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The use of handheld X-ray fluorescence (XRF) can be extremely beneficial to analyze platinum group metals in catalytic converters. Ultimately, handheld XRF can provide accurate, precise, fast, and nondestructive analysis of finely ground car catalyst material., Platinum (Pt), palladium (Pd), and rhodium (Rh) fall into the platinum group metals (PGMs), where several elements that share similar physical properties are grouped together. These three PGMs are used [...]

I constantly hear about how wonderful utility and government-mandated energy efficiency (EE) initiatives are. Many EE supporters claim these efforts to push consumers to buy higher-efficiency appliances and use more [...]

Drivers for industrial energy efficiency are factors that promote the sustained adoption of energy-efficient measures and practices. Leveraging drivers to overcome barriers and encourage action which improves industrial energy efficiency can contribute to closing the energy efficiency gap. In fossil-fuel-based systems, this will also contribute to greenhouse gas abatement. A systematic literature review was used to investigate how knowledge about drivers is generated and whether prevalent drivers can be mapped to existing taxonomies. The systematic literature review confirmed that surveys and/or interviews with managers from countries who are members of the Organisation for Economic Cooperation and Development (OECD) are the most common way to gather data on drivers for industrial energy efficiency. This means the extant knowledge on drivers may be incomplete because contributions from some stakeholders, industry types and company sizes may be missing. The review also found economic drivers are the most prevalent and that not all the drivers identified during the study can be mapped to contemporary driver taxonomies. Having an agreed-upon comprehensive taxonomy facilitates empirical research and comparison of studies. Further research into the views of frontline workers and the creation of a comprehensive driver taxonomy is recommended.

The development of global and regional energy markets is one of the most important problems of the current state of global economic relations and is one of the highest-priority areas in the formation of national and regional strategies for the socio-economic development of any country. The role of energy supply is focused on monitoring and compliance with standards. However, in recent years, the importance of energy supply to the housing stock has increased significantly, which has led to an expansion of the role of management within the framework of the risk management function. Kazakhstan has a Unified electric power system, which is represented by a set of power stations, transmission lines, and substations that provide reliable and high-quality energy supply to consumers. Currently, the main task within the framework of the priority of the development of Kazakhstan’s energy sector is to build up the energy base and provide the growing needs of the population and the economy with the necessary energy resources based on the development of modern energy complexes and alternative energy sources in conjunction with the implemented and planned macroprojects. Since the current economic development of Kazakhstan is closely interrelated with the realization of energy resources and their effective use, it acts as one of the fundamental levers for the development of the national economy. According to our research goal, it is necessary to consider sustainable energy supply in the country based on the analysis and assessment of energy consumption volumes and the impact of the country’s regional and sectoral policies on their use. The author’s approach to the distribution of countries by MNC has been developed and estimates of regression parameters, correlation coefficients, and elasticity coefficients. When constructing the author’s approach, the countries of Europe and Central Asia were studied and a sample of estimates was carried out, which has statistically significant effects on the formation of energy consumption volumes in the Republic of Kazakhstan.

To control and reduce energy consumption, it demands to install a network of sensors and using a dashboard to monitoring data acquisition from its. Energy monitoring is necessary to keep track of energy consumption according to the season, weather conditions and the flow of use of electrical appliances in the institution. The paper presents an approach for monitoring energy efficiency base on Arduino modules (smart-MAC) through a dashboard application. Dashboard WEB application has the advantage of leting the user a flexible indicator and chart widgets configuration for create an unlimited number of boards and devices connected to the same account. To realize an efficiency use of energy in public institution the date is analyze and on results can be take measurements for it. [ABSTRACT FROM AUTHOR]

Recent improvements in shipboard systems focus on the use of new technological systems and the adoption of innovative operating strategies for both increasing energy efficiency and reduce gas emissions. In such a context, this article studies a ship power system, where an energy storage system and a tailored energy management system are applied. It focuses on a detailed model of the on-board power system and points out a scenario of analysis larger than those usually adopted in the literature. The model is carried out with reference to DC, AC and hybrid AC/DC power grid architectures, by means of a power flow approach. The strategy of the energy management system optimally controls the on-board power system integrated with a battery storage device. The strategy aims to minimizes fuel consumption of the prime movers, while satisfying time-varying load demand under different operating scenarios. The procedure, tested on actual operative conditions of a supply vessel, shows feasibility and effectiveness of the power flow approach, giving evidence to the reduction of fuel consumption, while the correct operation of the power system is guaranteed. [ABSTRACT FROM AUTHOR]

Introduction. The article is concerned urgent problems that arise in agriculture sector of national economy Ukrainian concerning effective use of energy resources may be resolved by using such scientific and practical activity as energy management. Hereat the leading role granted to “energy efficiency” category. Purpose. The purpose of the paper is to study energy use and energy conservation problems in the agrarian sector and to develop measures to improve the energy conservation and energy management mechanism of the agrarian enterprise. Results. Agriculture enterprise potential of energy-saving is a totality of potential opportunities of enterprise concerning energy, resources and the means saving required for these opportunities to be realized taking into consideration specific levels of energy consumption in agriculture. Energy-saving mechanism is a combination of structures, standards, methods and means of managing energy preserving process that is based on rational consumption of energy resources. Energy management as a component of organization management should be interpreted as: managerial activity aimed at providing effective functioning of organization energy system and achieving the goals as well; management of distribution and use of energy resources within the bounds of the specific organization which provide producing definite number of products or services; making managerial decisions to use energy resources efficiently as well as monitor implementation of these decisions. Fundamental principles are of high importance for energy management. They help director to affect the controlled system more reasonably and expect possible feedback. Besides, the analysis of alternative variants of energy sources consumption, energy consumption management has to involve energy consumption planning and organization of its implementation. We should take into account the principle of energy resources interchangeability choosing between several resources. Energy consumption gain is reasonable until the effect of last energy resources consumption equalizes with output.

