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Publisher Copyright: Author In this paper, we compare in a new way the energy efficiencies of modulations that have been popular in ultra-low power (ULP) transmitters. The comparison considers how the choice of modulation affects the combined energy consumed per bit (EPB) by the carrier synthesizer and power amplifier (PA). The comparison includes on-off keying (OOK), binary phase-shift keying (BPSK), binary frequency-shift keying (BFSK), pulse-position modulation (PPM) and differential PPM (DPPM). The results suggest that using OOK, BPSK or BFSK can consume tens to hundreds of percents more energy per bit compared to PPM and DPPM. Furthermore, a new energy efficiency figure of merit (FOM) is derived for transmitters. It accounts for consumed power, output power, data rate, signal bandwidth and signal-to-noise ratio required by the utilized modulation. The FOM can be applied to various types of transmitters with numerous modulations. We also present a sub-100 W DPPM transmitter (TX) and a 3.2- W 2-axis gesture sensor interface, implemented in 0.18 m CMOS. The TX operates in the 433-MHz band, uses pulse shaping for improved spectrum and achieves a FOM of 189.7 dBJ/bit. The estimated uplink range is up to 1 kilometer

High performance and energy efficiency are critical requirements for Internet of Things (IoT) end-nodes. Exploiting tightly coupled clusters of programmable processors (CMPs) has recently emerged as a suitable solution to address this challenge. One of the main bottlenecks limiting the performance and energy efficiency of these systems is the instruction cache architecture due to its criticality in terms of timing (i.e., maximum operating frequency), bandwidth, and power. We propose a hierarchical instruction cache tailored to ultralow-power (ULP) tightly coupled processor clusters where a relatively large cache (L1.5) is shared by L1 private (PR) caches through a two-cycle latency interconnect. To address the performance loss caused by the L1 capacity misses, we introduce a next-line prefetcher with cache probe filtering (CPF) from L1 to L1.5. We optimize the core instruction fetch (IF) stage by removing the critical core-to-L1 combinational path. We present a detailed comparison of instruction cache architectures' performance and energy efficiency for parallel ULP (PULP) clusters. Focusing on the implementation, our two-level instruction cache provides better scalability than existing shared caches, delivering up to 20% higher operating frequency. On average, the proposed two-level cache improves maximum performance by up to 17% compared to the state-of-the-art while delivering similar energy efficiency for most relevant applications. ISSN:1063-8210 ISSN:1557-9999

This paper studies the long-term distribution of energy-efficiency outcomes in the German residential sector. To uncover the underlying energy efficiency of buildings, we estimate the causal response of building-level heat energy demand to variability in heating degree days. We examine heterogeneity in temperature response using both panel fixed-effects and causal forests. Our results suggest that the distribution of energy-efficiency is not equitable in the West of Germany, with buildings located in the South attaining the best energy performance standards. Although the housing stock in the East is significantly older and thus less subject to building standards, they perform better than the West counterpart, likely as a result of large investments in retrofitting post-reunification. Finally, we show that the regional distribution of energy-efficiency reflects differences in heating needs - thus, the poorer energy performance of buildings in the North-West should be weighed against the warmer climatic zone.

A group of small sensors can participate in the wireless network infrastructure and make appropriate transmission and communication sensor networks. There are numerous uses for drones, including military, medical, agricultural, and atmospheric monitoring. The power sources available to nodes in WSNs are restricted. Furthermore, because of this, a diverse method of energy availability is required, primarily for communication over a vast distance, for which Multi-Hop (MH) systems are used. Obtaining the optimum routing path between nodes is still a significant problem, even when multi-hop systems reduce the cost of energy needed by every node along the way. As a result, the number of transmissions must be kept to a minimum to provide effective routing and extend the system's lifetime. To solve the energy problem in WSN, Taylor based Gravitational Search Algorithm (TBGSA) is proposed, which combines the Taylor series with a Gravitational search algorithm to discover the best hops for multi-hop routing. Initially, the sensor nodes are categorised as groups or clusters and the maximum capable node can access the cluster head the next action is switching between multiple nodes via a multi-hop manner. Initially, the best (CH) Cluster Head is chosen using the Artificial Bee Colony (ABC) algorithm, and then the data is transmitted utilizing multi-hop routing. The comparison result shows out the extension of networks longevity of the proposed method with the existing EBMRS, MOGA, and DMEERP methods. The network lifetime of the proposed method increased by 13.2%, 21.9% and 29.2% better than DMEERP, MOGA, and EBMRS respectively.

