Market demand and technological progress drive continuous product evolution, upgrade and innovation, which necessitate readjustment and evolution balancing of the mixed model assembly line (MMAL) for improving product...
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Market demand and technological progress drive continuous product evolution, upgrade and innovation, which necessitate readjustment and evolution balancing of the mixed model assembly line (MMAL) for improving production efficiency. In the evolution process of MMAL, the rational matching between difficulty of assembly tasks and operating level are mainly considered, the mathematical model of evolution balancing optimization for MMAL is established, and an improvedparticleswarm optimization algorithm (IPSO) based on leapfrog algorithm is designed. In the process of optimization, the single population is divided into several subgroups for searching, information exchange between species is executed to get better particles and the strategy of returning to the beginning is introduced, in which particle diversity and global search capability are increased and improved, respectively. Finally, the effectiveness and feasibility of the method were validated by evolution balancing planning of MMAL.
In this study, firstly, the bi-directional energy flow of grid-connected photovoltaic and energy storage system based on power electronic transformer is demonstrated. Based on this, a bi-level programming model is pro...
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In this study, firstly, the bi-directional energy flow of grid-connected photovoltaic and energy storage system based on power electronic transformer is demonstrated. Based on this, a bi-level programming model is proposed for the location and capacity of energy storage. The optimisation of the location of the outer layer is based on the improved particle swarm algorithm. The energy storage location is a variable, and network loss as well as PET loss are objective functions. The improvedparticleswarm optimisation algorithm is still adopted to optimise the capacity in the inner layer. The cost of electricity from the main grid is taken as the objective function, and the economic dispatch is realised based on the energy routing strategy of power electronic transformer.
In this study, a comprehensive reconfiguration and operation optimisation of distribution system with flexible DC device (FDD) is discussed. The structures of distribution network with FDD are illustrated and the exac...
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In this study, a comprehensive reconfiguration and operation optimisation of distribution system with flexible DC device (FDD) is discussed. The structures of distribution network with FDD are illustrated and the exact operating of FDD set-points are discussed which realised power flow control and loop closing operation of distribution system. Then, the non-linear combinational optimisation models of reconfiguration and operation optimisation with FDD are established considering different objectives and constraints. In order to solve the complicated optimisation problems, improved particle swarm algorithm and sequential AC/DC power flow method are used. Results show that the FDD have stronger ability to promote the performance of distribution system with power flow optimal adjusting and cooperation with traditional switch.
This paper aims at the problem of dynamic target path planning for vehicles in ***,design an urban real-time dynamic path planning model(UR-MODE)based on the Storm framework;then,proposes an improvedparticleswarm op...
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This paper aims at the problem of dynamic target path planning for vehicles in ***,design an urban real-time dynamic path planning model(UR-MODE)based on the Storm framework;then,proposes an improvedparticleswarm optimization algorithm(Adaptive Partnerparticleswarm optimization,AP-PSO) which introduce the adaptive inertia weight and small scale perturbation strategy to ensure the efficiency of our proposed ***,we implement the improvedalgorithm on the Storm real-time processing system and realize the mass real-time traffic data *** with the existing path planning algorithms,the experiment proves that the UR-MODE based method can reduce the travel time by 15%-20% on average and increase the traffic resource utilization by 50%.It proves the efficiency of the method.
The air source heat pump heat collection control system is a system with strong nonlinearity and large time *** is difficult to achieve the expected control effect on the outlet water temperature by using conventional...
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The air source heat pump heat collection control system is a system with strong nonlinearity and large time *** is difficult to achieve the expected control effect on the outlet water temperature by using conventional control *** view of this problem,this paper makes up for the shortcomings of fuzzy control and PID control,and proposes an improvedparticleswarm optimization（IPSO） fuzzy PID control strategy to control the temperature of the effluent of the air source heat pump heat collection control *** of all,the particleswarm optimization algorithm is easy to fall into the problem of local *** increasing the vector,the optimal position of individual particles is stored to increase the range of particle *** use the improved particle swarm algorithm to optimize the fuzzy PID scale factor and quantization factor to modify the PID parameters in real time to improve the control accuracy of the heat pump ***,a MATLAB/Simulink simulation model for the heat collection temperature control of the heat pump is established and an improvedparticleswarm optimization algorithm program is written,and compared with the fuzzy PID and conventional PID control *** results show that the heat-collection control system based on IPSO has strong adaptability,robustness and anti-interference.
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