Multistage fuzzy‐robust transmission network expansion planning under uncertainties. (18th June 2019)

• Record Type: Journal Article
• Authors: Zhang, Libo; Zhou, Qinyong; Gao, Qian; Cheng, Haozhong; Zhang, Shenxi
• Is Part Of: International transactions on electrical energy systems. Volume 29:Number 7(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-06-18
• Subjects: fuzzy uncertainty model -- interval uncertainty model -- multistage planning -- predicted load -- renewable power -- transmission network expansion planning; Electric power -- Periodicals; Electric power systems -- Periodicals; Electrical engineering -- Periodicals; 621.3
• DOI: 10.1002/2050-7038.12054
• Languages: English
• ISSNs: 2050-7038

Abstract

Summary: High penetration of volatile renewable energy produces uncertainties in power system and poses severe challenges to transmission network expansion planning (TNEP). Usually, only one type of mathematical model of different uncertainties was considered in every single TNEP method. However, in the process of TNEP, different uncertainties may show different mathematical features and need to be represented by various types of mathematical models. Moreover, transmission network is expanded in stages. The dynamic characteristic should be considered. Aiming at these issues, a multistage fuzzy‐robust TNEP model taking into account interval model of renewable power and fuzzy model of predicted load is proposed based on the expanded fuzzy chance constrained programming. In accordance with the feature of the established planning model, the model is transferred to a multistage robust TNEP model considering interval uncertainty model of renewable power and predicted load. Thus, the calculation burden for solving the planning model decreases. A hybrid solving strategy is developed to solve the model, in which the particle swarm optimization (PSO) algorithm is to determine number of new lines in each corridor and the improved branch‐and‐bound (IBB) algorithm is used to check the security of the planning schemes. The analyses on the modified IEEE RTS 24‐bus system and a 231‐bus system verify the effectiveness and adaptability of the proposed method.