规模化储能系统电网主动支撑能力评价体系构建和评价方法支撑数据集
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为保证所提的规模化储能系统电网主动支撑能力评价指标真实准确、可信可用,在进行示范应用之前,先通过电磁暂态仿真算例进行验证。首先在CloudPSS电磁暂态仿真平台上搭建含规模化储能支撑的电力系统仿真算例,并完成时域仿真得到仿真结果;其次根据仿真算例中的设置确定规模化储能系统电网主动支撑能力评估方法的输入参数,并完成运算得到评估结果;将仿真数据和评估结果进行对比以验证所提评估方法的有效性。数据集记录了仿真算例的算例设置相关数据(发电机的容量、惯量、阻尼、一次调频下垂系数、一次调频再热时间常数等,储能的容量、控制参数等,变压器、传输线路的阻抗等,元件之间的连接关系等)、仿真算例的原始仿真数据(主要节点处的电压轨迹、频率轨迹、相角轨迹,各储能的有功功率轨迹、无功功率轨迹)、评估算法的输入参数(系统的等效惯量、等效阻尼、聚合一次调频下垂系数和时间常数各储能的频率控制策略等;系统的导纳矩阵,各储能的电压控制策略等;系统的潮流等;)和评估算法的评估结果数据(电网频率响应关键指标的改善效果(频率支撑能力)、各储能的无功控制增益与动作时间常数比值(电压支撑能力)、各储能的输出微分无源指标(暂稳支撑能力);各储能对应的附加频率轨迹(频率支撑贡献)、广义电压阻尼(电压支撑贡献)、暂态耗散能量(暂稳支撑贡献))。
To ensure the proposed evaluation indicators for the active grid support capability of large-scale energy storage systems are authentic, accurate, credible and applicable, validation is conducted via electromagnetic transient simulation cases prior to demonstration application. First, a power system simulation case with large-scale energy storage support is constructed on the CloudPSS electromagnetic transient simulation platform, and time-domain simulation is performed to obtain simulation results. Second, input parameters for the evaluation method of active grid support capability of large-scale energy storage systems are determined based on the settings in the simulation case, and calculations are completed to generate evaluation results. The simulation data and evaluation results are compared to verify the effectiveness of the proposed evaluation method. The dataset records: simulation case setup data including generator capacity, inertia, damping, primary frequency regulation droop coefficient, primary frequency regulation reheating time constant, etc.; energy storage capacity and control parameters, etc.; impedance of transformers and transmission lines, etc.; and connection relationships between components, etc.; original simulation data including voltage trajectories, frequency trajectories and phase angle trajectories at key buses, active power trajectories and reactive power trajectories of each energy storage unit; input parameters of the evaluation algorithm including equivalent inertia and equivalent damping of the power system, aggregated primary frequency regulation droop coefficient and time constant, frequency control strategies of each energy storage unit, system admittance matrix, voltage control strategies of each energy storage unit, system power flow, etc.; and evaluation result data including improvement effect of key indicators for grid frequency response (frequency support capability), ratio of reactive power control gain to action time constant of each energy storage unit (voltage support capability), output differential passive index of each energy storage unit (transient stability support capability), additional frequency trajectories corresponding to each energy storage unit (frequency support contribution), generalized voltage damping (voltage support contribution), and transient dissipated energy (transient stability support contribution).




