Titlebook: Assessment and Simulation Tools for Sustainable Energy Systems; Theory and Applicati Fausto Cavallaro Book 2013 Springer-Verlag London 2013

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Artificial Neural Networks and Genetic Algorithms for the Modeling, Simulation, and Performance Predresenting a number of problems in different solar energy systems applications, which include modeling and simulation of solar systems, prediction of the performance, and optimization of the design or operation of the systems. The systems presented include solar thermal and photovoltaic systems.

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Combining Mathematical Programming and Monte Carlo Simulation to Deal with Uncertainty in Energy Pro repeated many times (1,000) in order to have an adequate sample for drawing robust conclusions. Relationships between the values of these parameters (i.e., interdependent parameters) can also be incorporated in the Monte Carlo process. The specific work is focused on the energy project portfolio se

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1865-3529 s of theoretical foundations and applications of multi-criteria decision making. This is followed by chapters concentrating on the theory and practice of fuzzy inference, neural nets and algorithms genetics. Fi978-1-4471-5796-0978-1-4471-5143-2Series ISSN 1865-3529 Series E-ISSN 1865-3537

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Bilateral Aid to China Since 1979, a (PV) photovoltaic module. ModelSim-based simulation results confirm the effectiveness of the designed approach in tracking the MPP. In addition, it has been demonstrated that the employed FPGA chip is largely sufficient to implement the designed approach.

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Design and Implementation of Maximum Power Point Tracking Algorithm Using Fuzzy Logic and Genetic Al a (PV) photovoltaic module. ModelSim-based simulation results confirm the effectiveness of the designed approach in tracking the MPP. In addition, it has been demonstrated that the employed FPGA chip is largely sufficient to implement the designed approach.

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