Better Use Of Energy Research Articles

Smart Grid Management Enhanced by IoT Device Integration to Improve Energy Efficiency and System Reliability

As a potential way to improve energy economy and system stability, putting Internet of Things (IoT) devices into smart grid control has become clear. This study looks at the full effects of adding IoT devices to smart grid control, focusing on the good and bad things that might happen. The smart grid is an updated electricity grid that uses digital communication technologies to track and manage power flows. This makes energy supply more efficient, reliable, and long-lasting. The standard smart grid, on the other hand, has problems like not being able to see how the grid works, using energy inefficiently, and being easy to disrupt. IoT devices offer an answer by giving real-time information on how well the grid is working, which allows for proactive repair and improvement. A mixed-methods approach was used for this study, which includes both quantitative analysis of data on energy use and qualitative conversations with experts in the field. Machine learning techniques are used to predict how much energy IoT devices in a testbed smart grid will use. This lets us look closely at how adding IoT devices affects system stability and energy efficiency. The study finds that incorporating IoT devices into smart grid control greatly enhances energy economy, resulting in an average 15% drop in energy use. IoT devices also make systems more reliable by letting you see how the grid is doing in real time and responding quickly to problems. The results show that adding IoT devices could change how smart grids are managed, letting companies make better use of energy, make systems more reliable, and improve grid performance overall. But problems like data protection and communication still exist, which shows that this area needs more study and development.

Enhancing Energy Efficiency in Electrical Systems with Reinforcement Learning Algorithms

Improving the energy efficiency of electricity systems is important for lowering environmental damage and promoting sustainable growth. In recent years, reinforcement learning (RL) methods have become useful for finding the best ways to use energy in many areas. The point of this study is to look into how RL algorithms can be used to make electricity systems more energy efficient. The study looks into how RL algorithms can be used to make electricity systems more efficient by lowering waste, making the best use of energy, and maximizing energy use. The study suggests a new way to use RL methods to change things like power sharing, load scheduling, and resource allocation on the fly in order to keep system performance high while using as little energy as possible. Some important parts of the study method are creating RL models that work with electricity systems and their limitations, as well as coming up with the right payment functions to help people learn how to behave in ways that use less energy. Extensive models and real-world studies on sample electrical systems are used to test how well the suggested method works. According to the study's results, using RL algorithms can lead to big changes in how efficiently energy is used, with cuts in energy use running from [insert exact number range]. The study also shows how flexible and scalable RL-based solutions are when it comes to different system setups and operating scenarios. Overall, this study adds to the growing amount of research on energy efficiency by showing how RL algorithms can be used to solve difficult problems in electrical systems. Practical plans can be made to improve energy efficiency and promote sustainability in a wide range of businesses and uses based on what this study has taught us.

Hybrid Energy Regulated Constant Gain Kalman-Filter for Optimized Target Detection and Tracking in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are one of the most researched areas worldwide as the wide-scale networks possess low cost, are small in size, consume low power, and can be deployed in various environments. Among various applications of WSNs, target tracking is a highly demanding and broadly investigated application of wireless sensor networks. The parameter of accurate tracking is restricted because of the limited resources present in the wireless sensor networks, noise of the network, environmental factors, and faulty sensor nodes. Our work aims to enhance the accuracy of the tracking process as well as energy utilization by combing the mechanism of clustering with the prediction. Here, we present a hybrid energy-regulated constant gain Kalman filter-based target detection and tracking method, which is an algorithm to make the best use of energy and enhance precision in tracking. Our proposed algorithm is compared with the existing approaches where it is observed that the proposed technique possesses efficient energy utilization by decreasing the transference of unimportant data within the sensor network, achieving accurate results.

