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A column generation approach for solving generation expansion planning problems with high renewable energy penetration

机译：一种解决可再生能源渗透率高的发电扩展计划问题的圆柱发电方法

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The high penetration of renewables envisaged for future power systems will significantly increase the need for flexible operational measures and generation technologies, whose associated investment decisions must be properly planned in the long term. To achieve this, expansion models will need to incorporate unit commitment constraints, which can result in large scale MILP problems that require significant computational resources to be solved. In this context, this paper proposes a novel Dantzig-Wolfe decomposition and a column generation approach to reduce the computational burden and overcome intractability. We demonstrate through multiple case studies that the proposed approach outperforms direct application of commercial solvers, significantly reducing both computational times and memory usage. Using the Chilean power system as a reference case, we also confirm and highlight the importance of considering unit commitment constraints in generation expansion models. (C) 2016 Elsevier B.V. All rights reserved.
机译：未来电力系统中可再生能源的高渗透率将大大增加对灵活的操作措施和发电技术的需求，而这些技术和发电技术的长期投资决策必须得到适当规划。为此，扩展模型将需要合并单位承诺约束，这可能导致大规模的MILP问题，需要解决大量的计算资源。在这种情况下，本文提出了一种新颖的Dantzig-Wolfe分解和列生成方法，以减轻计算负担并克服难处理性。通过多个案例研究，我们证明了所提出的方法优于直接应用商业求解器，从而显着减少了计算时间和内存使用量。以智利的电力系统为参考案例，我们还确认并强调了在发电扩展模型中考虑机组承诺约束的重要性。 （C）2016 Elsevier B.V.保留所有权利。

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