https://gphjournal.org/index.php/eee <p style="font-family: 'Segoe UI', sans-serif; font-size: 16px; color: #333;"><strong>GPH - International Journal of Electrical And Electronics Engineering</strong> is a peer-reviewed, open-access journal dedicated to advancing research in the field of electrical and electronics engineering. The journal publishes original research articles, comprehensive reviews, and technical papers on topics such as circuit design, signal processing, power systems, telecommunications, embedded systems, microelectronics, control systems, and emerging technologies. By providing a global platform for researchers, practitioners, and industry experts, it fosters interdisciplinary collaboration and drives innovation in the rapidly evolving landscape of electrical and electronics engineering.</p> Global Publication House en-US GPH-International Journal of Electrical And Electronics Engineering <p>Author(s) and co-author(s)&nbsp;jointly&nbsp;and severally represent and warrant that the Article is original with the author(s) and does not infringe any&nbsp;copyright or violate any other right of any third parties, and that the Article has not been published&nbsp;elsewhere.&nbsp;Author(s) agree to the terms that the <strong>GPH Journal</strong> will have the full right to remove the published article on any misconduct found in the published article.</p> https://gphjournal.org/index.php/eee/article/view/2466 <p>The global renewable energy transition is advancing steadily. Traditional land-based renewable energy facilities are constrained by land space limits, and cannot meet the long-term demand for large-scale clean energy development. For the development of deep-water sea areas with water depths of 50 to 200 meters, there is an urgent need for implementable innovative technical solutions. This study proposes a deep-water floating offshore hybrid energy platform that integrates wind turbines and photovoltaic systems, which is positioned for gigawatt (GW)-level large-scale deployment. Its full-chain design verification is completed using a self-developed new hybrid artificial intelligence optimization framework, and all research data and conclusions are original outputs of this study. The platform is equipped with 15–20 MW floating wind turbines, high-efficiency bifacial photovoltaic arrays, and a dynamic positioning platform. Its AI framework includes three core categories of algorithms: machine learning to support real-time weather forecasting, deep reinforcement learning to achieve autonomous platform positioning, and a genetic algorithm to optimize the layout of multi-platform farms. Development work centers on four core goals: maximizing overall energy output, minimizing the levelized cost of energy (LCOE), reducing environmental impacts, and improving grid stability. This study uses a hybrid neural network to generate 72-hour forecasts of weather and sea conditions, with an accuracy rate of 95%. It also adopts a swarm intelligence algorithm to support coordinated operation of multiple platforms, and digital twin technology to achieve full-lifecycle real-time monitoring and predictive maintenance. Four core constraints are integrated into the optimization process: wave impact, seawater corrosion, wake interference between platforms, and marine ecological protection agreements. Simulation verification confirms that the energy output of this platform’s hybrid configuration is 32% higher than that of traditional offshore wind farms, and its capacity factor is 28% higher than that of standalone floating photovoltaic devices. The AI optimization reduces the LCOE by 18%, the overall system availability reaches 98.5%, the intelligent positioning system cuts the platform’s fatigue load by 25% and extends the service life of core components. The optimized platform spacing and bionic design create extremely low interference with marine ecosystems, modular deployment supports phased implementation of GW-scale projects, and the platform’s grid integration capacity can support a regional renewable energy penetration rate of over 80%. This study verifies the technical feasibility of deploying this type of platform in deep waters, provides a scalable framework for global offshore renewable energy development, and supports international decarbonization targets. Future research will focus on pilot verification and economic feasibility analysis for commercial deployment.</p> Adel Elgammal ##submission.copyrightStatement## https://creativecommons.org/licenses/by-nc-nd/4.0 2026-06-14 2026-06-14 4 1 01 27 10.5281/zenodo.20688797