With extraordinary growth in the Internet of Things (IoT), the amount of data exchanged between IoT devices is growing at an unprecedented scale. Most of the IoT devices are low-resource devices handling sensitive and confidential data. Conventional encryption methods are inappropriate for lowresource devices. Lightweight block ciphers are used to encrypt data on such devices, as it balances security requirements and energy consumption. The objective of this paper is to explore opportunities to improve performance and optimize energy consumption for cipher designs targeted for low-resource IoT devices. This paper also presents an energy management algorithm to improve IoT survivability against Denial-ofservice attacks in the form of battery exhaustion. We developed a simple and effective model for lightweight cipher performance metrics. Model results were compared and validated with published application-specific integrated circuit (ASIC) and field-programmable gate array (FPGA) designs. Using the model, we explored opportunities for performance enhancement in future cipher designs. Our analysis indicates that the optimum energy is achieved when block size is between 48-bit and 96-bit. Also, increasing size of overhead logic from one round to two rounds increases encryption energy-per-bit by 3.4%. Further, the optimum energy is attained when the number of algorithm rounds is 16 or less. Optimum throughput is achieved by implementations with large block sizes and large number of implemented rounds. Next, we present a novel algorithm to manage cipher energy consumption. The algorithm allows low-resource IoT devices to encrypt critical messages during low-energy mode while balancing throughput, energy per bit, and device activity.

In this work, a novel methodology to assess energy performance indicators of productive and economic sectors trough the analysis of the Italian mandatory energy audits database is presented. The updating of sectoral reference energy performance indicators is fundamental for both companies and policy makers—for the formers to evaluate and compare their energy performance with competitors in order to achieve improvements and for the latter to effectively monitor the impact of energy policies. This methodology could be potentially applied to all production sectors, providing key information needed to characterize various production processes from an energy point of view. Awareness of energy efficiency and sectorial benchmarking represent the first necessary steps for companies moving towards energy transition. This paper provides details of the statistical method developed and its application to the NACE 23 division “Manufacturing of other non-metallic mineral products”, with a focus on the cement industry. For this sector, results are presented in terms of specific indicators based on energy source. General results, methodological insights, and validation of the proposed case study are discussed.

Pakistan receives Direct Normal Irradiation (DNI) exceeding 2000 kWh/m²/annum on approximately 83% of its land, which is very suitable for photovoltaic production. This energy can be easily utilized in conjunction with other renewable energy resources to meet the energy demands and reduce the carbon footprint of the country. In this research, a hybrid renewable energy solution based on a nearly Zero Energy Building (nZEB) model is proposed for a university facility. The building in consideration has a continuous flow of water through its water delivery vertical pipelines. A horizontal-axis spherical helical turbine is designed in SolidWorks and is analyzed through a computational fluid dynamics (CFD) analysis in ANSYS Fluent 18.1 based on the K-epsilon turbulent model. Results obtained from ANSYS Fluent have shown that a 24 feet vertical channel with a water flow of 0.2309 m3/s and velocity of 12.66 m/s can run the designed hydroelectric turbine, delivering 168 W of mechanical power at 250 r.p.m. Based on the turbine, a hybrid renewable energy system (HRES) comprising photovoltaic and hydroelectric power is modelled and analyzed in HOMER Pro software. Among different architectures, it was found that architecture with hydroelectric and photovoltaic energy provided the best COE of $0.09418.

Deployment of CTA-2045–enabled devices is increasing in the U.S. market. These devices allow utilities or third-party aggregators to control appliance energy use in homes, and could also be applied to end uses in small commercial buildings. This study focuses on a field study using CTA-2045–enabled water heaters to shift electric load off the peak and toward periods when renewable resources are more prevalent (e.g., near noon for solar resources and near midnight for wind resources). The following load shifting strategies were compared to understand effects on the aggregate load-shifting capabilities of Heat Pump Water Heaters (HPWHs) and on consumer hot water supply: non-targeted (traditional), targeted (grouped, with different shifting schedules) and “smart” (adaptive control commands). The results of this study show that targeted and smart control strategies yield significantly more load-shifting potential from a population of water heaters than the non-targeted approach without sacrificing hot water supply to occupants. However, as control commands become more aggressive, aggregators may face challenges in meeting consumer hot water demand. The findings and lessons learned can benefit electric utilities and inform updates to manufacturer controls and communications standards. The data collected may also be useful for developing and validating HPWH models.

