A Transmission System Planning Method Considering Fuzzy Model of Load and Interval Model of Renewable Power

2018 International Conference on Power System Technology (POWERCON) Pub Date : 2018-11-01 DOI:10.1109/POWERCON.2018.8602143

Libo Zhang, Qinyong Zhou, Taishan Yan, Haozhong Cheng, Shenxi Zhang

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Abstract

High penetration of volatile renewable energy produces uncertainties in power system and poses severe challenges to transmission network planning (TNP). Usually, only one type of mathematical model of different uncertainties was considered in every single TNP method. However, in the process of TNP, different uncertainties may show different mathematical features and need to be represented by various types of mathematical models. Aiming at this problem, a TNP model taking into account interval uncertainty model of renewable energy generation and fuzzy uncertainty model of predicted load is proposed based on the expanded fuzzy chance constrained programming. In accordance with the features of the constructed planning model, the model is transferred to a robust TNP model considering interval uncertainty model of renewable energy generation and predicted load. Thus, the calculation burden for solving the planning model decreases. The analyses on the modified IEEE RTS 24-bus system and a 231-bus system verify the effectiveness and adaptability.

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考虑负荷模糊模型和可再生电力区间模型的输电系统规划方法

易失性可再生能源的高渗透给电力系统带来了不确定性，对输电网规划提出了严峻的挑战。通常，每一种TNP方法只考虑一种不同不确定性的数学模型。然而，在TNP过程中，不同的不确定性可能表现出不同的数学特征，需要用不同类型的数学模型来表示。针对这一问题，基于扩展模糊机会约束规划，提出了考虑可再生能源发电区间不确定性模型和预测负荷模糊不确定性模型的TNP模型。根据所构建的规划模型的特点，将其转化为考虑可再生能源发电和预测负荷区间不确定性的鲁棒TNP模型。从而减少了求解规划模型的计算负担。通过对改进后的IEEE RTS 24总线系统和231总线系统的分析，验证了该方法的有效性和适应性。

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2018 International Conference on Power System Technology (POWERCON)

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