1,721,004 research outputs found
Enhancement of Charging Resource Utilization of Electric Vehicle Fast Charging Station with Heterogeneous EV Users
Get PDFThis thesis presents innovative charging resource allocation and coordination strategies that maximize the limited charging resources at FCS with heterogeneous EV users. It allows opportunistic EV users (OEVs) to exploit available charging resources with dynamic event-driven charging resource allocation and coordination strategies apart from primary EV users (PEVs) (registered or scheduled EV users). Moreover, developed strategies focus on the limited charging resources that are allocated for primary/ registered EV users (PEVs) of the FCS who access the FCS with specific privileges according to prior agreements. But the available resources are not optimally utilized due to various uncertainties associated with the EV charging process such as EV mobility-related uncertainties, EVSE failures, energy price uncertainties, etc. Developed strategies consider that idle chargers and vacant space for EVs at the FCS is an opportunity for further utilizing them with OEVs using innovative charging resource coordination strategies. This thesis develops an FCS-centric performance assessment framework that evaluates the performance of developed strategies in terms of charging resource utilization, charging completion and the quality of service (QoS) aspects of EV users. To evaluate QoS of EV charging process, various parameters such as EV blockage, charging process preemptage, mean waiting time, mean charging time, availability of FCS, charging reliability, etc are derived and analyzed. In addition, the developed innovative charging resource allocation and coordination strategies with resource aggregation and demand elasticity further enhance the charging resource utilization while providing a high QoS in EV charging for both PEVs and OEVs.publishedVersio
Machine Learning Applications for Load Predictions in Electrical Energy Network
Get PDFIn this work collected operational data of typical urban and rural energy network are analysed for predictions of energy consumption, as well as for selected region of Nordpool electricity markets. The regression techniques are systematically investigated for electrical energy prediction and correlating other impacting parameters. The k-Nearest Neighbour (kNN), Random Forest (RF) and Linear Regression (LR) are analysed and evaluated both by using continuous and vertical time approach. It is observed that for 30 minutes predictions the RF Regression has the best results, shown by a mean absolute percentage error (MAPE) in the range of 1-2 %. kNN show best results for the day-ahead forecasting with MAPE of 2.61 %. The presented vertical time approach outperforms the continuous time approach. To enhance pre-processing stage, refined techniques from the domain of statistics and time series are adopted in the modelling. Reducing the dimensionality through principal components analysis improves the predictive performance of Recurrent Neural Networks (RNN). In the case of Gated Recurrent Units (GRU) networks, the results for all the seasons are improved through principal components analysis (PCA). This work also considers abnormal operation due to various instances (e.g. random effect, intrusion, abnormal operation of smart devices, cyber-threats, etc.). In the results of kNN, iforest and Local Outlier Factor (LOF) on urban area data and from rural region data, it is observed that the anomaly detection for the scenarios are different. For the rural region, most of the anomalies are observed in the latter timeline of the data concentrated in the last year of the collected data. For the urban area data, the anomalies are spread out over the entire timeline. The frequency of detected anomalies where considerably higher for the rural area load demand than for the urban area load demand. Observing from considered case scenarios, the incidents of detected anomalies are more data driven, than exceptions in the algorithms. It is observed that from the domain knowledge of smart energy systems the LOF is able to detect observations that could not have detected by visual inspection alone, in contrast to kNN and iforest. Whereas kNN and iforest excludes an upper and lower bound, the LOF is density based and separates out anomalies amidst in the data. The capability that LOF has to identify anomalies amidst the data together with the deep domain knowledge is an advantage, when detecting anomalies in smart meter data. This work has shown that the instance based models can compete with models of higher complexity, yet some methods in preprocessing (such as circular coding) does not function for an instance based learner such as k-Nearest Neighbor, and hence kNN can not option for this kind of complexity even in the feature engineering of the model. It will be interesting for the future work of electrical load forecasting to develop solution that combines a high complexity in the feature engineering and have the explainability of instance based models
Solar photovoltaic system applications: a guidebook for off-grid electrification
No full textPresenting a complete guide for the planning, design and implementation of solar PV systems for off-grid applications, this book features analysis based on the authors’ own laboratory testing as well as their in the field experiences. Incorporating the latest developments in smart-digital and control technologies into the design criteria of the PV system, this book will also focus on how to integrate newer smart design approaches and techniques for improving the efficiency, reliability and flexibility of the entire system. The design and implementation of India’s first-of its-kind Smart Mini-Grid system (SMG) at TERI premises, which involves the integration of multiple renewable energy resources (including solar PV) through smart controllers for managing the load intelligently and effectively is presented as a key case study. Maximizing reader insights into the performance of different components of solar PV systems under different operating conditions, the book will be of interest to graduate students, researchers, PV designers, planners, and practitioners working in the area of solar PV design, implementation and assessment
Techno-Economic Performance Evaluation of Photovoltaic based Micro-Grid with Energy Management Strategies
No full textThe operational performance of grid connected micro-grid system can be affected by many factors e.g. techno-economic sizing, appropriate energy management strategy, geographical locations, grid constrains and electricity energy pricing dynamics. To make renewable energy based micro-grid system more reliable as well as efficient and economically viable, it is imperative to consider a holistic approach and investigate all these factors for design and operation of the micro-grid system. In this work, techno-economic sizing of distributed generator(s) with energy storage are analyzed for operating grid connected PV based system as a micro-grid, even during the possible grid outage period. Energy management strategies have been proposed and evaluated for improving techno-economic performance of the PV based micro-grid system. Performance of the micro-grid system can be significantly improved using appropriate energy management strategies for maximizing the use of local energy resources and battery energy throughput. Impact of electricity energy pricing dynamics has been analyzed for techno-economic operation of the grid connected PV based micro-grids at the selected geographical locations (i.e. Tropical and Nordic climates). The local grid limits on the operation of the micro-grid system has been evaluated for maximizing the local energy resources utilization with consideration of peak demand and energy pricing. The regional energy pricing dynamics and local grid limits have considerable impact on performance of the PV based micro-grid. The maximum penetration of PV based micro-grid (i.e. hosting capacity study) within the distribution power network has been assessed considering the network constraints (e.g. voltage or/and loading of the power lines, etc.) and they have significant impact on PV capacity installations at different buses. The increasing penetration of PV based micro-grid system affects the voltage quality within the distribution network. The reactive power versus voltage (Q-V) droop control technique has been evaluated for managing the voltage profile within the prescribed limits. The Q-V droop function has been implemented in the PV inverter and tested its operation using the real time digital simulator and power hardware- in- loop method for improving the voltage profile within the distributed network. The presented results in this work are going to be useful for promoting the PV based micro-grid within the distribution network
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe 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
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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