Energy management focuses on improving the efficient use of resources and increasing energy access in a path towards a more sustainable society. In spite of the strategies that have been proposed to guarantee increased access to the energy resources at affordable costs, there are still challenges to ensure the conservation of the resources and the protection of the environment. In line with these objectives, Cloud Computing for Smart Energy Management project (CC-SEM) is a research effort for building an integrated platform for smart monitoring, controlling, and planning energy consumption and generation in urban scenarios. CC-SEM includes, firstly, the design of a low-cost IoT device capable of monitoring, operating, and controlling home appliances according to predefined rules. It was developed with the aim of automatically manage consumption. Secondly, an analysis of 5G Narrowband IoT as a suitable cellular technology for Smart Grid outage restoration and management message delivery was addressed. Thirdly, an analysis of domestic consumption patterns was carried out to help to predict home consumption, using literature measurements. Fourthly, within the context of electrical network simulation, a forecasting and performance evaluation methodology for the generation of individual photovoltaic systems is proposed. In summary, CC-SEM presents the research efforts to provide a set of tools for controlling home devices, planning/simulating scenarios of energy generation, and to propose advances in the communication infrastructure for transmitting the generated data. [ABSTRACT FROM AUTHOR]

Building information modeling can help in predicting the energy efficiency in future based on dynamic patterns obtained by visualization of data. The aim of this study was to investigate the effective parameters of energy consumption using BIM technology which can evaluate the buildings energy performance. First, three forms of general states in the building were modeled to evaluate the proposed designs in Autodesk Revit Software. Then, the main building form for energy modeling and analysis was selected. Autodesk Revit 2020 software was also used to obtain the results of climate data analysis and building energy consumption index. Finally, the most optimal mode was selected by examining different energy consumption modes. The results showed that the use of building information modeling technology in adjusting the parameters affecting energy consumption can save energy cost up to 58.23% in block D. Energy cost savings for block C and the western lobby were obtained as 51.03% and 43.05%, respectively. Based on energy use intensity, energy cost savings for blocks C, D, and the western lobby were estimated as 16.67%, 16.30%, and 11%, respectively. The results of parametric studies on alternative schemes of energy use intensity optimization showed that 16.30% savings could be achieved by the base building model in a 30-year time horizon. Therefore, it was concluded that optimization of energy consumption would reduce the environmental pollutants emission and contribute to preservation and sustainability of the environment. [ABSTRACT FROM AUTHOR]

This article presents optimal strategies in the home energy management system (HEMS) integrating solar power, energy storage, and vehicle-to-grid (V2G) capability for predetermined scenarios. The proposed system aims to address the demand response schemes, both real-time pricing and emergency load curtailment, V2G mode of operation. In the interruption event, the HEMS operates in the vehicle-to-home mode to ensure supply continuity. The control algorithms are experimentally implemented on the created hardware platform of EV and home batteries, solar power, and household loads with preset priorities. Both ac and dc charging technologies for EVs are considered. The HEMS simultaneously optimizes the scheduling of charging and discharging of EVs and home battery. Results on operation under predetermined scenarios have confirmed the validity of the proposed HEMS. [ABSTRACT FROM AUTHOR]

Battery driven computing devices such as laptops and cellular phones have become a necessity in this era. Mobile applications help us in daily life activities and with the rise of Internet of Things (IoT) new opportunities are open up to automate different task. However, batteries have their own limitations such as weight, cost, and size. Multiple applications and background processes running in parallel easily drain phone's battery within 24 hours consequently annoying users by limited battery capacity. Repeated charge, recharge cycles steadily diminish the full capacity of batteries resulting in the immense decreased performance of the device. Therefore, mobile devices and mobile applications are in great need of energy-aware modules. In this paper, a survey is performed to identify the needs of the mobile user in the context of energy consumption problem. The results of survey lead authors to propose a middle layer energy aware framework to address this issue. The proposed framework highly relies on the association between the operating system, application, and end user. The main objective of the proposed framework is to maintain an energy-aware capability to facilitate end user and mobile applications. The major components of the proposed framework are processing engine, application classifier, application resource management, system profiling, application modes, power estimator and power policy management. Proposed framework also offers a policy manager algorithm based on research community feedback and survey's results. Proposed framework emphasizes on energy efficient execution of mobile operations for end user and operating systems. [ABSTRACT FROM AUTHOR]

The paper presents a new vision on the energy consumption management in the case of the small and medium enterprises (SMEs), integrated into an advanced decision support platform, with technical and economic benefits on increasing the energy efficiency, with four modules for database management, profiling, forecasting, and production scheduling. Inside each module, artificial intelligence and data mining techniques were proposed to remove the uncertainties regarding the dynamic of technological flows. Thus, the data management module includes the data mining techniques, that extract the technical details on the energy consumption needed in the development of production scheduling strategies, the profiling module uses an original approach based on clustering techniques to determine the typical energy consumption profiles required in the optimal planning of the activities, the forecasting module contains a new approach based on an expert system to forecast the total energy consumption of the SMEs, and production scheduling module integrates a heuristic optimization method to obtain the optimal solutions in flattening the energy consumption profile. The testing was done for a small enterprise from Romania, belonging to the domain of trade and repair of vehicles. The obtained results highlighted the advantages of the proposed decision support platform on the decrease in the intensity of energy consumption per unit of product, reduction of the purchase costs, and modification of the impact for which energy bills have on the operational costs. [ABSTRACT FROM AUTHOR]

• The electricity technology mix is forecasted for the day-ahead market with a deep neural network. • The LCA aware scheduling framework allows to minimize the LCA impacts relative to the electricity consumption of the industrial plant. • The LCA aware scheduling could be adopted by all systems with a flexible consumption of electricity by customizing the optimization constraints. Here we show the possibility to forecast the hourly day-ahead electricity consumption mix exploiting a deep learning model. Thus, in the context of the proposed life cycle assessment (LCA) aware scheduling framework, a production scheduling could be optimized to adapt its load profile in those hours that are predicted to have a lower environmental impact. The objective functions of the optimization would therefore be the LCA impacts of the consumed electricity mix. The increase in detail in the accounting can also be exploited to complement the life cycle inventory, allowing the overall assessment to be more adherent to reality. [ABSTRACT FROM AUTHOR]