The Secure and Energy Efficient Data Routing in the IoT Based Networks

Over the course of the last few years, a great number of studies have been carried out in the field of IoT. It has been found that there is an issue with the performance of the secure data transmission that takes place between sensor nodes and IoT devices. There is an urgent need for inventive strategies that can increase the amount of data that can be sent. In addition to this, a strategy that makes better use of energy should be put into action as soon as possible. Research is now looking at both IoT and a deep learning approach as part of the preparation for the next set of activities. In addition to the energy consumptions, there are a number of other aspects that have the ability to impact both the performance and the throughput of the work that is now being provided. A few examples of these considerations include the geographical distance, the rate of motion of the sensor nodes, and the calibre of the transmission devices. Make a recommendation for a method that can combine data compression with machine learning in order to develop a system that is both efficient in terms of energy consumption and has a high throughput. There is now research being conducted on IoT-based systems to study their degree of performance and safety, in addition to the amount of energy they save while routing data.

Data Preprocessing for Vibration Analysis: Application in Indirect Monitoring of ‘Ship Centrifuge Lube Oil Separation Systems’

Air quality can be affected by merchant ships, so it is important to regulate emissions that are produced, as well as to use energy efficiently. In this sense, the cleanliness of the oil used in lubrication is essential to achieve a better use of energy and reduce losses in marine engines. For that, it is vital to carry out good maintenance strategies. Therefore, it is important to develop techniques that allow condition monitoring during engine operation. In order to detect potential problems as soon as possible, it is common to analyze vibratory signals, since sustainable changes in the rotating frequency and its harmonics can be detected, which was the objective of this work, by analyzing the time-frequency domain using wavelet packet transform. A methodology to select the optimal function (mother wavelet) and the best patterns to monitor, in order to determine the state of the purifiers of the marine lube oils, was carried out, including intelligent classification systems. Specifically, this document considers centrifugal oil lubricant separators systems, since the monitoring of these systems can determine the condition of different mechanical systems.

Heat storage design and performance analysis of a parabolic trough thermal power generation system based on sectional heating collection

The integration of solar thermal utilization and energy cascade utilization can bring the possibility to increase the overall plant efficiency by decreasing the exergy loss while maintain a firm supply. This paper takes SEGS VI Plant and its improved plant using sectional heating as research object, two novel thermal energy storage subsystem structures were proposed and designed for the improved plant, to explore the enhancing effect of energy cascade utilization on commercial solar thermal power plants. Calculation models of the energy storage efficiency and collector field multiples of the thermal energy storage tank were established. This paper used the software Ebsilon to establish the simulation model of the commercial 30 MW solar thermal power plant with traditional thermal energy storage structure, the improved plants with two different thermal energy storage structures, and conducted the performance analysis of the plants under design and operating conditions. The results show that, compared with the system using traditional thermal energy storage structure, the overall plant efficiency of the improved plant adopt the novel thermal energy storage structure increased by 0.71% and 0.95% under design conditions day, the overall plant efficiency increased by 0.60% and 0.81% under operating conditions, which can realize the better use of energy. Simultaneously, the total capital investment cost and levelized cost of electricity also can be reduced by 6.77 M$ and 4c$/kWh, which has good application prospects.

Energy efficiency measures and technical-economic study of a photovoltaic self-consumption installation at ENSA Kenitra, Morocco

Abstract The increase in energy demand, increasingly expensive and part of a sustainable development approach, has highlighted the importance of energy efficiency. Indeed, opting for energy efficiency allows to fight against the dissipation of energy and its costs by means of an optimization in the use of energy sources. It is in this sense, that several countries including Morocco, and in order to reduce its energy bill, has opted for a national strategy of energy efficiency which aims to achieve an energy saving of about 20% by 2030 through a better use of energy in all areas of economic and social activity. The integration of energy efficiency and renewable energy techniques in the construction sector is one of the levers that will enable the country to meet its energy challenges and achieve its objectives in the fight against climate change. In this context, Ibn Tofail University has started to exploit the interesting potential of this energy efficiency campus wide. Our addresses the problem of increasing electricity bills at the National School of Applied Sciences of Kenitra (ENSAK) while seeking to develop long-term solutions for the resolution of this problem as well as opening up promising prospects that will better meet its needs. In order to minimize energy consumption at the National School of Applied Sciences, we studied the different types photovoltaic installations and elaborated a study of technical feasibility, financial profitability and environmental impact of potential self-consumption photovoltaic installations.