En el artículo se analiza desde el punto de vista del consumo de energía como ha sido el comportamiento real de una vivienda de tipología residencial colectiva certificada Passivhaus y construida en el año 2019. La citada vivienda, que está ubicada en el municipio de Zaragoza en zona climática D3, ocupa la primera planta de un edificio de 3 alturas y tiene todos los sistemas de producción térmica y resto de servicios alimentados con energía eléctrica. El estándar Passivhaus es un certificado de edificios de muy alta eficiencia energética que tiene entre sus características que las viviendas tengan una demanda de energía para calefacción y para refrigeración inferior a 15 kWh/m2 y año para ambos casos, con una carga de calefacción y refrigeración menor o igual a 10 W/m2. Finalmente se realiza un estudio comparativo real del rendimiento real y del COP de la instalación de producción térmica de la aerotermia para cada uno de los tres servicios (ACS, calefacción y refrigeración), en cada uno de los meses del año, bajo diversas hipótesis operativas y de temperaturas de consigna, obteniendo resultados muy interesantes desde el punto de vista de determinar cuál es el servicio que más energía consume y de establecer unos parámetros de funcionamiento de estas instalaciones para un mejor aprovechamiento térmico de la vivienda. Se realiza también un comparativo con una vivienda construida con criterios bioclimáticos en el año 2009.AbstractThe article analyses from the point of view of energy consumption the real behaviour of a Passivhaus-certified collective residential dwelling built in 2019. The house, which is located in the municipality of Zaragoza in climate zone D3, occupies the first floor of a 3-storey building and has all the thermal production systems and other services powered by electricity. The Passivhaus standard is a certificate for buildings with very high energy efficiency, whose characteristics include that the dwellings have an energy demand for heating and cooling of less than 15 kWh/m2 and year for both cases, with a heating and cooling load of less than or equal to 10 W/m2. Finally, a real comparative study is made of the real performance and COP of the aerothermal thermal production installation for each of the three services (DHW, heating and cooling), in each of the months of the year, under different operating hypotheses and setpoint temperatures, obtaining very interesting results from the point of view of determining which service consumes the most energy and establishing the operating parameters of these installations for a better thermal use of the dwelling. A comparison is also made with a house built with bioclimatic criteria in 2009

The article shows that for the selection of rational heat supply schemes, it is necessary to take into account not only economic factors, but also conduct a multiparametric analysis. The urgency of the problem has especially increased due to the high cost and shortage of traditional fuels (coal, gas), which has led to the use of alternative energy sources in heat supply systems. In the paper, options for energy carriers and corresponding design schemes of heating systems, most often used for residential buildings, are considered. Their comparative evaluation and comparison of the given values of the cost of a unit of thermal energy was made. The peculiarities of the environmental impact of heat supply sources using different types of fuel are investigated. The cost of a unit of energy and the specific emissions of pollutants related to carbon monoxide emissions are determined. A comparative assessment of specific emissions for heat-generating devices operating on natural gas, coal, firewood, and pellets has been performed. The evaluation is based on their average indicators. Recommendations for choosing a heat supply source are offered on the basis of an ecological and economic assessment., В статье показано, что для выбора рациональных схем теплоснабжения необходимо учитывать не только экономические факторы, но и проводить многопараметрический анализ. Актуальность проблемы особенно возросла из-за высокой стоимости и дефицита традиционных видов топлива (угля, газа), что привело к применению альтернативных источников энергии в системах теплоснабжения. В работе рассмотрены варианты энергоносителей и соответствующие конструктивные схемы отопительных систем, наиболее часто применяемые для жилых домов. Произведена их сравнительная оценка и сопоставление приведенных значений стоимости единицы тепловой энергии. Исследованы особенности воздействия на окружающую среду источников теплоснабжения, использующих различные виды топлива. Определены стоимость единицы энергии и удельные выбросы загрязняющих веществ, приведенные к выбросам монооксида углерода. Выполнена сравнительная оценка удельных выбросов, для теплогенерирующих устройств, работающих на природном газе, каменном угле, дровах и пеллетах. Оценка проведена по их средним показателям. На основании эколого - экономической оценки предложены рекомендации по выбору источника теплоснабжения., В статті показано, що для вибору раціональних схем теплопостачання необхідно враховувати не лише економічні фактори, а проводити багатопараметричний аналіз. Актуальність проблеми особливо зросла у зв’язку з високою вартістю та дефіцитом традиційних видів палива (вугілля, газу), що привело до застосування альтернативних джерел енергії в системах теплопостачання. В роботі розглянуто варіанти енергоносіїв та відповідні конструктивні схеми опалювальних систем, що найчастіше застосовуються для житлових будинків. Виконана їхня порівняльна оцінка та зіставлення наведених значень вартості одиниці теплової енергії. Досліджено особливості впливу на довкілля джерел теплопостачання, що використовують різні види палива. Визначено вартість одиниці одержаної енергії та питомі викиди забруднюючих речовин, які наведені до викидів монооксиду вуглецю. Виконано порівняльну оцінку питомих викидів, для теплогенеруючих пристроїв, що працюють на природному газі, кам’яному вугіллі, дровах та пелетах. Оцінку проведено за їх середніми показниками. На підставі еколого - економічної оцінки запропоновано рекомендації щодо вибору джерела теплопостачання.

Nowadays, discussions about the use of energy efficiency in industries have intensified due to the need to optimize the resources used, especially the high cost in the production process. In this context, a literature review and a research agenda on energy efficiency in industrial environments can assist in the search for solutions and challenges to reduce energy consumption in manufacturing, as well as identify future trends for the topic. Therefore, this article proposes to update the energy efficiency research agenda in industrial environments, through a systematic review of the literature, between the years 2015 and 2020, in search of articles published in journals with current practices and the new strategies used in energy management. For the review of the research agenda, one hundred and eighty-five articles were selected, which were read and used in the bibliometric analysis, which was compared to the results obtained and observed in the base article for this update, thus helping in directing the creation of an agenda for studies and practices in energy efficiency in manufacturing environments.