Copyright of Opuntia Brava is the property of Universidad de Ciencias Pedagogicas de Las Tunas, Centro de Documentacion e Informacion Pedagogica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

An efficient scheduling reduces the time required to process the jobs, and energy management decreases the service cost as well as increases the lifetime of a battery. A balanced trade-off between the energy consumed and processing time gives an ideal objective for scheduling jobs in data centers and battery based devices. An online multiprocessor scheduling multiprocessor with bounded speed (MBS) is proposed in this paper. The objective of MBS is to minimize the importance-based flow time plus energy (IbFt+E), wherein the jobs arrive over time and the job's sizes are known only at completion time. Every processor can execute at a different speed, to reduce the energy consumption. MBS is using the tradition power function and bounded speed model. The functioning of MBS is evaluated by utilizing potential function analysis against an offline adversary. For processors m ≥ 2, MBS is O(1)-competitive. The working of a set of jobs is simulated to compare MBS with the best known non-clairvoyant scheduling. The comparative analysis shows that the MBS outperforms other algorithms. The competitiveness of MBS is the least to date. [ABSTRACT FROM AUTHOR]

Management of energy dissipation and battery life is a challenge in health monitoring wearables. Low-quality data collection, non-reliable monitoring process, and missing important health events are consequences of single-goal fixed-policy solutions. In this research, energy dissipation of IoT-based wearable systems is managed through a dynamic multi-goal approach. Health status of the user of a wearable device, the continuity of monitoring, and the accuracy of collected data are parameters we consider in our goal hierarchy to select a proper system management policy at run-time to achieve the most significant goal at a given time. In our approach, a dynamic observation process assesses the user and system data and a fog-assisted control engine detects the states, enforces the proper policy, and reconfigures the wearable sensor. To demonstrate our solution, we develop a real reconfigurable wireless sensor node with an ability to follow a set of parametrically defined policies and performed a set of experiments to find the most efficient setting. Our evaluation shows that the proposed system is able to reduce the power consumption by 44% and prevent the data loss due to battery shortage in 0.78% of total data collection time compared to a baseline system without a goal manager. [ABSTRACT FROM AUTHOR]

Taking advantage of the low-cost photovoltaic (PV) energy requires overcoming several process challenges. The Triple intercell bar technology, with current source topology, is a synergic solution. This bar overcomes faulty or open contacts and surpasses the anomaly of metallurgical short circuits. In addition, an extra 10% in sunlight PV energy is possible, thanks to lower current densities dispersions. This requires modulating the day–night process current of the copper cathodes electrowinning facility. The technology ensures bypass of defective contacts and prevention or attenuation of short circuits. Moreover, the technology extends the lifetime of the electrodes and improves the energy efficiency. A concentrated parameter model, using industrial data projects the results. [ABSTRACT FROM AUTHOR]

This article shows the creation and use of a monitoring and management system for water and energy home resources. This system allows the automation and visualization of home resources consumptions so that users can identify which are the most relevant points that generate expenses, showing consumption profiles and allowing their activation and deactivation to be controlled. This development results in a free software and hardware system, demonstrating that the use of applications handled with current tools are potential elements for the management and care of the environment, substantially reducing the cost of public utilities and fostering the use of tools and economic solutions such as free software and hardware. The management of home resources is currently one of the most important issues when it comes to sustainability and energy efficiency. Therefore, the use of hardware and free software allow developing Internet of Things (iot) applications that are easy to handle, economic and reliable. Finally, we present the results obtained with the measurement of consumptions using Arduino free software with the support of nodemcu free hardware. [ABSTRACT FROM AUTHOR]

Copyright of Revista Facultad de Ingeniería - UPTC is the property of Universidad Pedagogica y Tecnologica de Colombia, Facultad de Ingenieria and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this study, research was carried out on how to prevent unnecessary energy in the textile sector, and solutions were presented in this context, identifying the main problems. The textile industry is one of the most beautiful examples in the globalized world. A product is not manufactured in a plant from start to finish, but instead, it is customized to be small and medium-sized enterprises (SMEs) for one task. Energy efficiency is especially important for SMEs to compete with businesses in Asian countries in the market. The purpose of examining the energy sources used in this study under the headings of electricity and thermal energy was to prepare a more detailed report and create a resource that could be used in the sector. As a result of our study, energy savings of up to 60% can be saved by changing most machines and working methods used in the sector with simple customizations or new ones that can be made in machines because of the lack of old or working methods designed to meet the old or needs. [ABSTRACT FROM AUTHOR]

An energy management information system (EMIS) combines software, hardware, and data to support people in their efforts to manage energy at the process, system, facility, and enterprise level, year after year. A distributed measurement and monitoring system (DMS) is a fundamental part of an EMIS; it is constituted by the meters distributed in the switchboards of the power system. This article suggests a method of assessment of a DMS based on an indicator called level of coverage (LOC). This indicator can evaluate the LOC of a single meter or of a whole system considering the classification in significant energy uses according to the standard ISO 50001. [ABSTRACT FROM AUTHOR]