Evaluation of dual crude palm and kernel oil production in North Colombia via computer-aided exergy analysis

Palm production chains in Colombia have some unsatisfied demands that affect their competitiveness. Specific demands include efficiency in energy use. Therefore, in the present report, an exergy analysis for the dual crude palm and kernel oil production process was carried out to determine the main energy sinks and suggest technological improvements that allow better use of energy. For this study, the process was initially simulated in the Aspen Plus ® software, where the chemical and physical exergies of the species and streams involved were quantified. The process irreversibilities, the exergy loss, the exergy of waste, and the exergy of utilities were calculated for each stage and the whole process. An overall exergy efficiency of 18% was achieved, while the highest process irreversibilities contribution was due to the destroyed exergy with the waste in the threshing stage. To increasing the global exergy efficiency of dual crude palm and kernel oil production, it is proposed the evaluation of palm rachis use to obtain biofuels and/or high-value products.

Future directions of material chemistry and energy chemistry

Abstract Energy is an important substantial foundation for the survival and development of humans. However, the over-consumption of resources and environmental pollution have become more prominent. The key factors for solving energy problems are to increase energy utilization efficiency and optimize energy structure. The development of new materials is the research emphasis in the field of material chemistry all the time. For instance, developing new light-capture materials and catalysts to improve the efficiency of existing photovoltaic cells is one of the most effective approaches to increasing solar power capacity radically. The design of high-performance catalytic materials to make better use of energy from fossil fuels and biomass. In addition, it is an important research direction of material chemistry and energy chemistry to deeply understand the reaction mechanism of energy conversion.

Design and experimental analysis of an improved burner with natural gas

This research aimed to improve the thermal performance of industrial cookstoves using natural gas in Metropolitan Lima to promote good use of energy and reduce the impacts of climate change. The methodology was to use an appropriate test bench under the international standards of fuel gases; the appropriate instrumentation was used to record the variables such as temperature, pressure, mass flow, and relative air humidity. The burner was installed in the prototype cookstove and test bench to perform the experimental part. After that, the powers and performances of several industrial cookstoves in the Peruvian market were determined for comparison with the design of the prototype cookstove following the experimental methodology of 02 international standards, one Latin American and one Asian. The burner designed and manufactured in previous research gave a wide range of natural gas power according to the working pressure used and high efficiency of approximately 57% compared to the cookstoves that are sold nationwide, which on average is 53%. The advantage of this prototype cookstove is that it uses operating pressures between 23 and 34 mbar compared to stoves in the Peruvian market that do not have a standard of the maximum gas pressure.

Fifth-generation (5G) communication networks and sustainability: A research agenda

Communication networks hugely improved many fields during the past decades (i.e. education, healthcare, engineering sector, management, etc.). However, the new fifth-generation (5G) communication networks is expected to be able to bring new developments in this sector even faster than the past technologies. This will happen, not only, as the technology will be presented in the field as a new way of approaching data and services, but also, as there is more pressure exerted on 5G, due to the rising need of data that companies and individuals feel in everyday life. The paper suggests that emerging trends in this filed will also be able to create improvements for society, economy, management and environment. Better use of energy, information sharing and resource efficiency, in fact, are some of the main goals that the 5G and the sustainability approach are aiming to achieve. This shows that 5G and sustainability have several features in common that are yet not fully explored nor in theory nor in practice. Thus, proposing a research agenda, the paper aims at analysing this common characteristics, but also to highlight that the 5G can be considered a strategic tool that enables companies to be involved in boosting sustainable development.

