A block coordinate descent-based parallel decomposition-coordination algorithm for reactive power optimization

In allusion to inseparability of augmented Lagrangian function during the solution of decomposition-coordination mode for reactive power optimization model, a parallel decomposition-coordination algorithm based on the thought of block coordinate descent (BCD) is proposed. The proposed algorithm can implement decomposition and coordination of reactive power optimization of the whole grid, in which only power and voltage information of boundary nodes between adjacent sub-areas is needed to be exchanged for the coordination, thus both defects of slow computing speed and bottleneck of data transmission existing in centralized reactive power optimization of large-scale power grid are remedied. Besides, each sub-area needs not internal model and data of other sub-areas, thus each control center can choose optimization algorithm independently and the combination of autonomous decentralization with coordinated control. Simulation results of IEEE 118-bus system and IEEE 300-bus system show that the proposed algorithm can speed up the computation of reactive power optimization of the whole power grid obviously, and comparing with the decomposition-coordination algorithm based on auxiliary problem principle (APP) the convergence rate of the proposed algorithm is faster and its computational efficiency is higher.