Wind Power Forecasting Based on Extended Latin Hypercube Sampling
نویسندگان
چکیده
With the rise of distributed generation, such as wind power and photovoltaic (PV), it is necessary to consider the effect of distributed generation’s output randomness. Using the method of Latin hypercube sampling (LHS) can effectively fit output scenario. Considering the sampling number of conventional LHS (CLHS) must be fixed in advance, LHS(ELHS) can be Extended to predict wind power. The sample scenarios were extended exponentially on the basis of original scenarios by CLHS, taking the relative error of the output variation before and after the extension as the convergence criterion of ELHS. Numerical example results show the feasibility and accuracy of the proposed algorithm. Keywords-distributed generation; wind power forecast; Latin hypercube sampling
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