With the development and application of large-scale renewable energy sources, the electric power grid is becoming ever larger and more complicated. One of the most concerning problems is how to ensure coordination between a large number of varied controllers. Differential games theory is used to solve the problem of collaborative control. However, it is difficult to solve the differential game problem with constraints using the traditional algorithm. Furthermore, simulation models established by existing research are almost linear, which is not conducive to practical engineering application. To solve the above problem, this paper proposes a co-evolutionary algorithm based on the Weighted Fruit Fly Optimization Algorithm (WFOA) to solve a multi-area frequency collaborative control model with nonlinear constraints. Simulation results show that compared with a co-evolutionary genetic algorithm and a collaborative multi-objective particle swarm optimization algorithm, the method exhibits better control efficiency and better robustness to the changes in external disturbance and the internal unit parameters of systems. This work is supported by National Natural Science Foundation of China (No. 51867005).