SCOPF considering voltage and power fluctuation under renewable energy integration

Abstract

Security-Constrained Optimal Power Flow (SCOPF) method could generate system optimal operation point, which guarantee system security by avoiding any overload whenever expected N-1 contingencies occurred. However, renewable power integration increases uncertainty of system security, which is not well treated in conventional SCOPF model. Then this study proposes an improved SCOPF model, which aims at optimizing outputs of generators to increasing security of system facing challenges by N-1 contingencies accompanied by renewable power fluctuations. Semi-invariant is employed to express the stochastic behavior of wind and photovoltaic power generation. Considering the influence of transformer transformation ratio on admittance matrix, the uncertainty of injected renewable power is combined with the adjustable characteristics of network parameters to obtain the fluctuation model of branch power and bus voltage. Therefore, the constraints for SCOPF are restated to treat the problem that expected value based traditional model makes errors to confirm overload. The probability analysis for branch overload allows this study to present a potential reduced contingency set, in which small-probability events are rationally excluded. Thus, the constraint quantities as well as the complexity of the optimization problem are effectively reduced to decrease the computation burden. A Benders decomposition method based interior point approach is used to solve the improved SCOPF optimization model. Case studies based on IEEE39 bus system demonstrate the efficiency of proposed method.