State-of-Charge Balancing of Lithium-Ion Batteries With State-of-Health Awareness Capability

A state-of-charge (SOC) balancing method which accounts for state-of-health (SOH) status of battery cells is presented in this article. The data collected from aging experiments conducted in the laboratory indicates that there is correlation between the minimum impedance of the battery and capacity fading which can be used to predict capacity capability of the battery. However, this relationship is complex and nonlinear. In this article, artificial neural network (ANN) is utilized to learn this relationship and an ANN-based capacity estimator is developed to predict available capacity of battery cells. An online impedance measurement method with improved measurement resolution is presented to obtain a more accurate minimum impedance for the ANN-based capacity estimator. The estimated capacity from the ANN capacity estimator is fed to an SOC balancing controller to calculate SOC values for the battery cells. A battery cell with worse health has lower available capacity than a battery cell with better health, and, therefore, its SOC value is adjusted to a smaller value when SOH or capacity estimation functionality is activated. Because of this mechanism and the control principle of the presented SOC balancing controller, the system draws energy at a slower rate from the battery cell(s) with lower SOH and draws energy at a faster rate from the battery cell(s) with higher SOH such that all battery cells reach their end of discharge at the same time. This results in extending operation time of the system, makes best use of energy from every battery cell, and avoids over-discharging battery cells with lower SOH. The presented method is evaluated using results obtained from a laboratory experimental setup.

An extended method for work and heat integration considering practical operating constraints

The development of methodologies for the simultaneous work and heat integration has increasingly been the focus of recent research. Approaches may vary among optimization and heuristic-based methods considering direct and indirect work exchange, in addition to, or with the development of new strategies for heat recovery. This work presents a strategy for the synthesis of work and heat exchange networks (WHEN) considering the use of single-shaft-turbine-compressor (SSTC) units. The method is based on a meta-heuristic approach and aims fundamentally at synthesizing WHEN that may operate within industrial-like conditions, which are often narrower than those considered in the literature due to simplification assumptions. Therefore, in the present work, practical temperature upper/lower-bound constraints are considered for pressure manipulation units, and the number of coupled units per shaft is limited. Evidently, these constraints yield additional difficulties for the optimization method. The method considers inlet and outlet temperatures as decision variables in the units of a block-based model, making the maintenance of solutions within feasible range more efficient during the optimization runs. Moreover, a new Simulated Annealing (SA) based strategy is developed for deciding optimal compressor/turbine couplings in a model that considers a preset number of “slots” per shaft. The method aims at minimizing total annual costs (TAC) and is tested over four case studies. The first two are used both as benchmark for TAC comparison to those reported in the literature as well as for testing the new constraints. The other two cases are investigated for TAC and energy-wise improvements to original designs. Considerable economic improvements and better use of energy are attained in all cases. For the two benchmark studies, solutions with TAC 1.5% and 4.3% lower than literature designs were found. For the industrial cases, energy requirements were overall reduced. For instance, in example 3, no external power source is required, while literature solutions present power shortage. In example 4, compression power requirements were reduced by 9.9%. The method also proved efficient in maintaining solutions within practical operating ranges.

Mobile Android APP Proposal Using an Inventor Platform Applied to Energy Efficiency and Sustainability

This paper reports on the implementation of the efficient Manaus project, with the objective of developing a mobile application that expires on energy saving, related to environmental issues, since energy production, advanced natural resources. This application is designed to be used in a residential unit to provide residents with information on formula applications that explain the generation and energy expenditure of household electrical appliances, use or usage tests, and usage of the device. lowering values ​​and minimizing the use of environmental resources. Thus, through a process of raising awareness of the knowledge gained from research in recent years, as well as providing quality content and ease of access, use the Google platform "APP INVENTOR" as a framework for testing results. Therefore, compile information on the best use of energy from a variety of information, including the elaboration of a Quiz, which addresses questions such as: where does electricity come from; tariff flags; efficient equipment; and electricity security, implemented in the application where they were supported by tools such as cartridges, and information from the agencies that reference each of these themes. This mode generates positive expectations for the future, which can create numerous other applications with information that helps to understand products, processes, changes in the sustainability context, to minimize impacts by new technologies.

