Introduction  New energy power generation is intermittent and random, and its power is uncertain data, which will cause changes in grid voltage and frequency, thus pose a threat to the safe operation of the power system. In order to ensure the safety of grid voltage after large-scale new energy grid connection, considering the uncertainty of new energy generation, a reactive power optimization strategy of power grid incorporating renewable energy based on interval modeling is proposed.

  Method  This strategy used interval to describe uncertain parameters in reactive power optimization model, and then established interval reactive power optimization model. The interval power flow algorithm based on optimization scenario was used to solve the interval power flow equation, thus obtaining the interval of state variables and determining the feasibility of control variables. On this basis, the improved particle swarm optimization algorithm was used to solve the interval reactive power optimization model, and the local search method and discrete variable cross-processing operation were added to the particle swarm optimization algorithm to improve optimization ability. In order to verify the effectiveness and superiority of the proposed method, IEEE 14 - bus and IEEE 30 - bus examples were used for simulation, and the proposed algorithm was compared with the adaptive genetic algorithm and the ordinary particle swarm optimization algorithm.

  Result  The simulation results show that compared with adaptive genetic algorithm and ordinary particle swarm optimization algorithm, the improved particle swarm interval reactive power optimization strategy has a faster convergence speed, stronger optimization capabilities, and can effectively solve the discrete variables in the model.

  Conclusion  Our data suggest that the proposed strategy can effectively solve the interval reactive power optimization problem and ensure the operation safety of grid voltage after large-scale new energy grid connection.