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arXiv 1701.07941math.OC
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用于未来电网情景分析的高效计算市场模拟工具

Computationally Efficient Market Simulation Tool for Future Grid Scenario Analysis

Shariq Riaz, Gregor Verbic, Archie C. Chapman

摘要:

本文提出了一种计算效率高的电力市场模拟工具(MST),适用于未来的电网情景分析。市场模型基于机组承诺(UC)问题,并考虑到新兴技术的吸收,如需求响应,电池存储,集中太阳能热发电和高压直流输电线路。为了便于后续的稳定性评估,MST需要明确表示在线发电机组的数量,这会影响电力系统的惯性和无功功率支持能力。这些要求使得一个成熟的UC模型计算上难以处理,所以我们提出了单元聚类,滚动时域方法,约束减少,以提高计算效率。为了展示所提出的工具的能力,我们使用了一个简化的模型,澳大利亚国家电力市场与不同的可再生能源发电的渗透。结果表明,从所提出的工具产生的在线单元的数量是非常接近的二进制UC运行一周的时间跨度,这是证实了负载能力和惯性分析。这证实了该方法对未来电网长期研究的有效性,在未来电网研究中,人们更感兴趣的是找到系统中的薄弱点,而不是对单个运行条件进行详细分析。

英文摘要:

The paper proposes a computationally efficient electricity market simulation tool (MST) suitable for future grid scenario analysis. The market model is based on a unit commitment (UC) problem and takes into account the uptake of emerging technologies, like demand response, battery storage, concentrated solar thermal generation, and HVDC transmission lines. To allow for a subsequent stability assessment, the MST requires an explicit representation of the number of online generation units, which affects powers system inertia and reactive power support capability. These requirements render a fullfledged UC model computationally intractable, so we propose unit clustering, rolling horizon approach, and constraint reduction to increase the computational efficiency. To showcase the capability of the proposed tool, we use a simplified model of the Australian National Electricity Market with different penetrations of renewable generation. The results show that the number of online units resulting from the proposed tool is very close to the binary UC run over a week-long horizon, which is confirmed by the loadability and inertia analysis. That confirms the validity of the approach for long term future grid studies, where one is more interested in finding weak points in the system rather than in a detailed analysis of individual operating conditions.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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