Abstract: Crisscross optimization algorithm (CSO) has been applied to solve many complex problems in power system and remarkable results have been achieved. On this basis, a faster crisscross optimization algorithm (FCSO) is proposed to solve the optimal power flow problem. In this algorithm, a new operator—the central crossover operator is proposed based on the original double-crossover operator, which alternates with the crossover operator in a certain pattern; each individual in the population performs a crossover operation with the current optimal individual in turn, and then executes a competition operator to selectively move closer to the global optimal individual, thus improving the quality of each iteration and accelerating convergence. The simulation results in an IEEE-118 bus system show that, compared to other swarm intelligence optimization algorithms, the CSO has the advantage of high convergence accuracy and strong stability, while the FCSO can significantly improve the convergence speed and greatly shorten the consuming time without losing the convergence accuracy, which provides more possibilities for applying the CSO to the real-time control of the power grid.