Розвиток суспільства сильно залежить від енергії. Однак екстенсивне використання енергії викликає глобальні проблеми, такі як виснаження ресурсів і потепління клімату. Китай та Індія є типовими швидкозростаючими країнами, що розвива-ються, економічний прогрес в яких залежить від традиційного споживання енергії. Для реалізації бачення сталого розвитку цих держав необхідно вивчити економічну ефективність використання енергії цими націями. На основі аналізу тенденцій енергоспоживання та валового внутрішнього продукту в Китаї та Індії з 1990 по 2019 роки в цій статті обговорюються зміни індексу енергоспоживання на одиницю валового внутрішнього продукту. Автори дійшли висновку, що споживання енер-гії в Китаї та Індії здебільшого здіснюється промисловістю, житловим сектором і транспортом. Якщо аналізувати за типами ресурсів, Китай споживає переважно вугілля, нафтопродукти та електроенергію, тоді як Індія живиться здебіль-шого вугіллям, нафтопродуктами, біопаливом та відходами. Оскільки обидві країни переважно використовують вугілля та нафтопродукти, які належать до викопного палива, вони викидають велику кількість вуглекислого газу, що загрожує якості навколишнього середовища. Зважаючи на це, Китай та Індія повинні зосередитися на розвитку зеленої енергетики. Загальне споживання енергії в Китаї набагато більше, ніж в Індії, а валовий внутрішній продукт Китаю перевищує індійський. Однак енергоспоживання Китаю на одиницю валового внутрішнього продукту менше, ніж в Індії. Чим вище споживання енергії на одиницю валового внутрішнього продукту, тим більша залежність економічного розвитку країни від енергії. Тож пропозиції авторів полягають у стимулюванні розвитку невикопних джерел енергії та коригуванні енергетичного балансу досліджува-них країн, переробки твердих відходів та заохоченні торгівлі викидами, кліматичних інвестицій та фінансування в державах для досягнення цілей сталого розвитку. The development of society is highly dependent on energy. However, the extensive use of power causes global problems such as resource exhaustion and climate warming. China and India are typical fast-growing developing countries whose economic advancement relies on traditional energy consumption. To realize the vision of sustainable development for these states, it is necessary to study the nations' economic efficiency of power use. Based on the analysis of energy consumption and gross domestic product trends in China and India from 1990 to 2019, this paper discusses the changes in the energy consumption index per unit of gross domestic product. The authors concluded that the power consumption in China and India is mainly concentrated in the industry, residential, and transport sectors. Divided by resource types, the energy consumed by China comes primarily from coal, oil products, and electricity, while the power consumed by India is mainly from coal, oil products, biofuels and waste. Since both countries mostly use coal and oil products which belong to fossil fuels, they emit large amounts of carbon dioxide, endangering the environment quality. Given this, China and India should focus on green power development. China's total energy consumption is much larger than India's, and China's gross domestic product is much larger than India's. However, China's energy consumption per unit of gross domestic product is less than India's. The higher the energy consumption per unit of gross domestic product is, the higher the dependence of economic development on energy is. The authors' suggestions are to develop non-fossil energy sources and adjust the energy mix, recycle solid wastes, and encourage carbon trading, climate investment and financing in the states to reach sustainable development targets.

Relay node (RN) placement expands the network coverage and capacity and significantly reduces the energy consumption of heterogeneous networks (HetNets). Energy efficiency is the system design parameter in HetNets as it determines network operators' energy consumption and economic value. Relay is one of the energy-saving methods, where it can reduce the transmit power by breaking a long transmission distance into several short transmissions. However, placing an RN without a proper transmission distance may lead to a waste of energy. Thus, investigating an optimum RN placement in HetNets is crucial to ensure energy efficiency and maintain network performance. This paper presents an energy efficiency scheme for the RN based on four commonly used network topologies of indoor HetNets. The minimum energy consumption algorithm is proposed based on a comparison of distance and links of the RN. The results show that the circular network topology is an optimal network model with an efficiency factor increase of 6% that can be used to design the energy efficiency indoor HetNet.

The traditional sequential design of building elements, where every element performs only one dedicated function, carries significant embodied energy. Thus, modular pre-fabricated load-bearing elements could overcome the disadvantages of the current carbon-intensive construction practice and go beyond; as such, lightweight glass fiber-polymer composite profiles could be more advantageous in performance. Cellular structures of such profiles can be advantageous for adding water channels for active heating and cooling indoors and for fire protection. Therefore, the development of such a modular active building slab referred to as P-TACS (Prefabricated Thermally-Activated Fiber-Polymer Composite Slab) is explored in this work. The structural performance of a proposed P-TACS design is verified in terms of serviceability and ultimate limit states. The addition of local carbon fiber inclusions allows for an increase in the span of the slab to 10 m and a more uniform surface temperature. Thermal performance of the structurally optimized geometrical configuration is analyzed by, first of all, determining water parameters based on the 1D approach partially adopted from the standard radiant systems analysis and, secondly, by a detailed 2D thermal analysis using ANSYS Fluent numerical simulations. The hydraulic and thermal performance comparison of the novel P-TACS design with two standard radiant systems (ESS Type A and RCP) reveals that the P-TACS design outperforms the standard embedded surface system ESS Type A, both for floor heating and cooling case. In addition, the response time of P-TACS is three times faster compared to the ESS response time. The main advantage of the P-TACS is in lower mean water temperature, compared to traditional embedded radiant systems (e.g., EES type), required for conditioning the space, potentially resulting in lower operational energy use. The fire outbreak scenario is considered to complete the analysis, and the measures to switch water flow from nominal to fire scenario are proposed.