The energy efficiency gap is known as the difference between optimal level of energy efficiency and the actual level of achieved energy efficiency. Energy management has proven to further close the energy efficiency gap. Energy management may differ depending on whether it concerns a large, energy-intensive company or small and medium-sized enterprises (SMEs). SMEs are of high interest since they form a large share of the economy today. For SMEs, a lighter form of energy management, in the form of energy efficiency network participation, has proven to deliver sound energy efficiency impact, while for larger, energy-intensive firms, a certified energy management system may be more suitable. However, various barriers inhibit adoption of energy efficiency measures. While there is an array of research on barriers to and driving forces for energy efficiency in general, research on barriers to, and driving forces for, energy management is rare, one exception being a study of energy-intensive pulp and paper mills. This holds even more so for industrial SMEs. This paper aims to identify the barriers to, and drivers for, energy management in manufacturing SMEs. Results of this explorative study show that the top four barriers to energy management are lack of time/other priorities, non-energy-related working tasks are prioritized higher, slim organization, and lack of internal expert competences, i.e., mainly organizational barriers. The top four drivers for energy management are to reduce production waste, participation in energy efficiency networks, cost reduction from lower energy use, and commitment from top management. Furthermore, results show that energy management among the studied SMEs seems to not be as mature, even though the companies participated in an energy management capacity building program in the form of energy efficiency networks, which, in turn, shows a still largely untapped potential in the societal aim to reduce the energy efficiency and management gaps. The main contribution of this paper is a first novel attempt to explore barriers to, and drivers for, energy management among SMEs.

A prerequisite for achieving high energy efficiency of water supply systems (understood as using less energy to perform the same task) is the appropriate selection of all elements and their rational use. Energy consumption in water supply systems (WSS) is closely connected with water demand. Especially in the case of oversized water supply systems for which consumers’ water demand is at least 50% less than previously planned and flow velocity in some parts of the system is below 0.01 m·s−1, this problem of excessive energy consumption can be observed. In the literature, it is difficult to find descriptions and methods of energy management for such a case. The purpose of this study was both an evaluation of the current demand of an oversized WSS and a preliminary technical analysis of the possibility for energy saving. Solutions are presented that resulted in improvements in energy management, thus increasing energy efficiency. The conducted analyses indicate the wide use of numerical, hydraulic models, among others, for the needs of the sustainable oversize water supply systems management in order to improve energy efficiency. Those simulations only give energy consumption results as a first step in the process of decision-making for the modernization process, in which investment costs should be taken into account as a second step. Thus, this paper emphasizes the crucial role of hydraulic models as a good analytical tool used in decision support systems (DSS), especially for large, oversized water supply systems.

Neural-network training can be slow and energy intensive, owing to the need to transfer the weight data for the network between conventional digital memory chips and processor chips. Analogue non-volatile memory can accelerate the neural-network training algorithm known as backpropagation by performing parallelized multiply-accumulate operations in the analogue domain at the location of the weight data. However, the classification accuracies of such in situ training using non-volatile-memory hardware have generally been less than those of software-based training, owing to insufficient dynamic range and excessive weight-update asymmetry. Here we demonstrate mixed hardware-software neural-network implementations that involve up to 204,900 synapses and that combine long-term storage in phase-change memory, near-linear updates of volatile capacitors and weight-data transfer with 'polarity inversion' to cancel out inherent device-to-device variations. We achieve generalization accuracies (on previously unseen data) equivalent to those of software-based training on various commonly used machine-learning test datasets (MNIST, MNIST-backrand, CIFAR-10 and CIFAR-100). The computational energy efficiency of 28,065 billion operations per second per watt and throughput per area of 3.6 trillion operations per second per square millimetre that we calculate for our implementation exceed those of today's graphical processing units by two orders of magnitude. This work provides a path towards hardware accelerators that are both fast and energy efficient, particularly on fully connected neural-network layers.Analogue-memory-based neural-network training using non-volatile-memory hardware augmented by circuit simulations achieves the same accuracy as software-based training but with much improved energy efficiency and speed., Author(s): Stefano Ambrogio [sup.1] , Pritish Narayanan [sup.1] , Hsinyu Tsai [sup.1] , Robert M. Shelby [sup.1] , Irem Boybat [sup.2] [sup.3] , Carmelo di Nolfo [sup.1] [sup.3] , Severin [...]

For nearly two decades, researchers in the field of plasmonics.sup.1--which studies the coupling of electromagnetic waves to the motion of free electrons near the surface of a metal.sup.2--have sought to realize subwavelength optical devices for information technology.sup.3-6, sensing.sup.7,8, nonlinear optics.sup.9,10, optical nanotweezers.sup.11 and biomedical applications.sup.12. However, the electron motion generates heat through ohmic losses. Although this heat is desirable for some applications such as photo-thermal therapy, it is a disadvantage in plasmonic devices for sensing and information technology.sup.13 and has led to a widespread view that plasmonics is too lossy to be practical. Here we demonstrate that the ohmic losses can be bypassed by using 'resonant switching'. In the proposed approach, light is coupled to the lossy surface plasmon polaritons only in the device's off state (in resonance) in which attenuation is desired, to ensure large extinction ratios between the on and off states and allow subpicosecond switching. In the on state (out of resonance), destructive interference prevents the light from coupling to the lossy plasmonic section of a device. To validate the approach, we fabricated a plasmonic electro-optic ring modulator. The experiments confirm that low on-chip optical losses, operation at over 100 gigahertz, good energy efficiency, low thermal drift and a compact footprint can be combined in a single device. Our result illustrates that plasmonics has the potential to enable fast, compact on-chip sensing and communications technologies. Ohmic losses in plasmonic devices can be reduced by exploiting 'resonant switching', in which light couples to surface plasmon polaritons only when in resonance and bypasses them otherwise., Author(s): Christian Haffner [sup.1] , Daniel Chelladurai [sup.1] , Yuriy Fedoryshyn [sup.1] , Arne Josten [sup.1] , Benedikt Baeuerle [sup.1] , Wolfgang Heni [sup.1] , Tatsuhiko Watanabe [sup.1] , Tong [...]

