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access icon free Optimisation of time window size for wind power ramps prediction

© The Institution of Engineering and Technology
Received 04/05/2016, Accepted 15/08/2016, Revised 26/07/2016, Published 18/08/2016

A new long-term wind power prediction approach based on time windows is proposed to improve the accuracy and efficiency of wind power ramp prediction. An optimisation model is built to select the optimal time window size which is the key point of the wind power forecasting. First, a swinging door algorithm is applied to identify historical ramp events, and historical data is divided into several sections by assumed time window size. Then, windows are classified into ramp windows and non-ramp windows, and the non-ramp data of ramp windows is required to be minimal. The variables, parameters, and constraints of the model are investigated in the study, and a kind of genetic algorithm is utilised to achieve the optimal solution. The model presented in this study is validated by the study case of actual wind farms, and evaluation and discussion demonstrate the validity of the proposed approach.

Inspec keywords: load forecasting; genetic algorithms; wind power plants

Other keywords: historical data; wind power forecasting; wind farms; wind power ramps prediction; nonramp data; time window size optimisation; swinging door algorithm; historical ramp events; genetic algorithm; long-term wind power prediction; nonramp windows

Subjects: Wind power plants; Optimisation techniques; Power system planning and layout

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