Location and Capacity Determination Method of Electric Vehicle Charging Station Based on Simulated Annealing Immune Particle Swarm Optimization

As the number of electric vehicles(EVs)continues to grow and the demand for charging infrastructure is also increasing,how to improve the charging infrastructure has become a bottleneck restricting the development of EVs.In other words,reasonably planning the location and capacity of charging stations is important for development of the EV industry and the safe and stable operation of the power system.Considering the construction and maintenance of the charging station,the distribution network loss of the charging station,and the economic loss on the user side of the EV,this paper takes the node and capacity of charging station planning as control variables and the minimum cost of system comprehensive planning as objective function,and thus proposes a location and capacity planning model for the EV charging station.Based on the problems of low efficiency and insufficient global optimization ability of the current algorithm,the simulated annealing immune particle swarm optimization algorithm(SA-IPSO)is adopted in this paper.The simulated annealing algorithm is used in the global update of the particle swarm optimization(PSO),and the immune mechanism is introduced to participate in the iterative update of the particles,so as to improve the speed and efficiency of PSO.Voronoi diagram is used to divide service area of the charging station,and a joint solution process of Voronoi diagram and SA-IPSO is proposed.By example analysis,the results show that the optimal solution corresponding to the optimisation method proposed in this paper has a low overall cost,while the average charging waiting time is only 1.8 min and the charging pile utilisation rate is 75.5%.The simulation comparison verifies that the improved algorithm improves the operational efficiency by 18.1%and basically does not fall into local convergence.

Microporous Organic Nanotube Networks from Hyper Cross-linking Core-shell Bottlebrush Copolymers for Selective Adsorption Study

We report a synthesis of microporous organic nanotube networks（MONNs） by a combination of hyper cross-linking and molecular templating of core-shell bottlebrush copolymers. The intrabrush and interbrush cross-linking of polystyrene（PS） shell layer in the core-shell bottlebrush copolymers led to the formation of micropores and large-sized nanopores（meso/macrospores） in MONNs, respectively, while selective removal of polylactide（PLA） core layer generated mesoporous tubular structure. The size of PLA-templated mesoporous cores and porous structure both at micro-and meso-scale could be controlled by simple tuning of the ratio of core/shell or the PLA core fraction in the bottlebrush precursors. Moreover, the resultant MONNs showed a highly selective adsorption capacity for the positively charged dyes on the basis of multi-porosity and carboxylate group-rich structure. In addition, MONNs also exhibited effective performance in size-selective adsorption of biomacromolecules. This work represents a new avenue for the preparation of MONNs and also provides a new application for molecular bottlebrushes in nanotechnology.