Blog – ENTAIL

Jul182021 by adminNo Comments

Article “Optimal Design of Distribution Overhead Powerlines using Genetic Algorithms” was accepted for publication in IEEE Transactions on Power Delivery

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Article "Optimal Design of Distribution Overhead Powerlines using Genetic Algorithms" was accepted for publication in IEEE Transactions on Power Delivery. Congratulations, Graeme! Abstract: As the design of distribution overhead power lines becomes increasingly standardized in the 21st century, the reduced search space of its design parameters allows for increasing opportunities to automate the design process. It involves specifying the distribution utility pole heights and classes, pole-top attachments, and conductor span tensions. A successful algorithm must be able of generating designs that are compliant with applicable codes and utility standards, achieve construction labour and material costs that are commensurate to that of a human-created design, and require a reasonable computation time. A design automation algorithm is created for ATCO Electricity, Alberta, Canada. Based on provided requirements and constraints, it uses the…

Jul42021 by adminNo Comments

Article “Dimension-wise Particle Swarm Optimization: Evaluation and Comparative Analysis” was published in MDPI Applied Sciences

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Article "Dimension-wise Particle Swarm Optimization: Evaluation and Comparative Analysis" was published in MDPI Applied Sciences. Congratulations, Justin! Abstract: his article evaluates a recently introduced algorithm that adjusts each dimension in particle swarm optimization semi-independently and compares it with the traditional particle swarm optimization. In addition, the comparison is extended to differential evolution and genetic algorithm. This presented comparative study provides a clear exposition of the effects introduced by the proposed algorithm. Performance of all evaluated optimizers is evaluated based on how well they perform in finding the global minima of 24 multi-dimensional benchmark functions, each having 7, 14, or 21 dimensions. Each algorithm is put through a session of self-tuning with 100 iterations to ensure convergence of their respective optimization parameters. The results confirm that the new variant is a…

Jun192021 by adminNo Comments

Article “Distributed Learning Applications in Power Systems: Methods, Gaps, and Challenges” has been published in MDPI Energies

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Article "Distributed Learning Applications in Power Systems: Methods, Gaps, and Challenges" has been published in MDPI Energies. Congratulations, Nastaran! Abstract: In recent years, machine learning methods have found numerous applications in power systems for load forecasting, voltage control, power quality monitoring, anomaly detection, etc. Distributed learning is a subfield of machine learning and a descendant of the multi-agent systems field. Distributed learning is a collaboratively decentralized machine learning algorithm designed to handle large data sizes, solve complex learning problems, and increase privacy. Moreover, it can reduce the risk of a single point of failure compared to fully centralized approaches and lower the bandwidth and central storage requirements. This paper introduces three existing distributed learning frameworks and reviews the applications that have been proposed for them in power systems so far.…

Jun112021 by adminNo Comments

Article “Probabilistic Forecasting of Dynamic Thermal Line Rating with Temporal Correlations” was accepted to the International Journal of Electrical Power and Energy Systems

Articles

Article "Probabilistic Forecasting of Dynamic Thermal Line Rating with Temporal Correlations" was accepted to the International Journal of Electrical Power and Energy Systems. Congratulations Tomas! Abstract: Dynamic Thermal Line Rating is a technology that optimizes the utility of overhead power transmission lines by dynamically adjusting the rating according to current ambient conditions. It is often applied in discrete time intervals (i.e., the rating is updated hourly or daily) based on a rating forecast for the next period. This paper examines the effects of temporal discretization on rating prediction, discusses the importance of temporal correlations, and proposes an approach to include these correlations in a rating prediction system. It demonstrates that predictions may be biased towards extreme values if temporal correlation is not taken into account. The proposed solution to this…

May312021 by adminNo Comments

Article “Comparative Analysis of Machine Learning ‎Techniques for Temperature Compensation in ‎Microwave Sensors” was accepted for publication in IEEE Transactions on Microwave Theory and Techniques

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Nazli's article "Comparative Analysis of Machine Learning ‎Techniques for Temperature Compensation in ‎Microwave Sensors" was accepted for publication in IEEE Transactions on Microwave Theory and Techniques. Congratulations! Abstract: The planar nature of microwave sensors leaves them vulnerable to ambient temperature changes with potential impact on the perception of the material under test. A temperature compensation technique is required to consider its direct effect on the dielectric property of materials. In this article, machine learning algorithms are employed in two configurations of classifier and regressor on frequency response of a split-ring resonator operating at 1.19 GHz. A wide range of dielectric constant is covered with concentrations of [0:20%:100%]-methanol/acetone in water with a temperature cycle of 25 °C-50 °C. This broad variety of cases captures the complicacy of entangled trends that are…