In this work, we assess the performance and energy efficiency of high-performance codes for the convolution operator, based on the direct, explicit/implicit lowering and Winograd algorithms used for deep learning (DL) inference on a series of ARM-based processor architectures. Specifically, we evaluate the NVIDIA Denver2 and Carmel processors, as well as the ARM Cortex-A57 and Cortex-A78AE CPUs as part of a recent set of NVIDIA Jetson platforms. The performance–energy evaluation is carried out using the ResNet-50 v1.5 convolutional neural network (CNN) on varying configurations of convolution algorithms, number of threads/cores, and operating frequencies on the tested processor cores. The results demonstrate that the best throughput is obtained on all platforms with the Winograd convolution operator running on all the cores at their highest frequency. However, if the goal is to reduce the energy footprint, there is no rule of thumb for the optimal configuration. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This research was funded by Project PID2020-113656RB-C21/C22 supported by MCIN/AEI/10.13039/501100011033. Manuel F. Dolz was also supported by the Plan Gen–T grant CDEIGENT/2018/014 of the Generalitat Valenciana. Héctor Martínez is a POSTDOC_21_00025 fellow supported by Junta de Andalucía. Adrián Castelló is a FJC2019-039222-I fellow supported by MCIN/AEI/10.13039/501100011033. Antonio Maciá is a PRE2021-099284 fellow supported by MCIN/AEI/10.13039/501100011033.

Automation and control systems are constantly evolving, using artificial intelligence techniques to implement new forms of control, such as fuzzy control, with advantages over classic control strategies, especially in non-linear systems. Water supply networks are complex systems with different operating configurations, uninterrupted operation requirements, equalization capacity and pressure control in the supply networks, and high reliability. In this sense, this work aims to develop a fuzzy pressure control system for a supply system with three possible operating configurations: a single motor pump, two motor pumps in series, or two motor pumps in parallel. For each configuration, an energy efficiency analysis was carried out according to the demand profile established in this case study. In order to validate the proposed methodology, an experimental water supply system was used, located in the Laboratory of Energy Efficiency and Hydraulics in Sanitation at the Federal University of Paraiba (LENHS/UFPB).

In this paper, we study the performance of reconfigurable intelligent surfaces (RISs) in a multicell broadcast channel (BC) that employs improper Gaussian signaling (IGS) jointly with non-orthogonal multiple access (NOMA) to optimize either the minimum-weighted rate or the energy efficiency (EE) of the network. We show that although the RIS can significantly improve the system performance, it cannot mitigate interference completely, so we have to employ other interference-management techniques to further improve performance. We show that the proposed NOMA-based IGS scheme can substantially outperform proper Gaussian signaling (PGS) and IGS schemes that treat interference as noise (TIN) in particular when the number of users per cell is larger than the number of base station (BS) antennas (referred to as overloaded networks). In other words, IGS and NOMA complement to each other as interference management techniques in multicell RIS-assisted BCs. Furthermore, we consider three different feasibility sets for the RIS components showing that even a RIS with a small number of elements provides considerable gains for all the feasibility sets., Accepted at IEEE Transactions on Signal Processing

One of the main causes of energy consumption in Internet of Vehicles (IoV) networks is an ill-designed network congestion control protocol, which results in numerous packet drops, lower throughput, and increased packet retransmissions. In IoV network, the objective to increase network throughput can be achieved by minimizing packets re- transmission and optimizing bandwidth utilization. It has been observed that the congestion control mechanism (i.e., the congestion window) can plays a vital role in mitigating the aforementioned challenges. Thus, this paper present a cross-layer technique to controlling congestion in an IoV network based on throughput and buffer use. In the proposed approach, the receiver appends two bits in the acknowledgment (ACK) packet that describes the status of the buffer space and link utilization. The sender then uses this information to monitor congestion and limit the transmission of packets from the sender. The proposed model has been experimented extensively and the results demonstrate a significantly higher network performance percentage in terms of buffer utilization, link utilization, throughput, and packet loss.

Edge computing aims to make internet-based services and remote computing power close to the user by placing information technology (IT) infrastructure at the network edges. This proximity provides data centers with low-latency and context-aware services. Edge computing power consumption is mainly caused by data centers, network equipment, and user equipment. With edge computing (EC), energy management platforms for residential, industrial, and commercial sectors are built. Energy efficiency is considered to be one of the key aspects of edge power constraints. This paper provides the state of the art of power consumption and energy management for edge computing, the computation offloading methods, and more important highlights the power efficiency of edge computing systems. Furthermore, renewable energy and related concepts will also be explored and presented since no human participation is required in replacing or recharging batteries when using such energy sources. Based on such study, a recommendation is to develop a dynamic system for energy management in real-time with the assessment of local renewable energy so that the system be reliable with minimum power consumption. Also, regarding energy management, we recommend providing backup energy sources (or using more than one energy source) or (a hybrid technique).

