Abstract
A hybrid ship power system with fuel cell and storage system batteries/supercapacitors can be developed by adding renewable energy sources. Adding PV to the hybrid system enhances the system's reliability and dependability. However, a high-level control strategy is needed to manage the generated power between the fuel cell and the photovoltaic array and determine the suitable time to charge or discharge the stored energy according to the load demand. The perfect solution is using an intelligent neural network technique to control the ship's hybrid power system because of the system's nonlinearity and the existence of pulsing and high-density load demand. This paper introduces an intelligent artificial neural network (ANN) technique that depends on previous experience. ANN is flexible and easy to modify, adding/removing power system components, and be scaled to any ship power system rating. Simulation results using MATLAB software prove that the robust, intelligent power management system can control and identify which energy source will be exploited according to the daylight. Moreover, calculate the amount of generating power depending on the shipload demand. In addition to that, it ensures the system dependability considering the other source as standby while the storage system is the power source in the transient period in case of switching between the two systems and maintaining the storage system in the high state of charge possible. Furthermore, this will reduce fuel consumption during the ship's cursing mission. يعتبر نظام القدره الکهربيه المکون من خلايا هيدروجينيه ونظام تخزين للطاقه مناکثر الانظمه استخداما فى جميع المجالات. يهدفهذا البحث الى تحسين أداء هذا النظام عن طريقه إضافه مجموعه خلايا شمسيه لزيادة اعتماديه النظام وتوفير الوقودالمستخدم وايضا الى تقليل التلوث البيئى . وجود اکثر من مصدر للطاقه الغير متجانس يتطلب وجود نظام اداره قوى لتحديد المصدر المناسب لتغذيه الاحمال وافضل الاوقات لشحن او تفريغ البطاريات. يقدم البحث نظام اداره الطاقه الذکى باستخدام تقنيه الشبکات العصبونيه والذى يتميز بالمرونه والقدره على التکيف اعتمادا على الخبرات السابقه للمستخدم وامکانيه اضافه او حذف اى مصدر او تعديل المدخلات . تم استخدام المخاکاة باستخدام الماتلاب لضمان واختبار النظام تبعا للخبرات السابقه.
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