Multi-objective Optimization of Unit Restoration During Network Reconstruction Based on DE-EDA

The restoration of unit is the basis of the whole power system restoration. The start-up sequence of units has an influence on both the target network reconstruction whose goal nodes are units which are selected to supply with cranking power and the total power generation capability over a restoration period during network reconstruction. This paper provides a multi-objective optimization model of unit restoration of which optimization goals are to minimize the restoration cost of the target network and to maximize the total power generation capability. The weight of lines is dynamically set to extent the search space for avoiding the loss of the optimal solution when the target network is reconstructed. The model is solved by differential evolution and estimation of distribution algorithm (DE-EDA). Simulation results on IEEE 30-bus system show that the proposed optimization model and algorithm are able to find the solutions which have better convergence and are better spread; the effectiveness of the proposed optimization model and algorithm is further validated by the simulation result on Shandong west power grid of China.