Decision Support System (DSS) tool development for PV solar farm's short-term output power prediction

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Design and development of a DSS tool for accurate prediction of the sun irradiation and the related PV farm's output power profiles for the next 24 hours is the focus of this project.The results of this project enable Felix Technology Inc. to benefit their business as a company with weather information solutions for renewable energy suppliers and power system operators. The existing commercial software packages that are available in the market do not satisfy companies current requirements. The company requires to have its own algorithm that is compatible with its sun radiation data management system. We will develop a software package/DSS tool to process the measured solar radiation and PV farm output power and to predict the PV farm output power for the next 24 hours. Our expertise in data clustering, adaptive prediction of stochastic processes, and data mining will be used in this project. The proposed DSS tool has four main modules:1) data mining module; 2) hybrid forecasting module; 3) adaptive clustering module; 4) graphical user interface(GUI). We will use advanced mathematical modeling, data mining techniques and prediction algorithms to build the above named software modules and integrate them into a useful and practical DSS tool for the Felix Tech. Our DSS tool will benefit the Felix Tech in offering new analytical services. It will also benefit its customers (e.g. PV farms, Wind farms, and Power Utility companies) in optimal and risk free planning and operation of their renewable energy systems.