新能源与灵活调节煤电与电力系统安全稳定域数据集
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本数据集为电力系统安全稳定分析模块的输出成果，以山东-甘肃送受端系统2030年规划网架为基础搭建。本数据集为安全稳定域分析的结果集，其潮流与稳定计算相关的BPA基础数据来源于中国电力科学研究院。 山东作为受端，负荷密集、需求旺盛；甘肃作为送端，新能源资源丰富、发电能力充裕。两区域通过直流通道实现互联，这一格局高度契合我国大规模跨区输电的典型特征，是进行安全稳定域分析的理想对象。本数据集的安全稳定域约束为运行模拟与协同规划模块提供反映规划方案安全稳定要求的量化约束，从而实现规划过程中的安全稳定约束前置。 本数据集的生成采用的核心方法是基于配点法的多项式逼近。首先，在由规划参数（如各区域煤机、风电、光伏开机容量）构成的参数空间中，选取配点；针对每个配点所对应的具体规划方案，基于BPA平台执行时域仿真，以获取其暂态电压与频率稳定指标。随后，利用各配点的仿真结果，采用基于配点法的多项式逼近方法，拟合出规划参数与各稳定指标之间的显式函数关系。最终，通过令指标多项式等于指标临界值，得出可解析表达的安全稳定域的边界。 本数据集主要内容包括：基态数据与仿真设置数据，明确了开展稳定域分析的基态条件，包含基态下的潮流与暂态数据文件、基态潮流信息、以及故障设置与观测点配置；规划参数定义数据，包含山东、甘肃系统各6个规划参数的能源类型、其在参数空间中的上下边界等；配点仿真样本数据，包含山东、甘肃两个区域系统分别基于61个配点的时域仿真结果曲线，以及各观测点的暂态电压/频率响应曲线及安全稳定指标；指标多项式及稳定域多项式数据，针对山东、甘肃系统的不同观测点，提供了包含21个项的显式多项式，定量刻画了各电源参数与稳定指标之间的函数关系，并通过将指标临界值代入指标多项式，推导出可解析表达的稳定域多项式；误差分析数据，提供了误差分析结果，包括指标多项式与稳定域多项式的逼近误差，验证了方法的可靠性；结果分析数据，包含综合性分析报告和可视化图集。
This dataset is the output result of the power system security and stability analysis module, which is built based on the 2030 planning grid of the Shandong-Gansu sending-end and receiving-end power system. This dataset is a result set for security and stability region analysis. The basic BPA data related to power flow and stability calculations is sourced from China Electric Power Research Institute. Shandong serves as the receiving end, with intensive load and strong power demand; Gansu acts as the sending end, rich in new energy resources and sufficient power generation capacity. The two regions are interconnected via DC transmission channels, a pattern that highly aligns with the typical characteristics of large-scale cross-regional power transmission in China, making it an ideal subject for security and stability region analysis. The security and stability region constraints of this dataset provide quantitative constraints reflecting the security and stability requirements of planning schemes for the operation simulation and collaborative planning modules, thereby realizing the pre-positioning of security and stability constraints in the planning process. The core method adopted for generating this dataset is polynomial approximation based on the collocation method. First, collocation points are selected in the parameter space composed of planning parameters (such as the installed capacities of coal-fired, wind power, and photovoltaic generating units in each region). For the specific planning scheme corresponding to each collocation point, time-domain simulation is performed based on the BPA platform to obtain its transient voltage and frequency stability indices. Subsequently, using the simulation results of each collocation point, the polynomial approximation method based on the collocation method is employed to fit the explicit functional relationship between the planning parameters and each stability index. Finally, by setting the index polynomial equal to the critical value of the index, the analytically expressible boundary of the security and stability region is derived. The main contents of this dataset include: 1. Base case data and simulation setup data, which clarify the base case conditions for conducting stability region analysis, including power flow and transient data files under the base case, base case power flow information, as well as fault settings and observation point configurations; 2. Planning parameter definition data, which include the energy types of the 6 planning parameters for the Shandong and Gansu systems respectively, their upper and lower bounds in the parameter space, etc.; 3. Collocation point simulation sample data, which include the time-domain simulation result curves of the Shandong and Gansu regional systems based on 61 collocation points respectively, as well as the transient voltage/frequency response curves and security and stability indices of each observation point; 4. Index polynomial and stability region polynomial data, which provide explicit polynomials with 21 terms for different observation points of the Shandong and Gansu systems, quantitatively characterizing the functional relationship between each power supply parameter and the stability index, and derive the analytically expressible stability region polynomials by substituting the critical index values into the index polynomials; 5. Error analysis data, which provide error analysis results, including the approximation errors of the index polynomials and the stability region polynomials, verifying the reliability of the method; 6. Result analysis data, which include comprehensive analysis reports and visual atlases.
