A Branch-and-Cut Benders Decomposition Algorithm for Transmission Expansion Planning

作者：Huang, Shengjun^*; Dinavahi, Venkata

来源：IEEE Systems Journal, 2019, 13(1): 659-669.

DOI：10.1109/JSYST.2017.2775610

• Benders decomposition (BD)
• branch-and-cut (B&C) algorithm
• mixed-integer linear programming (MILP)
• parallel processing
• security constrained transmission expansion planning (SCTEP)

The emergence of a great number of regional planning projects worldwide has considerably increased the complexity and relevance of transmission expansion planning, prompting intensive research and investigation on the formulation and solution. In this paper, the security constrained transmission expansion planning problem is addressed by a branch-and-cut Benders decomposition (BCBD) algorithm. It is a deterministic method where the global optimal solution can be guaranteed in a finite number of iterations. Based on this implementation framework, four acceleration strategies have been employed to enhance the performance. For the validation of accuracy and efficiency, the commercial solver Cplex running on the same platform is introduced for comparison, where four types of mixed-integer linear programming algorithms are discriminated by specifying two pairs of key settings, including dynamic searching and parallel implementation. The superiority of BCBD over Cplex has been validated by case studies, where five benchmark systems ranging from 6 to 300 buses are employed. In addition, performance analysis between BCBD and classical Benders decomposition has also been carried out to distinguish the contribution of branch-and-cut framework and acceleration strategies.

• 出版日期2019-3
• 单位中国人民解放军国防科学技术大学