Application of novel nested decomposition techniques to long-term planning problems
Application of novel nested decomposition techniques to long-term planning problems
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DOI：
10.1109/pscc.2016.7540872
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发表时间：
2016-06
期刊：
影响因子：
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通讯作者：
P. Falugi;I. Konstantelos;G. Strbac
中科院分区：
文献类型：
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作者：
P. Falugi;I. Konstantelos;G. Strbac
成本效益，长期规划下的不确定性构成了一个重大的挑战，因为一个有意义的描述规划问题是由大型混合线性规划（MILP）模型，其中可能包含数千个二进制变量和数百万个连续变量。本文提出了一种新的基于嵌套Benders分解的多阶段分解方法，并将其应用于输电规划问题。突出的困难，在规划问题的背景下，由于存在非连续的投资状态方程使用时间分解方案。一个有效的和高度概括性的框架重铸的时间约束，这样的问题在一个结构适合嵌套分解方法。通过IEEE24节点测试系统的算例分析，证明了该方法的有效性和计算效益。
Cost effective, long term planning under uncertainty constitutes a significant challenge since a meaningful description of the planning problem is given by large Mixed Integer Linear Programming (MILP) models which may contain thousands of binary variables and millions of continuous variables. In this paper, a novel multistage decomposition scheme, based on Nested Benders decomposition is applied to the transmission planning problem. The difficulties in using temporal decomposition schemes in the context of planning problems due to the presence of non-sequential investment state equations are highlighted. An efficient and highly-generalizable framework for recasting the temporal constraints of such problems in a structure amenable to nested decomposition methods is presented. The proposed scheme's solution validity and substantial computational benefits are clearly demonstrated through the aid of case studies on the IEEE24-bus test system.