Neural Output Regulation for a Solar Power Plant
نویسنده
چکیده
In this paper the modelling capabilities of a recurrent neural network and the effectiveness and stability of the output regulation control theory are combined. The control structure consists in a neural based indirect adaptive control scheme, being the main goal to provide a viable practical control strategy suitable for real-time implementations. This control scheme was applied to the distributed solar collector field at Plataforma Solar de Almería, Spain. Experimental results obtained at the solar power plant are presented showing the effectiveness of the proposed approach.
منابع مشابه
Computational fluid dynamics analysis and geometric optimization of solar chimney power plants by using of genetic algorithm
In this paper, a multi-objective optimization method is implemented by using of genetic algorithm techniques in order to determine optimum configuration of solar chimney power plant. The objective function which is simultaneously considered in the analysis is output power of the plant. Output power of the system is maximized. Design parameters of the considered plant include collector radius (R...
متن کاملPerformance Enhancement and Environmental Impact Analysis of a Solar Chimney Power Plant: Twenty-four-hour Simulation in Climate Condition of Isfahan Province, Iran
The aims of this study are to enhance the performance of a solar chimney power plant (SCPP), investigate utilization of thermal energy storage (TES) and analyze the environmental impact of the SCPP in providence of Isfahan, Iran. To achieve these goals, multi-stage numerical simulations during twenty-four hours of a day are performed in climate condition of Isfahan province (central region of I...
متن کاملInterval-based Solar PV Power Forecasting Using MLP-NSGAII in Niroo Research Institute of Iran
This research aims to predict PV output power by using different neuro-evolutionary methods. The proposed approach was evaluated by a data set, which was collected at 5-minute intervals in the photovoltaic laboratory of Niroo Research Institute of Iran (Tehran). The data has been divided into three intervals based on the amount of solar irradiation, and different neural networks were used for p...
متن کاملEvaluation of solar-chimney power plants with multiple-angle collectors
Solar chimney power plants are plants based on solar thermal power including three parts of collector, chimney and turbine, which is able to produce electrical energy. One of the effective parameters in increasing the power production is the collector angles versus horizon. In the present study, a numerical analysis of a solar chimney power plant for different angles of the collector (divergent...
متن کاملB Jency Paulin and E Praynlin: Solar Photovoltaic Output Power Forecasting Using Back Propagation Neural Network
Solar Energy is an important renewable and unlimited source of energy. Solar photovoltaic power forecasting, is an estimation of the expected power production, that help the grid operators to better manage the electric balance between power demand and supply. Neural network is a computational model that can predict new outcomes from past trends. The artificial neural network is used for photovo...
متن کامل