The hydroxyl radical is the most powerful oxidant after fluorine, and is the key reactant of theadvanced oxidation processes AOP. Monitoring the kinetics of formation and reaction of this short life speciesis one of the challenging tasks from an experimental point of view. Thus, modelling is suggested to be oneefficient tool for a comprehensive and predictive study of AOPs, particularly the Galvano-Fenton process. In thepresent study, mathematical modelling is used to describe the kinetics of hydroxyl radical 𝐻𝑂• generation andorganic substrate 𝑅𝑂 degradation within the Galvano-Fenton process, based on the spontaneous galvaniccorrosion of iron waste and in situ ferrous ion catalyst generation. A range of typical absolute kinetic constantsof 106 à 1010 M-1.s-1 is considered to characterize the attack of 𝑅𝑂 species by 𝐻𝑂•. Phenol is presented as amodel pollutant for a total mineralization model. The numerical simulations demonstration a quasi-linearevolution of hydroxyl radical production during the first stage of the Galvano-Fenton process. A comparison ofthe Galvano-Fenton process with the classic Fenton in terms of kinetics, and electro-Fenton in terms ofenergetic performance, revealed that the spontaneous galvanic generation of ferrous ions in the Galvano-Fentonprocess leads to a higher rate of the reaction a higher instantaneous concentration of ferric ions accompanyingthe release of hydroxyl radicals and hence a better oxidation efficiency, as well as a positive energy balance. Aparticular attention was given to the ratio of the degradation efficiency to the released energy.

Türkiye’deki ticari yapılar arasında %35’lik oranla en yüksek enerji tüketimine sahip olan otel binalarında, enerji verimliliği potansiyelinden istifade edilmesi, sürdürülebilir enerji kullanımı için bir gereklilik haline gelmiştir. Bu çalışmada, enerji verimliliğini iyileştirmeye yönelik altı farklı yöntem için elektrik tüketiminden elde edilebilecek tasarruf miktarları, Antalya ilindeki 5 yıldızlı anonim bir otel için hesaplanarak kıyaslanmıştır. Antalya ili, turizm tesis sayısının fazlalığı ile enerji verimliliği konusunda yüksek bir potansiyele sahiptir. Analiz edilen yöntemlerin anonim otelde uygulanması halinde, yaklaşık olarak 300,000 TL ile 4,405,000 TL arasında tasarruf edilebileceği belirlenmiştir. Ön görülen tasarruf miktarının en iyi durumda 4 milyon TL’nin üzerinde olduğu düşünüldüğünde, otelin yaklaşık olarak 11 milyon TL olan aylık toplam elektrik giderinin yarı yarıya azaltılabileceğini söylemek mümkündür. Mevcut çalışmada farklı yaklaşımlardan elde edilebilecek tasarruf miktarları, potansiyel uygulamalar öncesinde yol gösterici olması amacıyla karşılaştırılmıştır. Her bir yaklaşımın ilk yatırım ve işletme maliyetleri birbirinden farklı olduğu için geri ödeme sürelerine bağlı olarak elde edilecek ekonomik fayda yerine muhtemel tasarruf miktarlarına odaklanılmıştır., The utilization of energy efficiency potential in hotel buildings, which has the highest energy consumption rate of 35% among commercial buildings in Turkey, is essential for sustainable energy use. In this study, the savings that can be obtained from electricity consumption for six different methods to improve energy efficiency were calculated and compared for a 5-star anonymous hotel in Antalya. Antalya province has great potential in terms of energy efficiency with a high number of tourism facilities. It has been determined that approximately 300,000 TL to 4,405,000 TL can be saved if the analyzed methods are applied in the anonymous hotel. Considering that the anticipated savings are above 4 million TL in the best case, it is possible to say that the monthly total electricity cost of the hotel, which is approximately 11 million TL, can be reduced by half. In the current study, the amount of savings that can be obtained from different approaches is compared to guide future applications. Since the initial investment and operating costs of each approach are different from each other, the focus is on possible savings instead of economic benefits that depend on payback periods.

Producción Científica, Input–output tables (IOTs) provide a relevant picture of economic structure as they represent the composition and interindustry relationships of an economy. The technical coefficients matrix (A matrix) is considered to capture the technological status of an economy; so, it is of special relevance for the evaluation of long-term, structural transformations, such as sustainability transitions in integrated assessment models (IAMs). The A matrix has typically been considered either static or exogenous. Endogenous structural change has rarely been applied to models. The objective of this paper is to analyze energy intensity, a widely used variable in IAMs, and its role as a driver of structural change. We therefore identify the most relevant technical coefficients in the IOTs time series and estimate an econometric model based on the energy intensity of five different final end-use energy sources. The results of this analysis show that energy intensity has a significant influence on the evolution of the A matrix and should therefore be taken into consideration when analyzing endogenous structural change in models., Ministerio de Asuntos Económicos y Transformación Digital, project MODESLOW (grant ECO2017-85110-R), European Union’s Horizon 2020 research and innovation program. Project “Low Carbon society: An enhanced modelling tool for the transition to sustainability (LOCOMOTION) grant award H2020-LC-CLA-01-2018, n. 821105

