基于非对称模型的变电所数据融合误差优化研究

牵引变电所作为电力系统中实现变换电能的场所,给电力机车提供稳定可靠的电能。由于机车具有非线性运载特点,在吸收电网电流的同时也在输入谐波电流,引起电网干扰波动和噪声误差、电压畸变等现象,对供电系统安全构成威胁。本文通过建立变电所三相匹配与失配模型,利用自适应数据融合算法仿真检测控制误差的效果和优化误差的最佳方案,合理控制参数的状态和优化参数的规律。结果表明数据融合可以解决局部电网误差波动电流超标和电压畸变,在保障供电质量和电网安全方面效果显著。

Research on Data Fusion Error Optimization of Substation Based on Asymmetric Model

Traction substation as a place of power conversion in power system, to provide stable and reliable electric energy for electric locomotive. Because the locomotive has the characteristics of nonlinear transportation, at the same time, the input current is absorbed, the disturbance of power grid, noise and voltage distortion, pose a threat to power system security. In this paper, the model of three-phase matching and mismatch is established; an adaptive data fusion algorithm is used to simulate the effect of detection error and the optimal solution, the state of control parameters and the rules of optimal parameters. The results show that the data fusion can solve the problem of local grid error fluctuation and voltage distortion, in ensuring the quality of power supply and power grid security significantly.