May282021 by adminNo Comments

Article “A High-Resolution Reflective Microwave Planar Sensor for Sensing of Vanadium Electrolyte” has been accepted to MDPI Sensors

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Article "A High-Resolution Reflective Microwave Planar Sensor for Sensing of Vanadium Electrolyte" has been accepted to MDPI Sensors. Congratulations, Nazli and Kalvin! Abstract: Microwave planar sensors employ conventional passive complementary split-ring resonators (CSRR) as their sensitive region. In this work, a novel planar reflective sensor is introduced that deploys CSRRs as the front-end sensing element at fres=6 GHz with an extra loss-compensating negative resistance that restores the dissipated power in the sensor that is used in dielectric material characterization. It is shown that the S11 notch of −15 dB can be improved down to −40 dB without loss of sensitivity. An application of this design is shown in discriminating different states of vanadium redox solutions with highly lossy conditions of fully charged V5+ and fully discharged V4+ electrolytes.

Apr212021 by adminNo Comments

Article “Distributed Optimization for Distribution Grids With Stochastic DER Using Multi-Agent Deep Reinforcement Learning” was accepted to IEEE Access

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Mohammed's article "Distributed Optimization for Distribution Grids With Stochastic DER Using Multi-Agent Deep Reinforcement Learning" was accepted for publication in to IEEE Access open access journal. Congratulations! Abstract: This article develops a special decomposition methodology for the traditional optimal power flow which facilitates optimal integration of stochastic distributed energy resources in power distribution systems. The resulting distributed optimal power flow algorithm reduces the computational complexity of the conventional linear programming approach while avoiding the challenges associated with the stochastic nature of the energy resources and loads. It does so using machine learning algorithms employed for two crucial tasks. First, two proposed algorithms, Dynamic Distributed Multi-Microgrid and Monte Carlo Tree Search based Reinforcement Learning, constitute dynamic microgrids of network nodes to confirm the electric power transaction optimality. Second, the optimal distributed…

Mar122021 by adminNo Comments

Article “A Comprehensive Review of Blockchain Consensus Mechanisms” accepted for publication in IEEE Access

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Bahareh’s paper "Comprehensive Review of Blockchain Consensus Mechanisms" was accepted for publication in IEEE Access open access journal. Congratulations! Abstract: Since the advent of distributed ledger technologies, they have provided diverse opportunities in a wide range of application domains. This article brings a comprehensive review of the fundamentals of distributed ledger and its variants. Analyzing 185 publications, ranging from academic journals to industry websites, it provides a comparative analysis of 130 consensus algorithms using a novel architectural classification. The distribution of the reviewed algorithms is analyzed in terms of the proposed classification and different application domains, along with the applicability of each class among the top 10 platforms in the most prominent blockchain application domains. Additional conclusions are drawn from the evolution of consensus mechanisms, and the analysis concludes envisaging…

Feb232021 by adminNo Comments

So you are interested in joining my research group?

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If you sent me an email expressing interest to join my research group, you will not receive a personalized detailed response. If I have time to respond at all (not guaranteed), you will receive a template email that may have brought you to this post. The reason is that your email is not the only supervision request I have received. In fact, I receive an average of 1,000-2,000 such emails every year. Compare this number with the 1-3 new students I can admit in the same period, and you will see that I cannot spend one week (assuming about 5 minutes per message) every year answering all such emails. However, it is possible that you may be a good match for our research group and we may work well together.…

Dec212020 by adminNo Comments

A Temperature-Compensated High-Resolution Microwave Sensor Using ANN

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Nazli Kazemi, an ECE doctoral student, has published an article on her work titled 'A Temperature-Compensated High-Resolution Microwave Sensor Using Artificial Neural Network' with supervisor Petr Musilek in IEEE Microwave and Wireless Components Letters. In this study, they develop and train an artificial neural network (ANN) to model the behavior of the microwave sensor and to eliminate the uncertainty caused by uncontrolled temperature variations on the sensor response. You can access the article here: https://lnkd.in/ggBHG6w Nazli had originally started working on this project as an M.Sc. student under the guidance of Mojgan Daneshmand, before Mojgan's tragic and untimely passing in January this year. This article is dedicated to Mojgan's memory and her commitment to support and uplift women in STEM. An in memorium article about Mojgan and her family is available here: https://lnkd.in/gc83Kqi