Soft-linking of a power systems model to an energy systems model
Soft-linking of a power systems model to an energy systems model
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DOI：
10.1016/j.energy.2012.03.052
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发表时间：
2012-06-01
期刊：
影响因子：
9
通讯作者：
Gallachoir, Brian P. O.
中科院分区：
文献类型：
--
作者：
Deane, J. P.;Chiodi, Alessandro;Gallachoir, Brian P. O.
在本文中，我们提出了一种软链接方法，该方法采用专用电力系统模型的详细模拟输出，从单独的能源系统模型中深入了解和理解电力部门的发电厂组合结果。我们应用该方法并展示和讨论结果。这种软链接的动机是提供从电力系统模型强项到能源系统模型的信息传输，并使用该信息来改进和发展对能源系统模型结果的理解。这一动机部分源于这样一种观点，即一种特定的能源建模工具无法详细解决整个能源系统的所有方面，通过利用多种建模工具的优势而不是试图将它们全部纳入一个综合模型中，可以获得更大的见解和进步。该方法从能源系统模型中获取特定年份的优化发电组合，并对电力系统模型中的同一组合进行详细的高分辨率时间顺序模拟，并增加了技术细节。这里提出的结果表明，在缺乏关键技术限制的情况下，能源系统模型可能会低估灵活资源的价值，低估风电弃风并高估基本负荷电厂的使用。 (C) 2012 Elsevier Ltd. 保留所有权利。
In this paper we present a soft-linking methodology that employs detailed simulation outputs from a dedicated power systems model to gain insights and understanding of the generation electricity plant portfolio results for the electricity sector from a separate energy systems model. We apply the methodology and present and discuss the results. The motivation for this soft-linking is to provide a transfer of information from the power systems model strong points to the energy systems model and use this information to improve and develop understanding of energy systems model results. Part of this motivation is derived from a view that one specific energy modeling tool cannot address all aspects of the full energy system in great detail and greater insights and progress can be gained by drawing on the strengths of multiple modeling tools rather than trying to incorporate them all into one comprehensive model. The methodology takes an optimized generation portfolio for a specific year from an energy systems model and undertakes a detailed high resolution chronological simulation of the same portfolio in the power systems model with added degrees of technical detail. Results presented here show that in the absence of key technical constraints, an energy systems model can potentially undervalue flexible resources, underestimate wind curtailment and overestimate the use of baseload plant. (C) 2012 Elsevier Ltd. All rights reserved.