2%, and 84.43% for Li-ion, lead–acid and super-capacitor respectively.

Utilities produce and supply products following local requirements and with the synchronizations which connect subscribers. Harmonics is a power efficiency/quality variable caused by electronic devices that domestic and industrial consumers use. The famous IEEE Standard 519 is maintained to calculate harmonic limits, which ensures power efficiency. In a standard power system, currents and voltages generate pure sine wave signals during regular operations. As harmonics influence the power system, they cause interference in the sine wave signals. So, the best practice method should be used to resolve the harmonics issue. One of the problem-solving techniques of harmonics is the measurement and reduction of harmonics detection, and it uses Fast Fourier Transform (FFT). Therefore, power output should assess in a peer-to-peer Blockchain scheme by measuring and minimizing harmonics detection. This paper uses a Shunt Active Power Filter (SHAPF). It describes the simulation analysis and reduction of harmonics detection in a peer-to-peer interconnected 3-phase power system with the help of an FFT algorithm. This research was carried out to assess the efficiency of the AC signal by collecting, processing, and evaluating power data. Using the shunt active filter, the proposed design outperformed the traditional methods for both six and twelve pulse rectifiers, achieving total harmonic distortion (THD) of only 1.42% and 0.92%, respectively.