A measurement-based estimation method of injection shift factors

Injection shift factors (ISFs) are often used in real-time scheduling, security check and congestion management. A normally operating high-voltage transmission network could approximately satisfy the linearization conditions so the ISFs remain constant. The existing ISFs calculation method is the DC approximations based on the branch reactance matrix. But this method has inherent drawbacks resulting in its inaccuracy in two aspects: (1) the parameters of power system elements are hard to acquire accurately because of parameter offset as operation states change; (2) we need to set a reference node to balance the power flow, but the setting is often inconsistent with the real balance strategy. In the above context, we propose a measurement-based estimation method which uses robust least-squares estimation and SCADA measurement data to calculate the ISFs. The effectiveness of the method is verified by comparing the ISFs got from the measurement-based robust estimation with the ones got from DC approximations and the ordinary least-squares estimation (LSE).