Guowei Hua

A location-sizing model for electric vehicle charging station deployment based on queuing theory

Imperfect electric vehicle charging infrastructure network has become a major obstacle for prompting the adoption of electric vehicles. Kuby (2005) considered the constraint of vehicle range, and developed a location model for alternative-fueling vehicles based on maximum flow -FRLM (flow - refueling location mode). In the plan of deploying an electric vehicle charging station network, not only should we consider the vehicle range, but also need to realize the queuing issue because of the number limitation of charging spots. Therefore, when we design a charging station network, we need to take the number of charging spots into consideration. In this paper, we extend the FRLM, combining with the queuing theory, and reformulate a new location-sizing model in a given largest waiting time that customers can accept. The location-sizing model optimally allocate the charging spots without exceed the given waiting time so as to maximize the total charging service. And we also conclude the different influence on the results of different factors via a series of numerical experiments, and give some advice for the developing direction of the electric car in the future.

The flow capturing location model and algorithm of electric vehicle charging stations

As a necessary supporting infrastructure in development of electric vehicles, electric vehicle charging stations can provide electric vehicles charging service. Their locations are reasonable or not directly related to the development of the electric vehicle industry and their service quality, efficiency, convenience, etc. On the basis of flow capturing location model, this paper treats intercepting the largest demand as the goal and uses particle swarm optimization algorithm to simulate the model to prove its effectiveness and practicability. The simulation result shows that the model and algorithm used in this paper can establish an optimal selection of location, and be able to provide some decisions to the real facility location.

The carbon emission reduction coordination of fresh supply chain based on the limited carbon quota and trading

In this paper, against the background of low-carbon fresh supply chain, the government of carbon quota for the whole supply chain is limited and the carbon training policy is exist, we analyzed the centralized and distributed decision-making scenario how the producer and retailer cooperate on the carbon emission reduction, then studied the interaction between the emission reduction rate of producer and retailer, and comprise the average emission reduction rate of supply chain, also explore the impact of carbon trading price on emission reduction in four situations. The results shows that at what conditions of the carbon emissions reduction make sense, also get the conclusion that in centralized decision-making scenario, the emission reduction rate of supply chain is optimal, and with the higher training price, the emission reduction rate is higher too, vice versa. The conclusions provide some intellectual support for enterprises to make rational emission reduction strategies. This paper theoretically support the methods of cooperation for supply chain.

Forecasting container throughput with big data using a partially combined framework

This study proposes a partially-combined forecasting framework for container throughput based on big data composed of structured historical data and unstructured data. Under the proposed framework, the structured data (the original time series) is firstly decomposed into linear component and nonlinear component. Seasonal auto-regression integrated moving average model (SARIMA) is adopted to capture and forecast the linear component, and a combined model, composed of least squares support vector regression (LSSVR) and artificial neural network (GP), is applied to modeling the nonlinear component. Next, unstructured data is analyzed by an expert system. With the synthesized expert judgment, the forecasts of linear and nonlinear components are integrated into a final forecast. For the illustration and verification purpose, an empirical study is conducted with the data of Qingdao Port. The results show that the model under the proposed framework significantly outperforms its competitive rivals.

Charging and discharging strategies for electric vehicles based on V2G

The extensive application of electric vehicles will make a series influence on power gird. Based on V2G technology this paper discusses the charging and discharging strategies, combining the peak-valley price and the travel habit. We propose a non-cooperation master-slave game model, in which the power company decides discharging price, and the owner of electric vehicles decides the amount of charging and discharging. In this game, we incorporate the loss of power grid into the total cost, and the amount of discharging is limited by the surplus power. At the game equilibrium point, both of the participants will achieve the maximum benefits.

Economic analysis for container shipping route

Asian container routes are the area where world 10 big ports are concentrated including Busan Port based on container cargo handling records in 2013 and the competition to attract container cargos between such ports is very tough. This paper has developed an economy evaluation model corresponding to change in transshipment cargo volume of neighbor ports in North East Asia classifying to Route 1 and Route 2 with Busan Port as a starting point and carried out an economy evaluation of the sea route, an important data for deciding sea routes and calling ports of the shipping companies by applying this model. As a result of analyzing such 2 routes, the shipping company can develop a more profitable route and the port related government authority or operational institution of each country can figure out the threshold of feeder cargo volume in economic viewpoint.

Research on two-stage supply chain to establish the carbon emissions trading alliance

As more and more enterprises are willing to join the carbon emissions trading mechanism, it is necessary to explore a two-stage supply chain which includes upstream and downstream enterprises how to formulate the enterprise plans to reduce emissions. Through the study of internal carbon trading price of the carbon emissions trading alliance, we have a deep discussion for the decision of establishing the carbon emissions trading alliance. The results show that the upstream and downstream enterprises in the supply chain have respective optimal pricing and maximum profits before and after establishing the carbon emissions trading alliance. They choose to establish the carbon emissions trading alliance only in their respective alliances internal carbon trading price range. Therefore, enterprises should obtain a mutually beneficial internal carbon trading price through negotiation to promote the establishment of carbon emissions trading alliance.