Study on Uncertainty of Load Model Parameters based on Cloud Theory

Wenping Hu, Weinan Wu, Jun Yang, Tengkai Yu, Pei Liu, and Zhili Zeng

Keywords

load model parameters, uncertainty, cloud theory, degree of membership, expected value

Abstract

The load model has an important influence on power system stability, while power load's characteristics such as diversity, complexity and time-varying would lead to uncertainty of load model parameters. The paper mainly considers the influence of temperature on parameters of the comprehensive load model as temperature is the main factor that leads to load model's uncertainty. Considering the uncertainty of load model parameters, a method to calculate the expected value of load model parameters based on Cloud Theory is proposed. Using the proposed method, the paper calculates the load model parameters of a specific city grid and calculation results show the feasibility and validity of the proposed method.

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