In this study, solar powered LED luminaire has been designed for street lighting. To drive the led luminaire a new lighting system called “multi-mode operating” and a computer interface based on C# have been introduced. The proposed system aims to decrease the alteration of PV panel power required between summer and winter due to different insolation time; it can also extend the employed battery life. In the software five different operation modes are performed considering traffic density and ambient light conditions. In the designed system, motion sensors are used to bring innovation to classical street lighting system. Moreover, RF communication modules are exploited to control and reach the system data. To verify the effectiveness of the system, an implementation study is carried out in a test area. The effect on the battery life and the energy-saving of the designed system are examined in detail. The implementation results show that the proposed system has been experimentally observed that the system using multi-mode operates as 42% more efficient than the classical lighting system.

Pressure is mounting on the wine industry to consider energy management interventions to, inter alia, reduce energy consumption – to be more competitive, become more self-reliant, and to reduce the carbon footprint of the sector. This paper then summarises the process that was undertaken to develop an appropriate energy management guideline for the South African wine industry. It is based on a literature analysis of best practices elsewhere, and a number of case studies across different sizes of winery operations in South Africa. The positive outcomes from energy management interventions at these cases are demonstrated, but a number of challenges are also highlighted. Recommendations are made accordingly.

The paper is a study on the energy efficiency indicators that can be used for the activities in logistics of freight distribution, at the company level, as well as at macroeconomic level. There are highlighted also some solutions for increasing energy efficiency in distribution channels, starting from technical and logistics management actions, at the company level. There are revealed also the impacts of energy efficiency measures.

Abstract. The article analyzes the activity of Russia’s first chair of «Energy service and energy saving management» established at the Institute of Management, Economics and Social Technologies of Moscow Aviation Institute (National Research University). The focus of the department staff is training of specialists in energy management for various industries. The first part of the article is devoted to analysis of the results achieved by the department. The main part of the study contains a detailed description of the structure and developed by the authors in collaboration with major European energyNefficient companies, engineering and economic education model called “an arrow of energy efficient competencies”. The authors dwell on the content of its individual units and components of their areas of study.

The relevance of the discussed issue is caused by the need to achieve the strategic state and society goal to increase the gross domestic product (GDP) in a few times and reduce its power consumption. It will allow Russia to join the ranks of developed countries, and not to be their raw materials appendage. This problem can only be solved by converting the Russian economy on energy saving technologies and improving the energy efficiency of fuel and energy resources, since the economic development by increasing oil and gas production has exhausted itself, and makes no significant GDP growth. The main aim of the study is to show the importance of an energy audit for effective management of energy saving at all stages of energy production, transmission, transformation, distribution and consumption. The methods used in the study: analysis of fulfillment of energy saving laws and regulations and problems preventing one of the wealthiest countries in the world in reserves and production of fuel and energy resources to join the ranks of highly developed countries. The results. The authors examined the contents of the main functions of energy management: planning, organization, motivation and control, as well as the types and content of an energy audit. It is shown that only with the help of in-depth energy audit, forming a bank of objective data about the energy flows, it is possible to realize the functions of energy management; calculate fuel and energy balances of equipment, company, region, country, allowing reliable and continuous supply of fuel and energy resources of the enterprise and regions. Critical analysis of the energy balance allows setting the objective rates of fuel and energy resources consumption, extraction and production, assessing possible energy saving potential in the implementation of various energy saving activities, and making a real energy saving program. Thus, the study concluded that it is impossible to manage effectively the energy efficiency in the country and to reduce the energy intensity of GDP without a comprehensive reliable energy audit in the production and consumption of energy resources, as well as without using all levers of power management.

The research explores the potential of digital-twin-based methods and approaches aimed at achieving an intelligent optimization and automation system for energy management of a residential district through the use of three-dimensional data model integrated with Internet of Things, artificial intelligence and machine learning. The case study is focused on Rinascimento III in Rome, an area consisting of 16 eight-floor buildings with 216 apartment units powered by 70% of self-renewable energy. The combined use of integrated dynamic analysis algorithms has allowed the evaluation of different scenarios of energy efficiency intervention aimed at achieving a virtuous energy management of the complex, keeping the actual internal comfort and climate conditions. Meanwhile, the objective is also to plan and deploy a cost-effective IT (information technology) infrastructure able to provide reliable data using edge-computing paradigm. Therefore, the developed methodology led to the evaluation of the effectiveness and efficiency of integrative systems for renewable energy production from solar energy necessary to raise the threshold of self-produced energy, meeting the nZEB (near zero energy buildings) requirements.

Since 2014, Taiwan has promoted a 1% annual electricity saving target to promote electrical efficiency efforts. As the industrial sector accounts for approximately 60% of the overall electricity consumption of Taiwan, this sector presents the greatest opportunity for improving Taiwan’s overall energy efficiency. Here, the energy audit data of industrial energy users are analyzed via logistic regression to understand the factors impacting their likelihood of achieving the targeted 1% electricity saving. Of the variables under study, the number of employees and the rank of the energy administrator were significantly correlated with the likelihood of reaching the electricity saving target. Within the management structure of the factory, energy users with higher-ranking energy administrators are more likely to achieve the targeted 1% electricity saving. As it is impractical to rapidly increase the number of employees, higher-ranking employees, i.e., factory executives, should be appointed as energy administrators to improve users’ electrical efficiency and thus reach the targeted 1% annual electricity saving. Based on the findings of our research, we put forward a point of view that in addition to the introduction of new technologies to improve energy efficiency, it can also be achieved through adjustments to the management structure of energy administration.

