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Computationally Efficient Market Simulation Tool for Future Grid Scenario Analysis

机译:计算效率高的市场仿真工具,用于未来电网情景分析

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This 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. To allow for a subsequent stability assessment, the MST requires an explicit representation of the number of online generation units, which affects power system inertia and reactive power support capability. These requirements render a full-fledged UC model computationally intractable, so we propose unit clustering, a rolling horizon approach, and constraint clipping 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 are verified by a comparison to a more expressive and computationally intensive binary UC, which confirm the validity of the approach for long term future grid studies.
机译:本文提出了一种适用于未来电网情景分析的计算有效的电力市场仿真工具(MST)。市场模型基于单位承诺(UC)问题,并考虑了对新兴技术的采用,例如需求响应,电池存储,集中式太阳能热发电和HVDC传输。为了进行后续的稳定性评估,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支持能力。这些要求使成熟的UC模型在计算上难以处理,因此我们提出了单元聚类,滚动水平方法和约束裁剪以提高计算效率。为了展示所建议工具的功能,我们使用了澳大利亚国家电力市场的简化模型,其中具有不同的可再生能源渗透率。通过与更具表现力和计算强度大的二进制UC进行比较来验证结果,这证实了该方法对长期未来网格研究的有效性。

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