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By using of concentration sensors on the premixed tower, the stratification phenomenon of methane has been observed; the change rule of methane concentration at different heights of premixed tower has been analyzed. The results show that, the relation between the time that methane concentration began to be stable and the height of methane in premixed tower shows linear function: T=T0+Ah; the relation between the stable methane concentration and the height of methane in premixed tower shows exponential function: C=C0(1-eAh) .Based on this, a simple, economic and safe method of separating and purifying methane in coal-bed gas has been proposed.

Evaluating the possible impact on power system of a large number of electric vehicles (EVs) is becoming of great interest. With the development of V2G technology, electric vehicles constitute a significant power reserve. In addition, batteries in electric vehicles may be used to provide storage capability for energy produced by renewable sources and to supply auxiliary services to the grid. The paper presents the preliminary results of an on-going project aimed at evaluating the impact of electric vehicles on power system. The simulation results shows significant benefits of V2G on the daily load profiles and network planning. Hypotheses such as battery size, number of users, load profiles without and with different EV penetration are presented for successive scenarios set-up and simulations.

To solve the problem of unsupervised anomaly detection, an unsupervised anomaly-detecting algorithm based on an evolutionary artificial immune network is proposed in this paper. An evolutionary artificial immune network is “evolved” by using unlabeled training sample data to represent the distribution of the original input data set. Then a traditional hierarchical agglomerative clustering method is employed to perform clustering analysis within the algorithm. It is shown that the algorithm is feasible and effective with simulations over the 1999 KDD CUP dataset.