Connections Between Induction Generator Effect and Open-loop Modal Proximity to Cause Sub-synchronous Oscillations in Series-compensated Power System

The induction generator effect(IGE)and the openloop modal proximity(OLMP)are two different reasons why subsynchronous oscillations(SSOs)in a series-compensated power system(SCPS)may occur.The IGE attributes the growing SSOs to negative resistance,while the OLMP explains the SSO mechanism from the standpoint of modal conditions.In this paper,we investigate the connections between the IGE and the OLMP through equivalent RLC circuit and open-loop modal analysis.Our investigation is conducted for two types of seriescompensated power systems where either a synchronous generator or a DFIG is connected at the sending end.The investigation reveals the conditions,in which the IGE and the OLMP may jointly cause the growing SSOs,i.e.,both the IGE and the OLMP can explain why the growing SSOs occur.Furthermore,the investigation indicates that the IGE and the OLMP may be totally irrelevant and lead to growing SSOs separately.This implies that it is possible that in a SCPS,the growing SSOs are only due to the IGE,and the OLMP is non-existent,and vice versa.Hence,when the growing SSOs occurs in a SCPS,examination based on both the IGE and the OLMP should be carefully conducted in order to find if the oscillatory instability is due to the IGE,or the OLMP,or both of them.

THEORETICAL MODEL OF EFFECTIVE STRESS COEFFICIENT FOR ROCK/SOIL-LIKE POROUS MATERIALS

Physical mechanisms and influencing factors on the effective stress coefficient for rock/soil-like porous materials are investigated, based on which equivalent connectivity index is proposed. The equivalent connectivity index, relying on the meso-scale structure of porous material and the property of liquid, denotes the connectivity of pores in Representative Element Area （REA）. If the conductivity of the porous material is anisotropic, the equivalent connectivity index is a second order tensor. Based on the basic theories of continuous mechanics and tensor analysis, relationship between area porosity and volumetric porosity of porous materials is deduced. Then a generalized expression, describing the relation between effective stress coefficient tensor and equivalent connectivity tensor of pores, is proposed, and the expression can be applied to isotropic media and also to anisotropic materials. Furthermore, evolution of porosity and equivalent connectivity index of the pore are studied in the strain space, and the method to determine the corresponding functions in expressions above is proposed using genetic algorithm and genetic programming. Two applications show that the results obtained by the method in this paper perfectly agree with the test data. This paper provides an important theoretical support to the coupled hydro-mechanical research.

Three-dimension micro magnetic detector based on GMI effect

The giant magneto-impedance（GMI）effect of amorphous wire was analyzed theoretically.The amorphous wire had strong GMI effect in the stimulation of sharp pulse of 680kHz and18 mV.A pulse generator was designed to provide high frequency pulse to a magnetic impedance（MI）element.The induced voltage on the pickup coil wound on the amorphous wire was sampled and held with a detect circuit using analog switch.A stable magnetic sensor was constructed.A three-dimension micro magnetic field detector was designed with a central controller MSP430F449.High stability and sensitivity were obtained in the MI sensor with the detect circuit.Experiment results showed that the resolution of the detector was 1nT in the full scale of±2 Oe and the detector worked stably from the room temperature to about 80℃.A small ferromagnetic target was detected by the three-dimension detector in laboratory environment without magnetic shielding.The target moving direction was ascertained with the wave shape of axis parallel in that direction.

Generalized Coherent States for Position-Dependent Effective Mass Systems

A generalized scheme for the construction of coherent states in the context of position-dependent effective mass systems has been presented. This formalism is based on the ladder operators and associated algebra of the system which are obtained using the concepts of supersymmetric quantum mechanics and the property of shape invariance. In order to exemplify the general results and to analyze the properties of the coherent states, several examples have been considered.

Optimal power flow calculation in AC/DC hybrid power system based on adaptive simplified human learning optimization algorithm

This paper employs an efficacious analytical tool,adaptive simplified human learning optimization(ASHLO)algorithm,to solve optimal power flow(OPF)problem in AC/DC hybrid power system,considering valve-point loading effects of generators,carbon tax,and prohibited operating zones of generators,respectively.ASHLO algorithm,involves random learning operator,individual learning operator,social learning operator and adaptive strategies.To compare and analyze the computation performance of the ASHLO method,the proposed ASHLO method and other heuristic intelligent optimization methods are employed to solve OPF problem on the modified IEEE 30-bus and 118-bus AC/DC hybrid test system.Numerical results indicate that the ASHLO method has good convergent property and robustness.Meanwhile,the impacts of wind speeds and locations of HVDC transmission line integrated into the AC network on the OPF results are systematically analyzed.

Joint model of user check-in activities for point-of-interest recommendation

With the rapid development of location-based networks, point-of-interest（POI） recommendation has become an important means to help people discover interesting and attractive locations, especially when users travel out of town. However, because users only check-in interaction is highly sparse, which creates a big challenge for POI recommendation. To tackle this challenge, we propose a joint probabilistic generative model called geographical temporal social content popularity（GTSCP） to imitate user check-in activities in a process of decision making, which effectively integrates the geographical influence, temporal effect, social correlation, content information and popularity impact factors to overcome the data sparsity, especially for out-of-town users. Our proposed the GTSCP supports two recommendation scenarios in a joint model, i.e., home-town recommendation and out-of-town recommendation. Experimental results show that GTSCP achieves significantly superior recommendation quality compared to other state-of-the-art POI recommendation techniques.