An Equivalent Modeling for Synthesis Load of Distributed Network with Small Hydropower

2014 ◽  
Vol 666 ◽  
pp. 119-124
Author(s):  
Zai De Xu ◽  
Guo Cheng Sun ◽  
Ben Ren Pan ◽  
Ning Xu ◽  
Chao Qun Li ◽  
...  
Keyword(s):  
Weighted Average ◽  
Active Power ◽  
Research Subject ◽  
Distributed Network ◽  
Small Hydropower ◽  
Rocking Curve ◽  
Weighted Average Method ◽  
Equivalent Impedance ◽  
Before And After ◽  
Methods Of Synthesis

A distributed network with small hydropower is taken as research subject, and in PSASP environment a simulation network is constructed, which is based on the network’s connection mode and operation data. At first, this paper give a description of 3rd mode of small hydropower generator, and generalize common analysis methods of synthesis load, and on this basis lists three means that used for aggregating parameters, then choose weighted average method to aggregate necessary parameters of Small hydropower generators. Secondly, the operation data is fully used to determine the equivalent impedance of the network. Finally, in order to verify the accuracy and feasibility of the method raised by the paper, the author make a comparison of small hydropower generators’ relative rocking curve before and after equivalence, meanwhile, analyzes change regulation of active power in contact line before and after the equivalence.

scholarly journals Fine-scale multiannual survey of benthic invertebrates in a glacier-fed stream used for hydropower generation

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Alberto Scotti ◽  
Roberta Bottarin
Keyword(s):  
Research Programme ◽  
Eastern Alps ◽  
Hydropower Plant ◽  
Research Network ◽  
Small Hydropower ◽  
Hydropower Plants ◽  
Before And After ◽  
Long Term Ecological Research ◽  
Research Facilities

AbstractThe present dataset contains information about aquatic macroinvertebrates and environmental variables collected before and after the implementation of a small “run-of-river” hydropower plant on the Saldur stream, a glacier-fed stream located in the Italian Central-Eastern Alps. Between 2015 and 2019, with two sampling events per year, we collected and identified 34,836 organisms in 6 sampling sites located within a 6 km stretch of the stream. Given the current boom of the hydropower sector worldwide, and the growing contribution of small hydropower plants to energy production, data here included may represent an important – and long advocated – baseline to assess the effects that these kinds of powerplants have on the riverine ecosystem. Moreover, since the Saldur stream is part of the International Long Term Ecological Research network, this dataset also constitutes part of the data gathered within this research programme. All samples are preserved at Eurac Research facilities.

Pre- and Post-Tsunami Depth Changes of Submarine Topography for the Analysis of Submarine Landslide-Induced Tsunami: Proposal of Digitization Method and Application to the Case of the 1923 Great Kanto Earthquake Tsunamis

2021 ◽  
Author(s):  
Kazuki Murata ◽  
Shinji Sassa ◽  
Tomohiro Takagawa ◽  
Toshikazu Ebisuzaki ◽  
Shigenori Maruyama
Keyword(s):  
Large Scale ◽  
Interpolation Method ◽  
Weighted Average ◽  
Tokyo Bay ◽  
Submarine Landslides ◽  
Sagami Bay ◽  
Seabed Topography ◽  
Kanto Earthquake ◽  
Before And After ◽  
Tsunami Event

Abstract We first propose and examine a method for digitizing analog data of submarine topography by focusing on the seafloor survey records available in the literature to facilitate a detailed analysis of submarine landslides and landslide-induced tsunamis. Second, we apply this digitization method to the seafloor topographic changes recorded before and after the 1923 Great Kanto earthquake tsunami event and evaluate its effectiveness. Third, we discuss the coseismic large-scale seafloor deformation at the Sagami Bay and the mouth of the Tokyo Bay, Japan. The results confirmed that the latitude / longitude and water depth values recorded by the lead sounding measurement method can be approximately extracted from the sea depth coordinates by triangulation survey through the overlaying of the currently available GIS map data without geometric correction such as affine transformation. Further, this proposed method allows us to obtain mesh data of depth changes in the sea area by using the interpolation method based on the IDW (Inverse Distance Weighted) average method through its application to the case of the 1923 Great Kanto Earthquake. Finally, we analyzed and compared the submarine topography before and after the 1923 tsunami event and the current seabed topography. Consequently, we found that these large-scale depth changes correspond to the valley lines that flow down as the topography of the Sagami Bay and the Tokyo Bay mouth.

Front vehicle detection based on improved fusion method for lidar and visual image

2022 ◽  
pp. 095440702110685
Author(s):  
Aijuan Li ◽  
Zhenghong Chen ◽  
Donghong Ning ◽  
Xin Huang ◽  
Gang Liu
Keyword(s):  
Average Method ◽  
Weighted Average ◽  
Visual Image ◽  
Vehicle Detection ◽  
Detection Accuracy ◽  
The Real ◽  
Weighted Average Method ◽  
Weighted Fusion ◽  
Vehicle Test ◽  
Real Vehicle

