Abstract
In this paper, we proposed a method to assess the impact of the uncertainty of forecast error of wind and photovoltaic generation on power transmission. First, we proposed a probabilistic model to characterize the uncertainty of the forecast error and established an index system to assess the performance of the transmission system in various aspects. Second, we adopted the Latin hypercube sampling technique to obtain the expectation and the variance of the assessment indices. Third, we introduced a sensitivity method to measure the variation of the probabilistic characteristics of the assessment indices propagated from the variation of the forecast error. Finally, we used a stochastic multi-attribute decision-making method to make the ranking of all renewable power plants by the comprehensive influence of the uncertainty of forecast error on them. With this ranking, it is able to judge which renewable power plant’s forecast accuracy should be improved in order to most effectively control the error of the power transmission. The effectiveness of the proposed models and methods are briefly verified by a case.
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