This paper presents the application of an active energy management strategy to a hybrid system consisting of a proton exchange membrane fuel cell (PEMFC), battery, and supercapacitor. The purpose of energy management is to control the battery and supercapacitor states of charge (SOCs) as well as minimizing hydrogen consumption. Energy management should be applied to hybrid systems created in this way to increase efficiency and control working conditions. In this study, optimization of an existing model in the literature with different meta-heuristic methods was further examined and results similar to those in the literature were obtained. Ant lion optimizer (ALO), moth-flame optimization (MFO), dragonfly algorithm (DA), sine cosine algorithm (SCA), multi-verse optimizer (MVO), particle swarm optimization (PSO), and whale optimization algorithm (WOA) meta-heuristic algorithms were applied to control the flow of power between sources. The optimization methods were compared in terms of hydrogen consumption and calculation time. Simulation studies were conducted in Matlab/Simulink R2020b (academic license). The contribution of the study is that the optimization methods of ant lion algorithm, moth-flame algorithm, and sine cosine algorithm were applied to this system for the first time. It was concluded that the most effective method in terms of hydrogen consumption and computational burden was the sine cosine algorithm. In addition, the sine cosine algorithm provided better results than similar meta-heuristic algorithms in the literature in terms of hydrogen consumption. At the same time, meta-heuristic optimization algorithms and equivalent consumption minimization strategy (ECMS) and classical proportional integral (PI) control strategy were compared as a benchmark study as done in the literature, and it was concluded that meta-heuristic algorithms were more effective in terms of hydrogen consumption and computational time.

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This study seeks to provide insights on understanding the contemporary problems of energy efficiency in Ukrainian universities by developing a comprehensive energy efficiency management framework that encompasses its participating subjects, objects and key drivers along with suggesting its implementation mechanism and tools. Emphasis should be given that the current situation of inefficient and irrational consumption of energy resources within the system of higher education in Ukraine challenges the development of an integrative approach to energy saving and energy efficiency management. It is argued that the key elements of this integrative approach to energy management are energy auditing, energy certification and energy monitoring based on the consistent use of ISO 9000 international standards. Over the last 10 years energy consumption in Ukrainian higher education institutions against the world best practice exceed by 30-40%. This triggers a critical need to building an integrative approach to energy saving and energy efficiency management. The findings revealed that disincentives reduce the degree of energy efficiency by 25%. Constructing energy profiles by a hierarchical clustering method demonstrated that 68% of the campus buildings belong to a 5th class out of 7, i. e. being highly energy intensive. Following the DGNB (German Sustainable Building Council) approach to evaluate energy efficiency has enabled to eliminate 17% of the G category classrooms (extra energy intensive) from the University heating facilities. The clustering method to assess 15 University buildings by 16 performance indicators identified 5 clusters in terms of energy consumption and energy efficiency. [ABSTRACT FROM AUTHOR]

The cloud-computing paradigm offers on-demand services over the Internet and supports a wide variety of applications.With the recent growth of Internet of Things (IoT)--based applications, the use of cloud services is increasing exponentially. The next generation of cloud computing must be energy efficient and sustainable to fulfill end-user requirements, which are changing dynamically. Presently, cloud providers are facing challenges to ensure the energy efficiency and sustainability of their services. The use of a large number of cloud datacenters increases cost as well as carbon footprints, which further affects the sustainability of cloud services. In this article, we propose a comprehensive taxonomy of sustainable cloud computing. The taxonomy is used to investigate the existing techniques for sustainability that need careful attention and investigation as proposed by several academic and industry groups. The current research on sustainable cloud computing is organized into several categories: application design, sustainability metrics, capacity planning, energy management, virtualization, thermal-aware scheduling, cooling management, renewable energy, and waste heat utilization. The existing techniques have been compared and categorized based on common characteristics and properties. A conceptual model for sustainable cloud computing has been presented along with a discussion on future research directions. [ABSTRACT FROM AUTHOR]

In this paper, a classic proportional--integral (PI) control strategy as an energy management strategy (EMS) and a microgrid stand-alone power system configuration are proposed to work independently out of grid. The proposed system combines photovoltaics (PVs), fuel cells (FCs), batteries, and supercapacitors (SCs). The system supplies a dump load with its demand power. The system includes DC/DC and DC/AC converters, as well as a maximum power point tracking (MPPT) to maximize the harvested energy from PV array. The system advantages are represented to overcome the problem of each source when used individually and to optimize the hydrogen consumption. The classic PI control strategy is used to control the main system parameters like FC current and the state-of-charge (SOC) for the battery and SC. In order to analyze and monitor the system, it was implemented in the MATLAB/Simulink. The simulation done for fuzzy logic and high frequency decoupling and state machine control strategies to validate the PI classic control strategy. The obtained results confirmed that the system works efficiently as a microgrid system. The results show that the SOC for the battery is kept between 56 and 65.4%, which is considered a proper value for such types of batteries. The DC bus voltage (VDC) is kept within the acceptable level. Moreover, the H2 fuel consumption is 12.1 gm, as the FCs are used as supported sources working with the PV. A big area for improvement is available for cost saving, which suggests the need for further research through system optimization and employing different control strategies. [ABSTRACT FROM AUTHOR]

