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(Volume: 2, Issue: 9)
Stabilize Power Grids with Optimal Placement of Phasor Measurement Unit
An unremittent and economic supply of power, without any cascading power failures, is the most important requirement for the stable and resilient operation of the grid. However, it is very cumbersome to incessantly monitor the power fluctuations of wider power grids, operating with multiple power units at various locations!!! It is at this situation the synchrophasor has emerged to help. As its name indicates, it includes units, which are specifically designed to measure the changes in the current or voltage phases at various grid locations and synchronizes them to a common time reference. It is the Phasor Measurement Unit (PMU) in the synchrophasors that does the major role of measuring the voltage or current phase changes. At this juncture, one might have numerous questions in mind. For instance, “How many PMUs are needed to be installed to measure the phase changes?”, “At which location does the PMU be installed?”, “Can the installed PMUs at distinct locations provide the maximum observability of all units in the grid?” and so on. Various researchers have addressed these issues by considering them as Multi-Criteria Decision-Making (MCDM) problem. Usually, the Optimal PMU Placement (OPP) problem involves two steps viz. (i) Obtain the sub-optimal solutions and (ii) Prune the sub-optimal solutions to identify the optimal solution. However, had the researchers strived for an optimal solution in a single shot, rather than obtaining and pruning the sub-optimal solutions? Obviously yes. A research article in the International Transactions on Electrical Energy Systems, authored by Shubhrajyoti Kundu, Mehebub Alam, Biman K. Saha Roy and Siddhartha Sankar Thakur, has dealt with this aspect. The researchers have employed the Preference Ranking Organization Method for Enrichment of Evaluation (PROMETHEE)-based MCDM technique to solve the OPP problem. As per the researchers, PROMETHEE has been firstly applied to the OPP problem. The researchers have also confirmed the effectiveness of their approach in solving the OPP problem at a single shot using benchmark datasets like, IEEE- 14, IEEE-30, IEEE- 57 and IEEE- 118 bus test systems. Additionally, the researchers have tested their approach using the Indian practical NRPG 246-bus system and the larger Polish 2383-bus system. “Some advanced criteria have been developed utilizing the concept of graph theory to find the optimal PMU location. Selected criteria and the PROMETHEE-based proposed MCDM approach not only determine the minimum number of PMUs for complete system observability, but also try to achieve maximum measurement redundancy in the process”, the researcher’s say. However, the International Energy Agency (IEA) claims that the smart grid investments need to be doubled by 2030 to meet the goal of Net Zero Emission by 2050. Hence, large- scale grids will be more common in the future that the upcoming researchers have a great scope in contributing towards grid allocation strategies and methods in power generation and distribution. Image Courtesy: www.vecteezy.com
Nanophosphor Synthesis and Property Investigation- A Machine Learning Perspective
Have you ever heard the term ‘nanophosphor’? It is a luminescence- exhibiting nanomaterial, upon the excitation by light or electrons. It is this attribute that makes the nanophosphor to be used for solid- state lighting, display technologies, medical diagnostics, solar energy conversion in photovoltaic cells and many other light-based applications. Numerous researchers have worked upon creating nanophosphors for Light Emitting Diode (LED)- based applications, so as to offer white lights of longer wavelengths or better Color Rendering Index (CRI) with decreased heat dissipation properties. One such was the SrAl2O4:Eu2+ nanophosphor, being synthesized using the urea fuel combustion method by Praveen Kumar Litoriya, Swati Kurmi and Ashish Verma of Dr. Harisingh Gour Vishwavidyalaya (A Central University), Madhya Pradesh, India. The researchers’ investigation on that nanophosphor’s structural, optical, morphological, photoluminescence and antimicrobial properties confirm that the synthesized nanophosphor had zero microbes and suits-well for the green LED and other optoelectronic devices. However, making these manual investigations is highly cumbersome. Can machine learning render hands in any ways? Why not? (i) It can aid in optimally choosing the color temperature or CRI of the lighting systems or (ii) It can allow the development of energy-efficient, smart-lighting systems and aid in their predictive maintenance. However, the user preferences, the environmental conditions, the duration of LED usage and the emitted spectrum needs to be carefully observed, while making predictions. Not only that, the design and the geometry of the nanophosphors too could be chosen optimally. The reason is that nanophosphors of varying sizes exhibit distinct light-emission proper ties and comply with distinct applications. Unfortunately, only few past researches have been reported to apply machine learning approaches on nanophosphor synthesis or their utilization in varied applications. Hence, there is a great scope for the upcoming researchers in this machine learning domain. The only consideration is that the researchers have to validate the truthfulness of their findings with the laboratory test-based outcomes, which in the longer run can render process automation. Image courtesy: www.freepik.com
High Power Applications Demand Cost- Effective and Efficiency- Enhanced Multi- Level Inverters
Most power systems or grids of these days rely on the conversion from Direct Current (DC) to Alternating Current (AC) by the multi- level inverters. In fact, the multi-level inverters have a significant role in various applications, as in: (i) Power unit integration in the grid that encompasses both renewable and non-renewable energy systems, operating with low, medium or high power, (ii) DC to AC power conversion from battery or other energy storage systems for utilization in AC devices, (iii) Seamless transmission and distribution of power over long distances, (iv) Better voltage and frequency control in high- power applications like, High-Voltage Direct Current (HVDC) transmission and (v) Driving high- power electric motors in commercial/ industrial applications and electric vehicles. So, what makes the multi-level inverters to be largely used than the traditional two- level inverters? It is their ability to generate less harmonically-distorted and near- ideal sinusoidal waveforms of improved power quality and reduced power losses. Indeed, such a waveform is generated using multiple DC voltage levels, being achieved through different arrangement of switches and energy storage elements like, diodes and capacitors, respectively. A few commonly used topologies include the