| In power distribution systems,circuit breakers,as the main switch devices,are used to connect the current in segmented circuits,so as to protect the electrical equipment and distribution lines from overcurrent damage.The key to ensure the normal and safe operation of the distribution system is to study and optimize the circuit breakers and to design high quality products.The traditional circuit breakers’ design method usually adopts the way of empirical estimation and large number of prototypes,which made the circuit breakers producing more energy consumption,large volume and poor segmental performance.Therefore,it is very important to propose a scientific design method for the optimization of the circuit breakers.Nowadays,the design using intelligent algorithms is scientific and efficient.Among them,Particle Swarm Optimization(PSO),as an intelligent global optimization algorithm,is an efficient method for solving multi parameters and multi conditional complex optimization problems.However,the traditional particle swarm optimization algorithm has some drawbacks in terms of convergence speed and computation accuracy.To solve this problem,an improved particle swarm optimization algorithm is proposed before optimizing the circuit breakers.Then,the improved algorithm is applied to further research and application of circuit breakers’ optimization.The main work and innovation are as follows:(1)The optimization design target and mathematical optimization model for a type of circuit breaker with a type of HSW6 are proposed.Fully considered the source of the energy consumption of HSW6 circuit breakers,the related design parameters will be integrated and establish the energy consumption model of HSW6 circuit breakers.The optimal design of the energy storage springs of HSW6 circuit breakers and their constraints are derived in the form of mathematical boundary conditions.The experimental research shows that the energy consumption mathematical optimization model and the energy storage springs design model of the circuit breakers are more reliable.(2)Research on Catfish Effect-Cloud Particle Swarm Optimization(CE-CPSO)algorithm.In order to solve those problem of traditional PSO algorithm falling into local optimum easily,premature convergence,slow convergence speed and poor diversity of the candidate solutions,cloud model is introduced to find optimal classification of multi particles and control particle swarms in different state using different inertia weights to speed up in the global scope rapid optimization;meanwhile,the mechanism of catfish effect is introduced so as to put forward new corresponding catfish disturbance model,which increases the number of candidate solutions.Through the test of classical functions,the comparison results show that the proposed CE-CPSO algorithm is superior to thetraditional PSO algorithm.(3)Application of the improved CE-CPSO algorithm in the low energy consumption optimization design of the circuit breakers.In order to optimize the energy consumption of circuit breakers,based on the mathematical optimization model of HSW6 circuit breaker,the CE-CPSO algorithm is applied to optimize the parameters of circuit breakers.The experimental results show that the performance and optimal design effect of the improved algorithm is better than the traditional PSO algorithm.The optimized circuit breakers are more energy saving and material saving.(4)Application of the improved CE-CPSO algorithm in the optimization of the energy storage springs of the circuit breakers.In order to optimize the structural parameters of circuit breaker energy storage springs,CE-CPSO algorithm is also used to optimize the parameters of mass springs.The experimental results show that in the spring optimization design of the circuit breakers,despite many complex constraints,while the CE-CPSO algorithm is still feasible,and the optimal design parameters are better than the traditional PSO algorithm.Under the same working conditions,the circuit breakers are smaller. |
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