In today’s environment of increasing pressure to reduce fuel consumption and emissions of carbon dioxide (CO2) and nitrogen oxides (NOx), the LNG (Liquefied Natural Gas) transportation industry is growing in size and influence. In this context, further efforts are needed to improve the energy efficiency of LNG marine energy power plant. The LNG vessels and their equipment considered in this study have different power consumption requirements depending on the vessel’s mode of operation (loading/unloading, maneuvering, anchoring, at sea, etc.). For each ship mode, where the power plant requirements are the same, the specific fuel consumption (SFOC) and exhaust emissions, NOx and CO2, are compared with a different number of engines in the network to find the optimal number of engines in the network, considering both the safety aspect and the port requirements. An analysis was performed showing the efficiency of the on-board power management system (PMS) in terms of manual load sharing between engines. A comprehensive analysis of the data and its comparison led to the conclusion that the manual distribution of power among the engines is the slightly better solution. The obtained results show that further analysis of the number of engines for a given load with minimum fuel consumption and CO2 and NOx emissions is required.

Thermal energy storage systems are systems that can be an alternative to the systems used especially in residential heating in our country. These systems are systems that reduce CO2 emissions, are efficient and can reduce consumption by shifting electricity demand to night. In this study, the ten-year price changes of the fuels used for heating in our country, the change in the real electricity consumption of a province over time, the electricity tariffs were examined and cost calculations were made in case of heating a space. It is seen that fuel prices have increased significantly in recent years, and thermal energy storage systems (TES) are 20-40% less costly than other systems until 2020, and 40-55% less costly than natural gas in 2021 and 2022.

Background. Peculiarities of the workload in a modern information and communication network (ICN) determine specific requirements for energy efficiency, performance and availability of its processing system. Existing approaches to increase en ergy efficiency and performance of workload processing do not take into account the possibility of dynamic changes in ICN workload arrival rate and individual energy consumption characteristics of computing nodes of the system. Objective. The purpose of the paper is to increase the energy efficiency and performance of ICN workload processing while meeting the requirements for the availability of the processing system, taking into account dynamic changes in the input workload arrival rate and the individual characteristics of the computing nodes’ energy consumption. Methods. A mathematical model of the workload processing system was built using the queueing theory methods, and an ontological model of this system was built using intelligent data analysis methods, which made it possible to quantitatively and qualitatively describe the complex relationships between system parameters and workload processing efficiency indicators. On the basis of the built models, a comprehensive method of energy-efficient workload processing was proposed, which differs from the known ones by the use of individual energy consumption models of computing nodes, combining the advantages of horizontal scaling and energy-efficient scheduling taking into account dynamic changes in workload arrival rate. Results. The efficiency of ICN workload processing is increased by 15.722% according to the efficiency criterion, which includes energy efficiency and performance indicators, compared to the known energy-efficient Backfill approach while meet ing the requirements for the availability of the processing system. Conclusions. The energy efficiency, performance and availability of the ICN workload processing system can be improved by combining horizontal scaling and energy-efficient scheduling approaches using individual energy consumption models of computing nodes and taking into account dynamic changes in the input workload arrival rate. Проблематика. Особливості навантаження сучасної інформаційно-комунікаційної мережі (ІКМ) визначають специфічні вимоги щодо енергоефективності, продуктивності та доступності систем його обслуговування. Існуючі підходи щодо підвищення енергоефективності та продуктивності обслуговування навантаження не враховують можливості динамічних змін інтенсивності навантаження в мережі та індивідуальних характеристик енергоспоживання окремих обчислювальних вузлів системи. Мета досліджень. Підвищення енергоефективності та продуктивності обслуговування навантаження ІКМ при забезпеченні вимог щодо доступності системи обслуговування з урахуванням динамічних змін інтенсивності вхідного навантаження та індивідуальних характеристик енергоспоживання обчислювальних вузлів. Методика реалізації. Побудовано математичну модель системи обслуговування навантаження із застосуванням методів теорії масового обслуговування, а також онтологічну модель цієї системи із застосуванням методів інтелектуального аналізу даних, що дозволило кількісно та якісно описати складні зв’язки між параметрами системи та показниками ефективності обслуговування навантаження. На основі побудованих моделей запропоновано комплексний метод енергоефективного обслуговування навантаження, що відрізняється від відомих використанням індивідуальних моделей енергоспоживання обчислювальних вузлів системи, поєднанням переваг підходів горизонтального масштабування та енергоефективного планування навантаження з урахуванням динамічних змін інтенсивності навантаження. Результати досліджень. Ефективність обслуговування навантаження ІКМ підвищено на 15,722% за критерієм ефективності, який включає показники енергоефективності та продуктивності, у порівнянні з відомим енергоефективним підходом Backfill при дотриманні вимог щодо доступності системи обслуговування. Висновки. Енергоефективність, продуктивність та доступність системи обслуговування навантаження ІКМ може бути покращено за рахунок поєднання підходів горизонтального масштабування та енергоефективного планування задач із використанням індивідуальних моделей енергоспоживання обчислювальних вузлів та при врахуванні динамічних змін інтенсивності вхідного навантаження.