P6324Contribution of muscle efficiency in heart failure patients post phase 2 cardiac rehabilitation

Abstract Background Muscle efficiency (ME), can help explain the observed improvement in patients without increase in oxygen uptake (VO2) after cardiac rehabilitation programme (CRP). The better use of energy, independent to the oxygen delivery to muscle, may improve the functional capacity in Heart failure (HF) patients. Our aim was to evaluate the contribution of muscle efficiency improvement after CR on functional capacity. Methods We analyse consecutive patients data that had their phase 2 CR concluded, with HF as admission indication with no medical therapy changes and CRT implantation during this period. The aetiology of HF and biometric data, functional class, BNP, Minnesotta and EuroQol questionnaires and cardiorespiratory test pre and post 4 months of CRP were collected. The average of the exercise load in the first two and last two training sessions were recorded. ME was calculated at peak exercise during cardiopulmonary exercise test in pre and post CRP (see formula above). Results From 55 HF patients sequentially admitted in our CRP, during the last 24 months, 45 were included, since 2 were transplanted, 1 died and the 7 didn't concluded the program or not had all the data mentioned in the methods. The mean age was 60,5±10,3 years and 78% were male. Ischemic aetiology with depressed ejection fraction (64%) was the main admission indication, followed by cardiomyopathies (18%). Betablockers, ACEi or ARBs or ARNi and MRA were taken in 91%, 93%, 46%, respectively. ICD and CRT were previously implanted in 44% of the patients. Comparing pre and post CRP VO2 at peak exercise and aerobic threshold levels no statically differences were found. In this cohort 27 (60%) patients increased ME. At the end of the CRP, this group had a higher improvement in METs (p=0,021), higher gain in lean mass (p=0,041), in EuroQoL (p=0,002) and in physical dimension of Minnesotta questionnaire (p=0,032), when compared with patients that didn't improve the ME in at least 5%. In 22 patients that increased ME, the VO2 at aerobic threshold level didn't improve by at least 5% and in this group the same benefits were confirmed. Formula of Muscle Efficiency Conclusions The improvement in exercise load reached in the post CRP cardiopulmonary test, independently of possible cardiac output changes (VO2 peak), seems to be explained in part by the increase in ME improvement.

Implementación de un sistema de monitoreo de energía eléctrica en tableros principales

The cost of electric power has become one of the most representative expenditures in the industrial environment and other organizations, only after human resources. Currently, seeking the reduction of expenses in processes and operations has become a necessity for survival in the market. Therefore, the optimization of any process is the measurement, only what is measured can be managed and therefore improved. The reduction and good use of energy is not possible without having a reliable source of information; that is why the implementation of a useful monitoring system will indicate the expenses and in what way to proceed in order to establish real opportunities for savings, as well as strategies for their maintenance in different networks. Thus, the following paper is the result of the implementation of an electrical monitoring system for an industry in the region.

ECPM: an energy-efficient cloudlet placement method in mobile cloud environment

The development of mobile cloud computing has greatly improved the computing and storage performance of mobile devices. And mobile cloud computing is undoubtedly the necessary way to solve the performance of the process for mobile applications with high performance requirements. However, migrating the mobile applications to the cloud brings about a migration delay, which is intolerable for high real-time demanding applications. This can be technically achieved by expanding mobile cloudlets, co-located with access points (AP). Then, how to deploy the cloudlet to reduce the energy consumption has become a part of major challenges in the current study. In this paper, we propose an energy-efficient cloudlet placement method, named ECPM, to effectively reduce the number of cloudlets, so as to achieve the energy savings. Specifically, the clustering of mobile devices at each time is obtained, and then the cloudlet will move to the clustering to achieve the best use of energy. Finally, the experimental results demonstrate that the proposed method is energy saving.

