A model of a hybrid power plant consisting of Compressed Air Exergy Storage (CAES) coupled with a wind farm is presented. The model employs neural network-based wind speed forecasting. By coupling CAES with a wind farm, some of the major limitations of wind power, such as a low power density and an unpredictable nature, can be overcome. The use of time-series neural network-based prediction models aims at reducing the stochastic uncertainty of wind power. As shown in the paper, knowledge of the future incoming energy can be a powerful means for planning the daily operation strategy of the storage system. A detailed economic analysis has been carried out, evaluating investment, maintenance and operational costs using actual energy market prices. The benefits critically depend on the performance of each subsystem, incoming energy, user load and economic regulations. Results show that advantages in terms of Net Present Value, energy savings and CO2 mitigation can be achieved.

Energy and Economic Evaluation of A Hybrid CAES/Wind Power Plant with Neural Network-Based Wind Speed Forecasting

ARSIE, Ivan;MARANO, VINCENZO;RIZZO, Gianfranco;
2006-01-01

Abstract

A model of a hybrid power plant consisting of Compressed Air Exergy Storage (CAES) coupled with a wind farm is presented. The model employs neural network-based wind speed forecasting. By coupling CAES with a wind farm, some of the major limitations of wind power, such as a low power density and an unpredictable nature, can be overcome. The use of time-series neural network-based prediction models aims at reducing the stochastic uncertainty of wind power. As shown in the paper, knowledge of the future incoming energy can be a powerful means for planning the daily operation strategy of the storage system. A detailed economic analysis has been carried out, evaluating investment, maintenance and operational costs using actual energy market prices. The benefits critically depend on the performance of each subsystem, incoming energy, user load and economic regulations. Results show that advantages in terms of Net Present Value, energy savings and CO2 mitigation can be achieved.
2006
9608758416
9608758424
9789608758414
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/3881727
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