In this study, a novel model of energy hub is proposed, which can promote the utilisation of clean energy and energy efficiency, and achieve the purpose of the local energy consumption. Secondly, based on the framework of interconnected energy hubs, call action is applied in energy internet. Then, a distributed energy management strategy is designed for energy hubs by consistency theory. Case studies show that the price adjustment mechanism is stable with more than 500 energy hubs and the price adjustment tends to a constant value after 15 times. Compared with traditional energy management, the management strategy proposed in this study is more beneficial for both surplus-hubs and short-hubs. [ABSTRACT FROM AUTHOR]

The international community is getting more and more involved in the energy management not only due to the depletion of energy resources, but also due to pollution. There are various solutions to these problems, with political economy being one of them. This is why this work was aimed at showing that political economy plays a leading role in appraising the energy management. The results showed that political economy serves cognitive, methodological, ideological, and practical purposes which have different, but closely related concepts. It was demonstrated that possible solutions suggested by governments could have social cost. However, the Cuban government's solution is to guarantee that the whole Cuban population has permanent access to the energy they need, and at the same time to limit the effects that energy consumption has on the environment. [ABSTRACT FROM AUTHOR]

Research has revealed the existence of an energy-efficiency gap – the difference between optimal and actual energy end-use, suggesting that energy efficiency can be improved. Energy management (EnM) is a means for improving industrial energy efficiency. However, due to various barriers, the full potential of EnM is not realised. Several studies have addressed drivers and barriers to energy efficiency but few to EnM. This study aims to identify EnM practices, the most important perceived drivers and barriers for EnM, and relations among them in the energy-intensive Swedish pulp and paper industry (PPI), which has the longest experience internationally of practising EnM systems, and has worked according to the standards since 2004. Our results show that, altogether, the PPI works regularly and continuously with EnM, with a clear division of responsibilities. The highest maturity for EnM practices was for energy policy, followed by organization, investments, and performance measurement. The study also shows that communication between middle management and operations personnel has potential for improvement. The most important categories of drivers were economic, whereas for barriers they were organizational. Nevertheless, knowledge-related barriers and drivers were amongst the most important, suggesting that the absorptive capacity for energy issues could be improved. Image 1029 • Energy is managed continuously, with clear policies and responsibilities. • The main drivers are economical while main barriers are organizational. • Knowledge related barriers and drivers are amongst the next most important. • Employees' absorptive capacity for energy issues could be improved. • Link between energy policy and performance measurement could be improved. [ABSTRACT FROM AUTHOR]

Abstract The implementation of International Maritime Organization regulations for CO 2 emission reduction has oriented ships to sail at lower speeds. Speed reduction reduces fuel consumption of ships significantly. In order to perform efficient ship operation, energy demand throughout the whole engine room has to be decreased. The goal of the study is to minimize electrical power consumption during slow steaming operation, hence equivalent fuel consumption and emissions could be decreased. A computational study was carried out in order to clarify potential savings with respect to main engine load. The study quantifies the energy savings in main engine cooling system which has significant potential to reduce electrical power consumption in slow steaming operations. Operational requirements are determined with the help of realistic engine room simulator of a container ship which has waste heat recovery system. The values, obtained from the simulator were verified using the technical manual of a diesel engine, which have similar output power range. The results of calculations show that there is great potential to improve energy efficiency when variable pumps are used. Based on the results, from the main engine cooling system, 60% of electrical power demand reduction can be achieved. The power reduction saved by pumps, decreases considerable amount of marine diesel oil consumption as 296.2 tons where 367.4 tons of fuel needed by diesel generators or oil fired boiler. The reduction in fuel consumption is 80% that the saving in the central cooling system corresponds 948 tons of CO 2 emission reduction and $207,300 cost saving. Highlights • Slow steaming was investigated with a novel perspective. • Cooling system is analysed for decreased engine loads. • Propose a cooling solution to decrease fuel consumption at marine engine operations. [ABSTRACT FROM AUTHOR]

As the adoption of distributed generation and energy storage grows and the attention to energy efficiency rises, Energy Management is assuming a growing importance in smart homes. Energy Management Systems (EMSs) should be easily deployable on smart homes and seamlessly integrate with the Internet of Things (IoT) ecosystem, including generators and storage devices. This paper redesigns a previously presented EMS to reduce its computational complexity, implement it on a Raspberry Pi, and make it compatible with the IoT paradigm. The EMS manages the power flows between smart home loads, renewable generators, electrical storage, and power grid. It communicates with a network of wireless sensors for electrical appliances and with a cloud-based utility data aggregator. The EMS uses Artificial Intelligence and a Dynamic Programming algorithm to fulfill two objectives at the same time: lowering the end user's electricity bill and reducing the uncertainty on the power exchanged between the end user and the grid manager. The latter goal is obtained by an effective compensation of forecasting errors. A test bench emulating four smart homes was used to measure the effectiveness of the EMS and the efficiency of the proposed implementation. The results show an uncertainty of the aggregated exchanged power of only 2.88% and a reduction of the electrical bill for end-users of up to 3.23%. Furthermore, the EMS can complete its most onerous task in less than 9 min. The good performance of the proposed EMS makes it a candidate for fast adoption by the market. [ABSTRACT FROM AUTHOR]