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A State Space Model for Wind Forecast Correction

Valérie Monbet, Pierre Ailliot, Anne Cuzol

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Abstract

Abstract. The accuracy of numerical weather forecasts is crucial in many engineering applications, especially for the management of renewable energy. In this paper, we give a short overview of methods used to improve local weather forecast. Then we propose a new state space model in order to correct bias and phase errors in numerical wind forecasts. We present some results for real life data.

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What this paper is about

Abstract. The accuracy of numerical weather forecasts is crucial in many engineering applications, especially for the management of renewable energy. In this paper, we give a short overview of methods used to improve local weather forecast. Then we propose a new state space model in order to correct bias and phase errors in numerical wind forecasts. We present some results for real life data.

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Available abstract

Abstract. The accuracy of numerical weather forecasts is crucial in many engineering applications, especially for the management of renewable energy. In this paper, we give a short overview of methods used to improve local weather forecast. Then we propose a new state space model in order to correct bias and phase errors in numerical wind forecasts. We present some results for real life data.

Key concepts: Renewable energy, Computer science, Wind power, Numerical weather prediction, State space, Meteorology, Space (punctuation), State-space representation

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