diode-clamped, the capacitor-clamped, the cascaded H-bridge and the hybrid multi-level inverters. However, numerous research questions arise in this context and they are: What number of diodes or switches are needed to yield a desired power quality or efficiency? Which topology suits the application at hand? Can a novel, optimal and cost-efficient topology be proposed to achieve enhanced efficiency and electromagnetic compatibility? How to effectively handle the heat dissipation and achieve excellent DC- link utilization? Hence, research becomes mandate in this domain. V. Aishwarya and K. Gnana Sheela of APJ Abdul Kalam Technological University, Trivandrum, India, have suggested a three-phase Extendable-Level Inverter (ELI) with fewer switches and enhanced DC-link utilization. They have also investigated the power losses and the efficiency from the same inverter using the Modified Sinusoidal Pulse Width Modulation (MSPWM). As per their findings, the three- phase ELI imparted minimal switching and conduction power losses. However, the researchers state that their inverter was limited to low and medium voltages, requiring wide bandgap devices or step- up transformers to handle high voltage applications. Hence, future researchers can aim at finding highly-efficient and cost-effective multi-level inverters for use in high- power applications. Image courtesy: www.freepik.com
Intelligent Robots for Hospitality Management and Tourism
It is not an amazing fact to foresee the robotic technology to ubiquitously master almost all fields like, military, healthcare, manufacturing industries, households, hospitality management and education sectors in future. In fact, the global stock of the operational robots has already been 3.5 million units by the initial months of 2023, as per the International Federation of Robotics reports. It is the advent of Artificial Intelligence (AI) and Machine Learning (ML) approaches, the incorporation of energy-efficient and safer technologies within the robot, the easy to program/use nature and the reduction of human workloads, which have greatly assisted in this growing utilization of robots. To be more specific, in recent years, research on employing human robots in the field of hospitality management and tourism has acquired greater attention. Dr. Ajeet Kumar Singh and Mandeep Singh from the School of Hotel Management and Catering Technology, Jaipur National University, Rajasthan, India, too have individually shown interest towards this notion. In their research in the International Journal for Multidimensional Research Perspectives, the researchers’ view was that the robot utilization in the hotel industry can improve guest services and assistance, room service and delivery, housekeeping and maintenance, and efficient inventory management in an efficient, contactless, hygienic and secure manner. However, the researchers also state that there are few limitations in the current research like: (i) Simulations with different software have only been highly- concentrated than real- world implementation; (ii) The user’s acceptance and adaptation to robotic technology has been less- regarded, (iii) Research is not more generalized or at times, it might be more application- specific and (iv) Human- robot collaboration must come up with improved loyalty and satisfaction with higher assurance on privacy and ethical concerns. Hence, the research on developing highly intelligent robots with consideration on the limitations of current research has a great scope in the future.
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Heading Towards Agricultural Mechanization
Improved crop yield is what the agriculture sector is aimed at. Though human power and animal power were combinedly used those days for crop plantation, maintenance, cutting, storage and processing, the growing population demands farm mechanization using machineries, which work on mechanical, electrical or renewable power, to meet the growing food demands. With farm mechanization, the crops can be timely planted or watered to render high crop productivity and to assure good returns for the farmers. Though it sounds easy, the success of agricultural mechanization revolves around the feasibility of achieving few key components such as: (i) Hiring service transactions; (ii) Mechanization clusters and (iii) Land consolidation. Indeed, these components have a major role in uplifting the agricultural community, especially in the developing and under-developing nations of the world. With the hiring of service transactions, the farmers can rent or lease agricultural machineries or equipment, safeguarding them from huge buying and maintenance costs of the machineries. In contrast, the mechanization clusters allow the farms or the agricultural operations to collectively access and share the agricultural machinery or resources. Finally, land consolidation allows larger agricultural plots to be formed by rearranging the smaller land holdings from individual farm owners. However, all these factors cannot be met altogether because of the costs, coordination and the social or legal issues, which arise during agricultural mechanization. Yared Deribe Tefera and Bisrat Getnet Aweke from the Ethiopian Institute of Agricultural Research have intended to analyse the heterogeneity of mechanization service transactions, the factors influencing the farmers’ coordination in mechanization clusters and the readiness to agree for land consolidation. Conducting a cross-sectional survey of producer households in the major crop production areas of Oromia, SNNPR, Amhara and Tigray regions in Ethiopia, the researchers have found cluster farming to be advantageous against diseconomies, rationalized by upgrading the mechanization scale. Additionally, in their article in the Journal of Agribusiness in Developing and Emerging Economies, they have found that mechanization clusters and land consolidation were affected by household, land, crop, mechanization service, remoteness and location-related factors. However, proper coordination between the participants has to be met based on their demands, so that the costs can be greatly cut down and the mechanization resources can be made available, even to remote areas. Hence, as a researcher, one can contribute to the following aspects of agriculture mechanization: (i) Develop machineries of low costs, which can operate with clean, sustainable and renewable energy; (ii) Develop approaches for soil health and crop health monitoring; (iii) Develop approaches to assist the farmers in predicting the market as well as the crop prices; (iv) Develop approaches for planning the period of machinery usage and their maintenance, so as to build coordination and (iv) Render methods for the optimal planning of land consolidation, so as to avail easy service transactions, improve irrigational and other infrastructures, and to increase the crop productivity.
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