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Optimized Control Strategy for Power Management in Hybrid Systems

المؤلف الرئيسي: Elaal, Ali Hameed (Author)
مؤلفين آخرين: Almosawy, Sadiq Muhsin Ihmood (Advisor)
التاريخ الميلادي: 2018
موقع: الناصرية
الصفحات: 1 - 103
رقم MD: 1008185
نوع المحتوى: رسائل جامعية
اللغة: الإنجليزية
الدرجة العلمية: رسالة ماجستير
الجامعة: جامعة ذي قار
الكلية: كلية الهندسة
الدولة: العراق
قواعد المعلومات: Dissertations
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المستخلص: This thesis study a hybrid control system includes the use of renewable energy sources (solar and wind) and use artificial intelligence. The world is witnessing significant rise in fossil fuel prices since the end of the last century until now, where this increase in prices and the decrease in inventory day by day. Therefore, turned the attention of researchers in the field of power generation to expand a non-conventional energy sources (new and renewable energy sources). It is inexhaustible energy in use because they depend on renewable natural resources. This study included a detailed explanation about the photovoltaic and wind turbine systems. The mathematical model is an important part of the detailed study for wind turbine and photovoltaic systems. As well as study models for photovoltaic system (PV) and wind turbine through the MATLAB/Simulink for simulation and analysis. Photovoltaic system needs to apply the maximum power point tracking (MPPT) algorithm due to the instability of external circumstances such as solar radiation and temperature. Perturb and observe (P&O) maximum power point (MPP) algorithm is used for a comparison with the proposed neural network technique. From the simulation results based on the mathematical model of the system, the comparison of proposed MPPT with the classical P&O reveals the robustness of the proposed PV control system for solar irradiance and temperature changes. Therefore, a neural network technology applied to train solar cell data is intended to perform the optimization process and get the MPP value of power. This thesis presents a control strategy for power management in on- grid photovoltaic and wind hybrid power system based on artificial intelligence techniques. The fuzzy logic controller (FLC) power management strategy is developed to manage the power flow to the system. results also show that the proposed FLC power management and control strategy for the hybrid system gives a greater reliability in terms of power generation and distribution compared to a stand- alone system with single source. The entire system is analyzed through simulation in MATLAB/Simulink. The power distribution between the sources photovoltaic cells, wind turbine and sum of them are (2.2%, 2.9%, and 75%) respectively, the remaining 19.6% of the power is supplied through the grid. This results depend on particular conditions (wind speed, temperature and radiation) as an inputs to the model for hybrid system for one city. Where this conditions System Advisor Model National Renewable Energy Laboratory (NREL)taken from the (Jan. 2014).