In order to ensure the detection accuracy, an improved adaptive weighted (IAW) method is proposed in this paper to fuse the data of images and lidar sensors for the vehicle object’s detection. Firstly, the IAW method is proposed in this paper and the first simulation is conducted. The unification of two sensors’ time and space should be completed at first. The traditional adaptive weighted average method (AWA) will amplify the noise in the fusion process, so the data filtered with Kalman Filter (KF) algorithm instead of with the AWA method. The proposed IAW method is compared with the AWA method and the Distributed Weighted fusion KF algorithm in the data fusion simulation to verify the superiority of the proposed algorithm. Secondly, the second simulation is conducted to verify the robustness and accuracy of the IAW algorithm. In the two experimental scenarios of sparse and dense vehicles, the vehicle detection based on image and lidar is completed, respectively. The detection data is correlated and merged through the IAW method, and the results show that the IAW method can correctly associate and fuse the data of the two sensors. Finally, the real vehicle test of object vehicle detection in different environments is carried out. The IAW method, the KF algorithm, and the Distributed Weighted fusion KF algorithm are used to complete the target vehicle detection in the real vehicle, respectively. The advantages of the two sensors can give full play, and the misdetection of the target objects can be reduced with proposed method. It has great potential in the application of object acquisition.

scholarly journals Evaluation of a plot-scale methane emission model using eddy covariance observations and footprint modelling

2014 ◽  
Vol 11 (17) ◽  
pp. 4651-4664 ◽  
Author(s):  
A. Budishchev ◽  
Y. Mi ◽  
J. van Huissteden ◽  
L. Belelli-Marchesini ◽  
G. Schaepman-Strub ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Methane Emission ◽  
Average Method ◽  
Temporal Dynamics ◽  
Weighted Average ◽  
Ambient Atmosphere ◽  
Emission Model ◽  
Closed Chamber ◽  
Weighted Average Method ◽  
Emission Models

Abstract. Most plot-scale methane emission models – of which many have been developed in the recent past – are validated using data collected with the closed-chamber technique. This method, however, suffers from a low spatial representativeness and a poor temporal resolution. Also, during a chamber-flux measurement the air within a chamber is separated from the ambient atmosphere, which negates the influence of wind on emissions. Additionally, some methane models are validated by upscaling fluxes based on the area-weighted averages of modelled fluxes, and by comparing those to the eddy covariance (EC) flux. This technique is rather inaccurate, as the area of upscaling might be different from the EC tower footprint, therefore introducing significant mismatch. In this study, we present an approach to validate plot-scale methane models with EC observations using the footprint-weighted average method. Our results show that the fluxes obtained by the footprint-weighted average method are of the same magnitude as the EC flux. More importantly, the temporal dynamics of the EC flux on a daily timescale are also captured (r2 = 0.7). In contrast, using the area-weighted average method yielded a low (r2 = 0.14) correlation with the EC measurements. This shows that the footprint-weighted average method is preferable when validating methane emission models with EC fluxes for areas with a heterogeneous and irregular vegetation pattern.

scholarly journals Efektivitas Terapi Seni Mewarnai Terhadap Depresi Pada Remaja Putri

2020 ◽  
Vol 2 (2) ◽  
pp. 109-120
Author(s):  
Sayuri Asnani
Keyword(s):  
Art Therapy ◽  
Beck Depression Inventory ◽  
Severe Depression ◽  
Study Data ◽  
Research Subject ◽  
Before And After ◽  
History Of ◽  
Depression Level ◽  
Case Study Data

This study aims to find the effectiveness of coloring art therapy against depression in a teenage girl in Yogyakarta. The hypothesis in this study is that there is a difference in the level of depression of the research subject before and after being given coloring art therapy. The level of depression after coloring art therapy was lower than before coloring art therapy. The sample in this study was a 13-year-old girl in Yogyakarta who had a history of being away from her parents and experienced moderate-severe depression. Coloring art therapy is given individually, twice, using drawing art media and markers. The subject’s depression level was measured using the Beck Depression Inventory (BDI) II scale from initial to final measurements. This study used one research subject with a single one-shot case study pre-experimental design. The data were analyzed by using visual inspection and qualitative analysis. The results of this study indicate that coloring art therapy is effective in reducing depression in young women.Abstrak. Penelitian ini bertujuan untuk mengetahui efektivitas terapi seni mewarnai terhadap depresi pada remaja putri di Yogyakarta. Hipotesis dalam penelitian ini adalah ada perbedaan tingkat depresi subjek antara sebelum diberikan terapi seni mewarnai dengan setelah terapi seni mewarnai. Tingkat depresi setelah terapi seni mewarnai lebih rendah dibanding sebelum terapi seni mewarnai.  Sampel dalam penelitian ini adalah remaja putri di Yogyakarta yang berusia 13 tahun, memiliki riwayat pernah berjauhan dari orangtua dan mengalami depresi sedang-berat. Terapi seni mewarnai ini diberikan secara individual, dua kali, menggunakan media seni gambar dan spidol. Depresi subjek diukur dengan menggunakan skala Beck Depression Inventory (BDI) II dari pengukuran awal sampai akhir. Penelitian ini menggunakan 1 subjek penelitian dengan desain pre-eksperimen single one shot case study. Data analisis dengan inspeksi visual dan analisa kualitatif. Hasil penelitian ini menunjukkan bahwa terapi seni mewarnai efektif dalam menurunkan depresi pada remaja putri.

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