EAI Endorsed Transactions on Energy Web https://publications.eai.eu/index.php/ew <p>EAI Endorsed Transactions on Energy Web is an open access, peer-reviewed scholarly journal focused on cross-section topics related to IT and Energy. The journal publishes research articles, review articles, commentaries, editorials, technical articles, and short communications with a bi-monthly frequency (six issues per year). Authors are not charged for article submission and processing.</p> en-US <p>This is an open-access article distributed under the terms of the Creative Commons Attribution <a href="https://creativecommons.org/licenses/by/3.0/" target="_blank" rel="noopener">CC BY 3.0</a> license, which permits unlimited use, distribution, and reproduction in any medium so long as the original work is properly cited.</p> publications@eai.eu (EAI Publications Department) support@eai.eu (EAI Support) Thu, 29 Dec 2022 12:47:24 +0000 OJS 3.3.0.13 http://blogs.law.harvard.edu/tech/rss 60 Sensors and Simulations for Transport Resilience https://publications.eai.eu/index.php/ew/article/view/1946 <p>With the aim of enhancing resilience, the need for method of its measurement arises. To apply the method, resilience indicators must be identified and collected. In this paper we deal with questions of acquisition of indicators, needed to assess resilience of the transport system of the city. More specifically, we will look at the sensors and simulation and their possibilities in this task. That is why the first part of the paper will start with introduction of the Laboratory of Simulation and Modelling of Crisis Phenomena in Transport, and of the simulation program VR®Forces, that we plan to use for application of this paper´s outcomes and for further research of resilience. In second part of this article, we will briefly guide the reader through our view on resilience with focus on transport system of the city. Next, we will move to identification of transport resilience indicators, that could be obtained by the use of sensors within the traffic network and its vehicles or devices, and also indicators, that we can obtain by the use of simulation. Identification of sensors, usable for this task will follow. Finally, the possible use of modelling and simulation in collection of resilience indicators will be explained.</p> M. Lacinák, J. Ristvej, M. Jánošíková Copyright (c) 2022 EAI Endorsed Transactions on Energy Web https://creativecommons.org/licenses/by/3.0/ https://publications.eai.eu/index.php/ew/article/view/1946 Wed, 13 Jul 2022 00:00:00 +0000 Power Quality Improvement using Parallel Connected FACTS Device with Simplified d-q Control https://publications.eai.eu/index.php/ew/article/view/2139 <p>INTRODUCTION: Distribution network is mainly affected by the end user load nature. Ruinous influence on power system operation based on the type of load used by the end user and due to the presence of non-linear loads causes Harmonics in power system. The concept of reducing the harmful effect of harmonics on power system attracted the research attentiveness.</p><p>OBJECTIVES: To reduce these harmonics and reactive power problems FACTS devices are found reliable. Out of various FACTS devices, Active Power Filter (APF) is one FACTS device which identifies and controls the harmonic contamination in power system with non-linear loads. This work mainly presents a parallel APF concept for the compensation of harmonics to improve the reliability of the system.</p><p>METHODS: The main contribution of this work is proposal of single control strategy for compensation of Power quality. Corrective back currents (for parallel APF) to compensate the identified harmonics are generated using modified d-q reference-based control methodology.</p><p>RESULTS: The models are developed, and analysis is presented using MATLAB/SIMULINK software</p><p>CONCLUSION: d-q reference theory control strategy is explained in detail. Load current, Source Voltage and DC link voltage which are measured using various sensors and send to processor. modified d-q reference the signals to be measured are same</p> N. Rajesh, M. Venu Gopala Rao, R. Srinivasa Rao Copyright (c) 2022 EAI Endorsed Transactions on Energy Web https://creativecommons.org/licenses/by/3.0/ https://publications.eai.eu/index.php/ew/article/view/2139 Mon, 25 Jul 2022 00:00:00 +0000 A Sustainability-focused Project-based Learning Experience for Engineering Undergraduates: Case Study of a Smart Greenhouse Project https://publications.eai.eu/index.php/ew/article/view/2192 <p>In this paper, a smart greenhouse project has been presented as an example of a sustainability-focused project-based learning experience for undergraduates. While project-based instruction and learning experience has already gained enough momentum in several fields of education, the inclusion of sustainability perspectives from the science and engineering fields of studies is yet to make its room in the current course curricula as well as in the mindset of new generations of engineering undergraduates. This smart greenhouse project is an example of how sustainability can be brought into a classroom setting of engineering and technology programs as a project-based learning experience. The objective of this smart greenhouse project is to create an automated system capable of growing vegetation with little human input by utilizing electricity, computer programming, and a microcontroller operation. While this project was implemented by a group of two students with electrical engineering technology (EET) major as parts of their Introduction to Programming (ET 142) and Supervisory Control and Data Acquisition (ET 342) courses requirements at the University of Wisconsin-Green Bay, Wisconsin, USA, a similar sustainability-focused project-based learning approach can also be applied successfully in other courses at different levels of engineering and technology programs at other academic institutions.