Atmospheric Turbidity Forecasting using Side-by-side ANFIS

Abstract : In a context of sustainable development, enthusiasm for CSP technologies is developing. To achieve a better competitiveness of the CSP plants, the CSPIMP (Concentrated Solar Power efficiency IMProvement) project has been recently initiated. The main target is to develop a new procedure to improve steam turbine start up cycles, maintenance activities and advanced plant control schemes. One challenge of the project is to better forecast the solar resource in order to better manage the CSP plant. An important parameter to estimate or predict the solar radiation is the atmospheric turbidity. Indeed, the direct normal irradiance (DNI) under clear sky can be expressed as a function of extraterrestrial irradiation, a coefficient depending on the altitude of the site and on the atmospheric turbidity. This paper focuses then on forecasting this atmospheric turbidity at different time horizons (until 3 hours). The proposed forecast method consists of an adaptive network-based fuzzy inference system based on data selected from the NREL laboratory by using discrete wavelet transform. From the ANFIS model developed and its different blocs, future values of atmospheric turbidity are then obtained. The best configuration for the tools used leads to satisfactory forecasting results and validates the proposed ANFIS methodology.
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Article dans une revue
Energy Procedia, Elsevier, 2014, Proceedings of the SolarPACES 2013 International Conference, 49, pp.2387-2397. 〈〉. 〈10.1016/j.egypro.2014.03.253〉
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Julien Nou, Rémi Chauvin, Adama Traoré, Stéphane Thil, Stéphane Grieu. Atmospheric Turbidity Forecasting using Side-by-side ANFIS. Energy Procedia, Elsevier, 2014, Proceedings of the SolarPACES 2013 International Conference, 49, pp.2387-2397. 〈〉. 〈10.1016/j.egypro.2014.03.253〉. 〈hal-01273334〉



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