Suburban neighbourhoods pose challenges to decarbonisation, due to high car-dependency and relatively large and energy inefficient homes. Home ownership dominates suburbia, thus putting responsibility on households to adopt measures to decarbonise their domestic lives and transportation. This paper examines household perspectives on the feasibility of such measures. We ran a survey and focus groups in Perth (Scotland) during the energy crisis. Whilst we found high levels of concern about climate change, energy costs, and growing engagement with cleaner technologies (e.g. heat pumps), most residents felt decarbonisation options were limited. Barriers like technologies’ up-front costs, worsened with the cost of living crisis. Participants had low familiarity with sharing economy approaches like car clubs. Despite high (non-electric) bike ownership and prevalence of storage space (garages), cycling was more perceived as a leisure activity than a regular transport mode. There were shared views that the state should take a stronger role in coordinating and implementing systemic changes required for energy transition, including measures affecting residents directly, like reducing car traffic into the city centre. We conclude that despite the economic privilege of high home and car ownership in suburbia, few felt financially able to decarbonise and most seem locked into high-carbon suburban lifestyles.

Kiln geometries were developed to reach homogeneous temperatures above 900 °C, during the firing process, aiming to improve the production process of the ceramists from Vale do Jequitinhonha (MG/Brazil). Techniques of reactive flow numerical solution using the software Ansys CFX have been used to foresee the behavior of the firings. Two types of catenary geometries, simple and robust, were studied, capable of being easily reproduced. The firewood used as an energy source in the current kilns and the developed ones, in this research project, favored the control of the kiln’s atmosphere during the firing, beyond being a source found with easiness for the ceramists. The results of the numerical simulations demonstrated the energy efficiency of the kilns and the level of temperature reached. Knowing well thermal and gas dynamic behavior, some parameters of the burning could be improved, aiming for a better quality of used ceramics.

Energy efficiency is a critical issue in the management and operation of cloud data centers, which form the backbone of cloud computing. Virtual machine (VM) placement has a significant impact on energy-efficiency improvement for virtualized data centers. Among various methods to solve the VM-placement problem, the genetic algorithm (GA) has been well accepted for the quality of its solution. However, GA is also computationally demanding, particularly in the computation of its fitness function. This limits its application in large-scale systems or specific scenarios where a fast VM-placement solution of good quality is required. Our analysis in this paper reveals that the execution time of the standard GA is mostly consumed in the computation of its fitness function. Therefore, this paper designs a data structure extended from a previous study to reduce the complexity of the fitness computation from quadratic to linear one with respect to the input size of the VM-placement problem. Incorporating with this data structure, an alternative fitness function is proposed to reduce the number of instructions significantly, further improving the execution-time performance of GA. Experimental studies show that our approach achieves 11 times acceleration of GA computation for energy-efficient VM placement in large-scale data centers with about 1500 physical machines in size.

International audience; This work focuses on evaluating the potential of variable speed limits (VSLs) in a synthetic urban network to improve both environmental sustainability and traffic performance. The traffic system is modeled using the microscopic traffic simulator SUMO, and a physical fuel consumption and NOx emission model is used to assess the vehicles' energy efficiency. Speed limits are controlled through a nonlinear model predictive control (NMPC) approach, in which the traffic evolution and fuel consumption are respectively predicted with a macroscopic traffic model, namely the cell transmission model (CTM), and a pre-calibrated artificial neural network (ANN). The results reveal that in transient phases between different levels of congestion, the proposed eco-VSL controller is faster to decongest the network, resulting in an improvement of the environmental sustainability and the traffic performance both in the controlled network, and at its boundary roads.

An extensive, representative, and, multi-country tailored survey questionnaire eliciting social practices with heat as an energy service and the relative perceptions about heating devices was submitted to a randomized sample of more than 6,000 potential end-users in Europe within the framework of the Horizon 2020 project SWS-HEATING. The project is developing an innovative seasonal thermal energy storage unit for residential use. Moreover, within the project, the role of occupancy variability and use conditions in the performance of the proposed system is assessed. The present study focuses on tailor-made user-building interaction models to be implemented into dynamic simulation for the assessment of the proposed and similar systems starting from the sociological assessment of such large-scale survey results. These models take advantage from the knowledge raised by the findings of the social survey to frame for the first time occupants’ behavior scenarios representative of South, central, and North European countries. In this way, the influence of cultural context and demographic factors and their relation to heating practices are considered when developing these tailored occupant behavior models. Results show the non-negligible influence (up to 43% in the coldest climate) of implementing these models on predicted building heating energy needs, as quantitative demonstration of the role of societal-related variables on final energy use estimation.

Sensor nodes in wireless sensor networks (WSN) are used for perceiving, monitoring, and controlling a wide range of applications. Owing to the small size of sensor nodes and limited power sources, energy saving is critical for ensuring network longevity. Protocols in different layers consume energy for their function. It is possible to significantly reduce energy usage by including energy-efficiency measures in the protocol design. Most protocols in the literature focus on the energy efficiency in individual layers. Recent studies have shown that cross-layer designs are more energy efficient than individual layer designs. Therefore, this study presents a cross-layer protocol design that combines network and data link layers to minimize energy consumption. This article proposes a novel "Quality of Service Based Cross-layer (QSCL) Protocol" by combining the IEEE 802.15.4-based MAC protocol and the LEACH-based routing protocol. The dynamic duty cycle of the IEEE 802.15.4 protocol was modified based on the amount of data present in the node, which minimized the energy consumption of the data-transfer mechanism. The cluster head (CH) selection of the LEACH-based protocol was modified to consider the average residual energy (RE) of the nodes and their distance from the sink. This helps preserve the energy in the CH, thereby extending the network lifetime. Simulation studies demonstrated that the proposed QSCL outperformed the existing protocols by prolonging the network lifetime.

