Nowadays, the technology of renewable sources grid-connection and DC transmission has a rapid development. And phasor measurement units(PMUs) become more notable in power grids, due to the necessary of real time monit...Nowadays, the technology of renewable sources grid-connection and DC transmission has a rapid development. And phasor measurement units(PMUs) become more notable in power grids, due to the necessary of real time monitoring and close-loop control applications. However, the PMUs data quality issue affects applications based on PMUs a lot. This paper proposes a simple yet effective method for recovering PMU data. To simply the issue, two different scenarios of PMUs data loss are first defined. Then a key combination of preferred selection strategies is introduced. And the missing data is recovered by the function of spline interpolation. This method has been tested by artificial data and field data obtained from on-site PMUs. The results demonstrate that the proposed method recovers the missing PMU data quickly and accurately. And it is much better than other methods when missing data are massive and continuous. This paper also presents the interesting direction for future work.展开更多
In order to improve the efficiency of overpass and the safety level of pedestrian, this paper aims to investigate the contributing factors for selective preference of overpass. Eight overpasses were investigated in Xi...In order to improve the efficiency of overpass and the safety level of pedestrian, this paper aims to investigate the contributing factors for selective preference of overpass. Eight overpasses were investigated in Xi＇an, and a questionnaire was conducted by the pedestrians near the overpass. Totally, 1131 valid samples （873 used of overpasses and 258 non-used of overpasses） were collected. Based on the data, a binary logit （BL） model was developed to identify what and how the factors affect the selective preference of overpass. The BL model was calibrated by the maximum likelihood method. Likelihood ratio test and McFadden-R2 were used to analyze the goodness-of-fit of the model. The results show that the BL model has a reasonable goodness-of-fit, and the prediction accuracy of the BL model can reach 81.9%. The BL model showed that the selective preference of overpass was signifi- cantly influenced by eight factors, including gender, age, career, education level, license, detour wishes, detour distance, and crossing time. Besides, the odds ratios of significant factors were also analyzed to explain the impacts of the factors on selective preference of overpass.展开更多
基金supported in part by National Natural Science Foundation of China(NSFC)(51627811,51707064)Project Supported by the National Key Research and Development Program of China(2017YFB090204)Project of State Grid Corporation of China(SGTYHT/16-JS-198)
文摘Nowadays, the technology of renewable sources grid-connection and DC transmission has a rapid development. And phasor measurement units(PMUs) become more notable in power grids, due to the necessary of real time monitoring and close-loop control applications. However, the PMUs data quality issue affects applications based on PMUs a lot. This paper proposes a simple yet effective method for recovering PMU data. To simply the issue, two different scenarios of PMUs data loss are first defined. Then a key combination of preferred selection strategies is introduced. And the missing data is recovered by the function of spline interpolation. This method has been tested by artificial data and field data obtained from on-site PMUs. The results demonstrate that the proposed method recovers the missing PMU data quickly and accurately. And it is much better than other methods when missing data are massive and continuous. This paper also presents the interesting direction for future work.
基金sponsored by the National Natural Science Foundation of China(No.51178108)the Scientific Research Foundation of Graduate School of Southeast University(No.YBJJ1458)the Fundamental Research Funds for the Central Universities and the Scientific Innovation Research of College Graduates in Jiangsu Province(Nos.KYLX_0173,KYLX_0174)
文摘In order to improve the efficiency of overpass and the safety level of pedestrian, this paper aims to investigate the contributing factors for selective preference of overpass. Eight overpasses were investigated in Xi＇an, and a questionnaire was conducted by the pedestrians near the overpass. Totally, 1131 valid samples （873 used of overpasses and 258 non-used of overpasses） were collected. Based on the data, a binary logit （BL） model was developed to identify what and how the factors affect the selective preference of overpass. The BL model was calibrated by the maximum likelihood method. Likelihood ratio test and McFadden-R2 were used to analyze the goodness-of-fit of the model. The results show that the BL model has a reasonable goodness-of-fit, and the prediction accuracy of the BL model can reach 81.9%. The BL model showed that the selective preference of overpass was signifi- cantly influenced by eight factors, including gender, age, career, education level, license, detour wishes, detour distance, and crossing time. Besides, the odds ratios of significant factors were also analyzed to explain the impacts of the factors on selective preference of overpass.
