186,524 research outputs found
Statistical simulation of Electric Vehicle behaviour applied to low voltage distribution network
No full textThe usage of Electric vehicles is increasing every day, and its penetration into the present electrical distribution network on large-scale needs to be investigated by the distribution companies to be future-ready and to provide good quality of electric supply. This article provides a statistical methodology to model electric vehicle charging behavior in a large network using real measurement data set. The vital information such as time of connection, duration of the connection, and power absorbed during the charging are extracted. The probability distribution of these extracted events is used to model 300 electric vehicle charging behavior whose integration with a non-synthetic low voltage European test network built using the real measurement data set is investigated for voltage distribution and the Voltage unbalance factor among the busses, feeders, and other elements present in the network. The numerical simulation framework is executed with Opendss for load flow analysis and MATLAB for statistical analysis and to invoke the load flow solver
Analyzing the Impact of Coordinated Charging of Electric Vehicles on the Power System
No full textElectric vehicle charging stations drastically affect the power quality of the distribution network. To improve power quality with greater charging station involvement and optimal use of space availability in the charging station infrastructure, it is necessary to develop new charging algorithms to optimize the use of electric resources. Coordinated charging is one of the key solutions to reduce the negative impacts of electric vehicle charging stations, which makes the charging duration similar to the connection duration. In this way, it is possible to spread the energy avoiding the peak of absorption. In contrast, the nominal power of charging is lower, with which the power quality in the network can be maintained. In this paper, an analysis is presented on distribution networks of the use of uncoordinated recharging and coordinated recharging, showing how the latter type of recharging makes it possible to significantly improve the impact of recharging on the power grid. The network considered is a medium voltage IEEE 69 bus test network
Statistical analysis of PV penetration impact on residential distribution grids
No full textThis paper presents a comprehensive approach to the probabilistic analysis of residential distribution grid injected by distributed PV sources. The approach is data-driven and is able to deal with the general scenario that includes the uncertainty of correlated PV sources and of statistically independent consumer loads. The novel method adopts a Gaussian-Mixture-Model for correctly representing PV sources correlation and a fresh probabilistic analysis technique employing Multi-Expansion polynomial chaos. Numerical experiments carried out on the Non-Synthetic European low voltage test system, highlight the importance of the comprehensive modeling strategy in order to realistically quantify uncertainty impact on the grid
Gaussian copula methodology to model photovoltaic generation uncertainty correlation in power distribution networks
No full textDeterministic load flow analyses of power grids do not include the uncertain factors that affect the network elements; hence, their predictions can be very unreliable for distribution system operators and for the decision makers who deal with the expansion planning of the power network. Adding uncertain probability parameters in the deterministic load flow is vital to capture the wide variability of the currents and voltages. This is achieved by probabilistic load flow studies. Photovoltaic systems represent a remarkable source of uncertainty in the distribution network. In this study, we used a Gaussian copula to model the uncertainty in correlated photovoltaic generators. Correlations among photovoltaic generators were also included by exploiting the Gaussian copula technique. The large sets of samples generated with a statistical method (Gaussian copula) were used as the inputs for Monte Carlo simulations. The proposed methodologies were tested on two different networks, i.e., the 13 node IEEE test feeder and the non-synthetic European low voltage test network. Node voltage uncertainty and network health, measured by the percentage voltage unbalance factor, were investigated. The importance of including correlations among photovoltaic generators is discussed
Impact Analysis of Electric Vehicle Charging Stations on the Medium Voltage Distribution Network
No full textThe distribution system is highly penetrating with the Electric Vehicle charging stations for increasing Electric Vehicle demand for a sustainable future. The impact of this large-scale integration into the distribution network at a medium voltage level has to be analyzed before dealing with the optimization problem of Electric Vehicles. This article elucidates the modeling of Electric Vehicle charging behavior using a measurement dataset whose aggregation integrated into the medium voltage network is analyzed to study their impact on the power network using probabilistic load flow simulation. The medium voltage network selected is the 69 bus test network to which Electric Vehicle aggregation is imposed as PQ load, and the voltage distribution and the voltage unbalance factor for such integration are discussed in the article at three different time windows i.e., morning, midday and evening
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
Usage Pattern of Institutional Repositories for Scholarly Communication by Academician in Maharashtra
No full textThis paper discuss the awareness and use of institutional repositories by the academicians of the selected institutions in Maharashtra based on the questionnaire response received from 584 academicians and it comprises a total response rate of 12.67% of the total population of 4611. Outcomes of the study show that majority of the users are from Arts and Humanities, Social
Sciences and Pure Science discipline prefer to publish their research in open access journals and self-archive in institutional repositories. Also found that majority of the users prefer to use Journal articles,Research papers, Theses and Dissertation and conference proceedings and a considerable percentage of users with mean value 3.88 and standard deviation 1.953 were not self-archiving in IR due to lack of knowledge about the submission process . The study recommends promotion of self-archiving by conducting seminars, workshops, and tutorials for the
academicians
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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