Cameroon is currently grappling with a significant energy crisis, which is adversely affecting its economy due to cost, reliability, and availability constraints within the power infrastructure. While electrochemical storage presents a potential remedy, its implementation faces hurdles like high costs and technical limitations. Conversely, generator-based systems, although a viable alternative, bring their own set of issues such as noise pollution and demanding maintenance requirements. This paper meticulously assesses a novel hybrid energy system specifically engineered to meet the diverse energy needs of Douala, Cameroon. By employing advanced simulation techniques, especially the Hybrid Optimization Model for Electric Renewable (HOMER) Pro program, the study carefully examines the intricacies of load demands across distinct consumer categories while accommodating varied pricing models. The paper offers a detailed analysis of the proposed grid-connected PV/Diesel/Generator system, aiming to gauge its performance, economic feasibility, and reliability in ensuring uninterrupted energy supply. Notably, the study unveils significant potential for cost reduction per kilowatt-hour, indicating promising updated rates of $0.07/kW, $0.08/kW, and $0.06/kW for low, medium, and high usage groups, respectively. Furthermore, the research underscores the importance of overcoming operational challenges and constraints such as temperature fluctuations, equipment costs, and regulatory compliance. It also acknowledges the impact of operational nuances like maintenance and grid integration on system efficiency. As the world progresses towards renewable energy adoption and hybrid systems, this investigation lays a strong foundation for future advancements in renewable energy integration and energy management strategies. It strives to create a sustainable energy ecosystem in Cameroon and beyond, where hybrid energy systems play a pivotal role in mitigating power deficiencies and supporting sustainable development.

Environment conservation is a matter subject affecting both developing and developed countries. Long-lasting energy can be achieved by attenuating Greenhouse gas emissions. All over the world, Hybrid Renewable Energy Sources (HRES) appear as a vital element when it comes to cover the rapid growth of the energy demand. Moreover, renewable energy (RE) is an unaffordable response to the fight against unpredicted events such as the diseases, industries development, reliability of energy sources, added to the various directives related to produce sustainable electricity. Henceforth, it is crucial to optimize the various energy sources for satisfying the electrical demand. In particular, this paper aims to value the hybridization of optimization techniques to achieve a robust optimization. Photovoltaic (PV), and Battery Storage Systems (BSS) constitute the various RE sources in this work. The main goal was to simultaneously minimize the Deficit of power supply probability (DPSP) and maximize the BSS capacities. Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), and hybridization of both techniques are employed to proceed with the optimization. This study reveals the performance of hybrid optimization used for several configurations of loads. Indeed, the results show that the autonomous day of the BSS can reach 03 days, while the DPSP can decrease towards 1%. In this way, the HRES built up is more ecofriendly and autonomous. Furthermore, the proposed idea provides improved reliability and robustness of our system under various types of loads due to different climate scenario. The statistical analysis also carried on shows a good stability while doing hybridization of both techniques and a better efficiency in comparison to single techniques.

This paper is interested in the study of the dynamics and control of the permanent magnet synchronous motor with load torque (PMSMLT). PMSMLT has three fixed points where one is saddle and the two others are saddle focus. PMSMLT exhibits no oscillations, periodic characteristics, chaotic characteristics and coexistence between no oscillations and chaotic characteristics. In order to validate the results obtained numerically, an electronic implementation of PMSMLT is performed in probe simulation program with integrated circuit emphases (PSPICE) environment which reveals a concordance between the numerical simulations and the experimental verifications. The coexisting characteristics is eliminated by the linear augmentation control method.

In this work, we put forth a rapid, lightweight, and resilient chaos‐based cryptographic system (CBC‐RTCIP) designed for the encryption of real‐time color images, executed on a Nexys4 FPGA platform. In contrast to traditional methodologies that consider RGB channels independently, our novel approach leverages the inter‐channel dependencies through the implementation of dual S‐boxes, pixel‐channel concatenation, and a pseudo‐random number generator based on Chen chaotic oscillator. The system effectively accomplishes substantial confusion and diffusion while maintaining minimal hardware overhead. Empirical findings reveal a near‐optimal global Shannon entropy of 7.99943, alongside formidable resistance to differential attacks, evidenced by NPCR and UACI metrics of 99.5978% and 33.4549%, respectively. The design attains an impressive throughput of 1021.44 Mb/s while consuming a mere 115 mW at a clock frequency of 42.56 MHz, thereby affirming its appropriateness for real‐time embedded systems and Internet of Things (IoT) applications. Moreover, the system demonstrates resilience against statistical, differential, and data loss attacks, thereby substantiating its robustness and practical applicability. These outcomes position CBC‐RTCIP as an efficient and secure methodology for safeguarding visual data in critical fields such as medical imaging and intelligent surveillance.