Research On Artificial Bee Colony Algorithm And Optimal Design For Circuit Breakers

In evolutionary computation,artificial bee colony algorithm(ABC)is a new swarm intelligence optimization algorithm with few control parameters,strong adaptability,strong global search ability and fast convergence speed.Therefore,it has attracted the attention of experts and scholars.It has been applied to many fields such as scientific research and engineering optimization.The optimization effect is good.However,the randomness of honey source selection mechanism,the basic artificial bee colony algorithm is prone to fall into local optimal solution and slow convergence in the later stage.Circuit breaker is an important electronic device used to protect and control circuit,distribute and transmit energy,and field bus bidirectional communication in distribution system.At present,experiential trial calculation and virtual prototyping technology are often used to design circuit breakers.However,the design cycle is long,the result is large,energy consumption is high,and the breaking performance is poor.The key to reliable breaking of circuit breaker is contact spring,but the loading space of the spring is very limited.Therefore,it is particularly important to design miniaturized and low-energy circuit breakers.So the artificial bee colony algorithm and its improved method are deeply studied.The improved algorithm is applied to the optimal design of contact spring and energy consumption of circuit breaker.The application area of the algorithm is extended.The design efficiency of circuit breakers has been improved.The main work and innovation are as follows:(1)Simulation and analysis of commonly used improvement methods of artificial bee colony algorithms.Three commonly used improved methods are simulated and analyzed.The shortcomings of artificial bee colony algorithm such as premature convergence and slow convergence rate are pointed out.The idea of improving the algorithm by adding candidate solutions is proposed.(2)Improvement of artificial bee colony algorithms.An improved artificial bee colony algorithm(CCE-ABC)is studied based on catfish effect and cloud crossover operation.In order to overcome the shortcomings of premature algorithm and slow convergence of the algorithm,a variety of candidate solutions are generated by catfish effect strategy and global search are guide by combining the global optimum idea of particle swarm optimization.Combining the crossover operation of genetic algorithm and cloud model,cloud crossover operation is proposed.The crossover factor is adjusted in time to accelerate the convergence speed of the algorithm and improve the global optimization ability.The results of classical test functions show that the performance of the improved CCE-ABC algorithm is better than the basic ABC algorithm,adaptive particle swarm optimization algorithm(APSO)and adaptive genetic algorithm(AGA).(3)Research on circuit breaker model.Firstly,the working principle of circuit breaker contact system is analyzed.The working conditions of contact spring are deduced and a new type of spring optimization model and constraint condition is constructed.Secondly,the source of energy consumption of circuit breaker is analyzed.Considering the cost,copper consumption,number of contacts and other factors,a reliable energy consumption optimization model is established.(4)Optimum design of circuit breaker based on improved CCE-ABC algorithm.The improved CCE-ABC algorithm is used to iteratively optimize the proposed contact spring model function and energy consumption model function.The results show that the spring parameters designed by CCE-ABC algorithm are more reasonable,the volume is smaller,the contact wear can be reduced,and the improved algorithm has lower energy consumption,less material consumption and cost saving.