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Inicio  /  Applied Sciences  /  Vol: 9 Par: 5 (2019)  /  Artículo
ARTÍCULO
TITULO

Multi-Objective Interval Prediction of Load Based on the Conditional Copula Function

Gang Zhang    
Zhixuan Li    
Jinwang Hou    
Kaoshe Zhang    
Fuchao Liu and Xin Zhang    

Resumen

As the load characteristics of power systems tend to be complex, the difficulty of accurate and reliable load point prediction is constantly increasing, and it is more and more difficult to only use the point prediction results to ensure the safe and stable operation of the power system. By using the multi-objective interval prediction algorithm based on the conditional copula function, the power system decision-makers can better understand the fluctuation range of future load changes, so that they can clearly recognize the possible uncertainties and facing risk factors when they are performing tasks such as real-time scheduling and system security analysis of the future load, and then make more reasonable, safe, and economical scheduling decisions in a timely manner, and more in line with the future development needs of the power market.

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