Decentralized dynamic system for optimal power dispatch in wind farms based on node-dependence nature

Meeting the power demand from the transmission system operator is an important objective for power dispatch, which introduces a power supply-demand equality constraint coupling all the wind turbines among the wind farm into the optimization problem. For a large-scale wind farm, processing the global equality constraint in a centralized or distributed framework is time-consuming and computationally complex. Here we considered the fast and localized execution issue of the power optimal dispatch problems. A completely decentralized dynamic system was designed to optimize power flow while satisfying the electricity supply constraints. A voltage optimization problem with the global power constraints was decoupled into local wind turbine controllers based on the node-dependence nature, which is an inherent characteristic of wind farms and was fitted to the power sensitivity matrix in this paper. The local optimization problem was solved iteratively using the gradient projection method, and the system converged linearly to the equilibrium point. The simulations for the case studies performed in Simulink demonstrate that the proposed method achieves a near-global optimal performance using only local measurements. Sheng Huang, Xiaohui Huang and colleagues propose a methodology for the optimal power dispatch from the wind farms. Their method relies on local data only and allows iterative convergence.