Coordinated Voltage Control of Distribution Network ConsideringMultiple Types of Electric Vehicles

The couple between the power network and the transportation network(TN)is deepening gradually with the increasing penetration rate of electric vehicles(EV),which also poses a great challenge to the traditional voltage control scheme.In this paper,we propose a coordinated voltage control strategy for the active distribution networks considering multiple types of EV.In the first stage,the action of on-load tap changer and capacitor banks,etc.,are determined by optimal power flow calculation,and the node electricity price is also determined based on dynamic time-of-use tariff mechanism.In the second stage,multiple operating scenarios of multiple types of EVs such as cabs,private cars and buses are considered,and the scheduling results of each EV are solved by building an optimization model based on constraints such as queuing theory,Floyd-Warshall algorithm and traffic flow information.In the third stage,the output power of photovoltaic and energy storage systems is fine-tuned in the normal control mode.The charging power of EVs is also regulated in the emergency control mode to reduce the voltage deviation,and the amount of regulation is calculated based on the fair voltage control mode of EVs.Finally,we test the modified IEEE 33-bus distribution system coupled with the 24-bus Beijing TN.The simulation results show that the proposed scheme can mitigate voltage violations well.

CPS Modeling of CNC Machine Tool Work Processes Using an Instruction-Domain Based Approach

Building cyber-physical system(CPS) models of machine tools is a key technology for intelligent manufacturing. The massive electronic data from a computer numerical control(CNC) system during the work processes of a CNC machine tool is the main source of the big data on which a CPS model is established. In this work-process model, a method based on instruction domain is applied to analyze the electronic big data, and a quantitative description of the numerical control(NC) processes is built according to the G code of the processes. Utilizing the instruction domain, a work-process CPS model is established on the basis of the accurate, real-time mapping of the manufacturing tasks, resources, and status of the CNC machine tool. Using such models, case studies are conducted on intelligent-machining applications, such as the optimization of NC processing parameters and the health assurance of CNC machine tools.

The Influence of Survival Analysis on Runx3 Gene Expression in the Primary Tumor of Patients Suffering from Stomach Carcinoma

Background: Runt domain transcription factor 3 (Runx3) is a putative tumor suppressor in human neoplasia. Previous researches suggested that a lack of Runx3 function contributed to human gastric carcinogenesis, however, it is not clear whether Runx3 is closely associated with clinicopathological features of primary stomach tumor and survival rate of patients. Aims: The article is to investigate the influence of survival analysis on Runx3 gene expression in the primary stomach tumor. Methods: Runx3 mRNA expression was detected in 108 primary gastric tumors and non-tumor tissue by semiquantitative reverse transcription-PCR (RT-PCR). All patients were followed up more than five years after radical gastrectomy. Results: There was a loss or substantial decrease of Runx3 mRNA expression in 108 cases of gastric tumors as compared with that in normal gastric mucosa (p 0.001). According to the gray scale median of Runx3 mRNA in primary tumors, the 108 cases were separated into two groups: The lower expressing group (≤0.403) and the over one (>0.403). By comparing analysis of clinical information between two groups, it was found that the lower expression of Runx3 mRNA in the primary tumor was not only associated with the poor clinicopathological factors, but also the inferior survival duration and cumulative survival rate of patients (p 0.05). Conclusions: These results strongly suggest that Runx3 was an independent prognostic factor and a potential therapeutic target for gastric cancer.