The increasing penetration of distributed generation (DG) brings about great fluctuation and uncertainty in distribution networks. In order to improve the ability of distribution networks to cope with disturbances caused by uncertainties and to evaluate the maximum accommodation capacity of DG, a multi-objective programming method for evaluation of the accommodation capacity of distribution networks for DG is proposed, considering the flexibility of distribution networks in this paper. Firstly, a multi-objective optimization model for determining the maximum accommodation of DG by considering the flexibility of distribution networks is constructed, aiming at maximizing the daily energy consumption, minimizing the voltage amplitude deviation, and maximizing the line capacity margin. Secondly, the comprehensive learning particle swarm optimization (CLPSO) algorithm is used to solve the multi-objective optimization model. Then, the mixed strategy Nash equilibrium is introduced to obtain the frontier solution with the optimal joint equilibrium value in the Pareto solution set. Finally, the effectiveness of the proposed method is demonstrated with an actual distribution network in China. The simulation results show that the proposed planning method can effectively find the Pareto optimal solution set by considering multiple objectives, and can obtain the optimal equilibrium solution for DG accommodation capacity and distribution network flexibility. the connection of DG into distribution networks may cause many problems, such as power quality, relay protection, and flexibility, which will affect the secure and reliable operation of the distribution network [7]. The volatility, intermittency, and unpredictability of renewable energy influence the fluctuation in distribution networks under high penetration of DG, resulting in low efficiency and great investment in distribution network equipment [8]. Improving the flexibility of distribution networks and effectively reducing the adverse impact of the high penetration of DG have become global research hotspots in recent years [9,10].Many research works have studied the flexibility of distribution networks by considering DG connection. In [11], an intelligent distribution network optimization planning model aiming to minimize comprehensive costs is proposed. The influence of flexible resources and strategies such as operation control means and demand side management on the distribution network planning are comprehensively considered in the proposed model. In [12], a multi-objective optimization dispatching model considering interruptible loads and energy storage is constructed based on the five flexibility indices. It is proven that the optimal dispatching of flexible resources can effectively improve the flexibility of the distribution network, with high penetration of DG, and that the ability of the distribution network to accommodate DG can be assessed with the proposed model. In [13], the flexible planning for power systems with high penetration of renewable energy is ...

Ant colony algorithm is a kind of effective combinatorial optimization problem solving algorithm has been increasingly, thorough research, and gradually get used. Ant colony algorithm is a set of parameters, the algorithm, a lack of adequate experiences often. The paper has put forward a single genetic character of ant colony algorithm. Will the ant colony algorithm each search results as the initial population, single genetic improvement, for the shortest route optimization. In the traveling salesman problem of the experiments prove the effectiveness of the proposed algorithm.