Dynamic stochastic optimal power flow considering spatial correlation of wind speed based on simplified pair copula

摘要

With large-scale wind power integrating into power grid, it's increasingly important to consider uncertainty factors into power system operation scheduling. In actual operation, wind power outputs are relatively strong correlation. It will bring larger computational error without considering these factors. Current researches are inadequate to model multiple dependent wind power outputs. Recently, presented stochastic optimal power flow models have lower computational efficiency and not able to assure the convergence. To solve these problems, a second-order cone dynamic stochastic optimal power flow model is proposed based on Simplified Pair Copula model. In this model, original non-linear models are transformed into SOCP models after constructing multiple correlated wind power outputs. Improved point estimate method and GUROBI are used to solve this model. Comparing with the program without considering the correlation of wind speed, the proposed method is proved to be effectiveness and practicability.