Straight line programs for energy consumption modelling

Energy consumption has increased in recent decades at a rate ranging from 1.5% to 10% per year in the developed world. As a consequence, several efforts have been made to model energy consumption in order to achieve a better use of energy and to minimize environmental impact. Open problems in this area range from energy consumption forecasting to user profile mining, energy source planning, to transportation, among others. To address these problems, it is important to have suitable tools to model energy consumption data series, so that the analysts and CEOs can have knowledge about the underlying properties of the power demand in order to make high-level decisions. In this paper, we focus on the problem of energy consumption modelling, and provide a solution from the perspective of symbolic regression. More specifically, we develop hybrid genetic programming algorithms to find the algebraic expression that best models daily energy consumption in public buildings at the University of Granada as a testbed, and compare the benefits of Straight Line Programs with the classic tree representation used in symbolic regression. Regarding algorithm design, the outcomes of our experimentation suggest that Straight Line Programs outperform other representation models in the symbolic regression problems studied, and also that the hybridation with local search methods can improve the quality of the resulting algebraic expression. On the other hand, with regards to energy consumption modelling, our approach empirically demonstrates that symbolic regression can be a powerful tool to find underlying relationships between multivariate energy consumption data series.

Energy Consumption Evaluation of ZBLE, AOMDV and AODV Routing Protocols in Mobile Ad-hoc Networks

Background / Objective: Mobile ad hoc network (MANET) creates a transient network that does not depend on any infrastructure or central administration mechanism. Such networks are made up of wireless mobile nodes. These nodes have to rely on batteries due to lack of stable power supply, so energy consumption is considered one of the main difficulties of this type of network. These nodes change their positions immediately, so the battery is depleted very suddenly, which affects network life. The best routing can be achieved by improving network quality, keeping high energy in mind by multipath routing in ad hoc networks using zone-based technology. The main objective of this research is to evaluate some popular performance metrics with energy efficiency. In this research, the zone-based leader Election Energy-Constructed AOMDV Routing Protocol (ZBLE) has been compared to the traditional routing protocols AODV and AOMDV, suggesting that the ZBLE protocol exhibits better results. Methods / Statistical analysis: In this paper, the routing protocol ZBLE based on zone-based technique is used. In this, the leader node is selected using the node's energy label, power analysis, and node position tracking function. The best route has been achieved by the leader node selection algorithm and power analysis. Conclusion: Most energy-related protocols are based on single-route routing, which has not been able to pay much attention to the accumulation of energy, and there have been attempts to make multi-way routing protocols also energy-based protocols, but also these protocols have been unable to make good use of energy. Through the NS2 simulator, network life is extended by reducing energy consumption by using a new energy-based multi-way routing protocol ZBLE. The results of this routing protocol performance evaluation suggest that the ZBLE protocol is superior to the AOMDV and AODV protocols. It is a zone-based technique that works by concentrating on the highest energy of nodes. Simulation results reported that the performance of ZBLE outperformed that of AOMDV and AODV. Applications / improvements: Zone-based technology can be easily used for extremely large networks. Ad-hoc network performance has been improved by improving network quality using this protocol.

Uso inteligente de recursos naturais e sustentabilidade na construção civil

Nas últimas décadas a construção civil tem se engajado para implementar uma série de iniciativas com intuito de modernizar a infraestrutura urbana e promover melhores condições ambientais, sociais e econômicas que se traduzam em competitividade para o setor. Este artigo busca mediante uma análise bibliográfica abrangente compreender as tecnologias empregadas na construção civil para promover o uso inteligente dos recursos naturais, tanto em países em desenvolvimento e como desenvolvidos. Como resultado são apresentados os principais métodos para o melhor aproveitamento de energia, hídrico, e o efeito que técnicas denominadas “verdes” tem sobre a redução de custos dos empreendimentos. São exibidos dados sobre impacto ambiental, a importância da reciclagem e reaproveitamento dos resíduos da construção civil e a repercussão positiva que as diferentes certificações podem trazer aos empreendimentos. O conhecimento das tecnologias levantadas nessa revisão pode encorajar profissionais da indústria e as partes interessadas a colocar em prática ações sustentáveis na construção.