Wind Farm Level Coordination for Optimal Inertial Control With a Second-Order Cone Predictive Model
Gang Zhang, Feng Zhang, Lei Ding, Ke Meng, Zhao Yang Dong
Abstract
Multiple wind farms (WFs) should be spatially and temporally coordinated during inertial control to avoid the under- or over-power supply. For this purpose, we propose a second-order cone predictive model to exploit the optimal inertial control scheme (ICS) of multiple WFs for under-frequency and over-frequency events. Specifically, we firstly build the nonlinear predictive model including the predictive models of synchronous generators and wind turbines (WTs), power flow model and the stable operating constraints. In this nonlinear model, multiple WFs can be properly coordinated to achieve the optimal ICS. Then, the approximation methods are proposed to recast the above nonlinear model as a second-order cone programming (SOCP), and a sequential SOCP algorithm (SSA) is presented for the optimal solution. The SOCP model is offline executed to generate the optimal power references of WFs, and power references are further fitted with 5-parameter piecewise curves to reduce the communication burden. Lastly, the fitted curves can be distributed to WF controllers to be online tracked after detecting the disturbance. Numerical tests are conducted based on the 5 WFs integrated IEEE 39-bus system to validate the effectiveness and superiority of the proposed method.