</p> Rick Todd Kaske Jr, Brady Connaher, Mohammad Upal Mahfuz Copyright (c) 2022 EAI Endorsed Transactions on Energy Web https://creativecommons.org/licenses/by/3.0/ https://publications.eai.eu/index.php/ew/article/view/2192 Wed, 27 Jul 2022 00:00:00 +0000 Adaptive FPA Algorithm based OPF with Unified Power Flow Controller https://publications.eai.eu/index.php/ew/article/view/150 <p class="ICST-abstracttext"><span lang="EN-GB">In this work a novel modified flower pollination algorithm has been developed to solve the problem of single and multi-objective Optimal Power Flow operations for Unified power Flow Controller in Flexible Alternating Current Transmission Systems. In the proposed Adaptive Flower Pollination Algorithm the best initial solution can be chosen from the fittest and also the weights are adaptively adjusted to get better convergence characteristics. The nature of the objective functions is non-linear and difficult to get best possible solutions within the boundary conditions of total power demand. The weak nodes are determined in the system to locate the UPFC with Fuzzy approach considering input parameters as L-Index and voltage magnitudes. The projected method is validated using IEEE-30 and IEEE-57 bus systems for three objective functions, namely, system real power loss minimization, fuel cost minimization and the combination of total generating cost and system real power loss. Results of Fuzzy- Adaptive Flower Pollination Algorithm based OPF optimization for UPFC produced optimum results for the considered objectives of total fuel cost, real power loss and for the multiobjective.</span></p> Immanuel A., Challa Babu, Sudheer P., Pavan Kumar Naidu R., Nageswara Rao Atyam Copyright (c) 2022 EAI Endorsed Transactions on Energy Web https://creativecommons.org/licenses/by/3.0/ https://publications.eai.eu/index.php/ew/article/view/150 Wed, 12 Oct 2022 00:00:00 +0000 Static Voltage Stability Assessment of Ethiopian power System Using Normalized Active Power Margin Index https://publications.eai.eu/index.php/ew/article/view/141 <div><p class="ICST-abstracttext"><span lang="EN-GB">Voltage stability assessments, made so far on the Ethiopian electric power system (EEP), are limited both in number and in methodology. Here, in this paper the static voltage stability of the Ethiopian power system is investigated using an index called normalized active power margin. The methodology starts from determining Thevenin equivalent of a system as viewed from the load buses. The Thevenin equivalent parameters help to determine the load bus maximum active power transfer limit and to draw the PV relation curves. The approach avoids the time-consuming method of PV curve based maximum active power transfer determination, which requires large number of power flow computations. The resulting maximum active power transfer and current operating active power load are used for the index calculation. </span><span lang="EN-GB">The index is tested using IEEE 30 bus system and produced results matching with other previously established indices. The index is capable of ranking vulnerability of load buses to voltage instability.</span> <span lang="EN-GB">Then, scenarios of heavy load and light</span><span lang="EN-GB"> load EEP cases, with and without system reactive power compensation, are investigated. Results reveal weakest buses are supplied from 66kV transmission lines, load bus 232 being the weakest of all. On the other hand, the most stable buses are supplied from 132 kV transmission lines, bus 149 being the most stable bus. PV curves drawn, also, reveal the improvement that come with reactive power compensation and with operating in light load condition.</span></p></div> Ahadu Hilawie, Fekadu Shewarega Copyright (c) 2022 EAI Endorsed Transactions on Energy Web https://creativecommons.org/licenses/by/3.0/ https://publications.eai.eu/index.php/ew/article/view/141 Thu, 15 Dec 2022 00:00:00 +0000 A Hybrid Framework for Visual Positioning: Combining Convolutional Neural Networks with Ontologies https://publications.eai.eu/index.php/ew/article/view/2959 <div><p class="ICST-abstracttext"><span lang="EN-GB">Visual positioning is a new generation positioning technique which has been developed rapidly during recent years for many applications such as robotics, self-driving vehicles and positioning for visually impaired people due to advent of powerful image processing methods, especially Convolutional Neural Networks. Nowadays, deep Convolutional Neural Networks are capable of classifying images with high accuracy rates; however, comparing visual perception by a human being, pure Neural Networks lack background knowledge which is essential for estimating the position through a reasoning process. In this paper we present a hybrid framework for employing ontologies over Convolutional Neural Networks to integrate a knowledge-based reasoning with Neural Networks for taking advantages of capabilities similar to human brain’s functions. The proposed framework is generic so it can be applied to a wide variety of scenarios in smart cities where visual positioning represents added value.</span></p></div> Abdolreza Mosaddegh, Sérgio Lopes, Habib Rostami, Ahmad Keshavarz, Sara Paiva Copyright (c) 2022 EAI Endorsed Transactions on Energy Web https://creativecommons.org/licenses/by/3.0/ https://publications.eai.eu/index.php/ew/article/view/2959 Thu, 29 Dec 2022 00:00:00 +0000