Orderly Discharging Strategy for Electric Vehicles at Workplace Based on Time-of-Use Price

According to the parking features of electric vehicles (EVs) and load of production unit, a power supply system including EVs charging station was established, and an orderly discharging strategy for EVs was proposed as well to reduce the basic tariff of producer and improve the total benefits of EV discharging. Based on the target of maximizing the annual income of producer, considering the total benefits of EV discharging, the electric vehicle aggregator (EVA) and time-of-use (TOU) price were introduced to establish the optimization scheduling model of EVs discharging. Furthermore, an improved artificial fish swarm algorithm (IAFSA) combined with the penalty function methods was applied to solve the model. It can be shown from the simulation results that the optimal solution obtained by IAFSA is regarded as the orderly discharging strategy for EVs, which could reduce the basic tariff of producer and improve the total benefits of EV discharging.

Solving the Dynamic Model of Metabolic Network of Escherichia coli by Adams Methods

We previously analyzed the dynamic flux distribution and predicted glucose, biomass concentrations of metabolic networks ofE. coliby using the penalty function methods. But the consequences were not as well as we expected. In order to improve the predicated accuracy of the metabolite concentrations, instead of using Runge-Kutta algorithm, we apply Adams methods which belong to the multi-step ones in the process that solves the dynamic model of metabolic network ofE. coliand obtain better simulation results on the metabolic concentrations.