The paper presents a two-dimensional numerical investigation of a solar chimney combined with an absorbing capacity wall in a building’s south façade. The analysis was carried out in Aversa (Italy), in July and December, from sunrise to sunset. The chimney is made up of a converging channel, a vertical absorbing wall, and a two-degree angled glass plate. It is 5.0 m tall, while the height of the channel is 4.0 m, with an inlet of 0.34 m and an outlet portion of 0.20 m. A phase change material with metal foam makes up the thermal energy storage system. Four possible configurations are investigated to identify the ideal hybrid system arrangement in terms of thermal performance; the commercial code Ansys-Fluent is used to solve the problem. The results of the thermal energy storage system with metal foam and PCM are provided in terms of liquid fractions, stored energy, and stream function fields, while the ones of the wall temperature distributions in the channel are reported. Thermal and fluid dynamics behaviours are so evaluated to have some useful indications to improve the system.

The building sector is responsible for a significant amount of energy consumption and greenhouse gas (GHG) emissions. Thus, the monitoring, control and optimization of energy consumption in buildings will play a critical role in the coming years in improving energy efficiency in the building sector and in reducing greenhouse gas emissions. However, while there are a significant number of studies on how to make buildings smarter and manage energy through smart devices, there is a need for more research on integrating buildings with legacy equipment and systems. It is therefore vital to define mechanisms to improve the use of energy efficiency in existing buildings. This study proposes a new architecture (PHOENIX architecture) for integrating legacy building systems into scalable energy management systems with focus also on user comfort in the concept of interoperability layers. This interoperable and intelligent architecture relies on Artificial Intelligence/ Machine Learning (AI/ML) and Internet of Things (IoT) technologies to increase building efficiency, grid flexibility and occupant well-being. To validate the architecture and demonstrate the impact and replication potential of the proposed solution, five demonstration pilots have been utilized across Europe. As a result, by implementing the proposed architecture in the pilot sites, 30 apartments and four commercial buildings with more than 400 devices have been integrated into the architecture and have been communicating successfully. In addition, six Trials were performed in a commercial building and five key performance indicators (KPIs) were measured in order to evaluate the robust operation of the architecture. Work is still ongoing for the trials and the KPIs’ analysis after the implementation of PHOENIX architecture at the rest of the pilot sites.

Актуальность исследования заключается в необходимости повышения энергоэффективности добычи нефти на месторождениях, находящихся на поздних стадиях работки. Сущность работы заключается в интеграции периферийного нефтепромыслового оборудования, в том числе замерных установок, устройств по борьбе с отложениями, в единую со скважинами систему - интеллектуальную станцию управления. В настоящее время динамика работы скважин не влияет на параметры работы данных установок. При их интеграции в систему и написании соответствующих алгоритмов возможно увеличение энергоэффективности добычи нефти, снижение затрат на обслуживание скважин и, в перспективе, интеллектуализацию их работы. Цель: определить алгоритмы регулирования периферийного оборудования, работу которого можно оптимизировать на основании динамики изменения параметров работы нефтедобывающей скважины. Методы: гидравлическое моделирование работы куста скважин, численное определение напорной характеристики скважины, обзор научных источников и анализ параметров борьбы с органическими отложениями. Результаты. Приведены сценарии оптимизации работы нефтедобывающих скважин при интеграции в интеллектуальную станцию управления периферийных устройств. Так, интеграция устьевого блока подачи реагента, устройства очистки лифтовой колонны или станции управления греющего кабеля, при идентификации образования парафиновых отложений, может изменить режим работы, что позволит оптимизировать процессы борьбы с отложениями и увеличить межочистной период скважины. Расчет изменения устьевых давлений при значительном кратковременном изменении дебита одной или нескольких скважин позволит изменить диаметр штуцера на скважине, что сохранит точку пересечения напорной характеристики скважины и характеристики электроцентробежного насоса. Согласно технологическому расчёту, это позволит избежать нестабильной работы насоса и сохранить оптимальное значение коэффициента полезного действия, падение которого может превышать 2 %. Третий алгоритм описывает способ снижения затрат инженерно-технического персонала на обслуживание скважин при получении некондиционных данных дебита. При их получении предлагается запуск алгоритма оценки дебита скважины по косвенным данным - технология «Виртуальный расходомер». По результатам проверки система автоматически запустит повторный замер или сообщит инженерно-техническому персоналу о нарушениях в работе глубинно-насосного оборудования. Выводы. Полученные алгоритмы могут быть интегрированы в станции управления. Это обеспечит оптимизацию работы глубинно-насосного оборудования, увеличение межочистного периода скважины, а также снизит затраты времени инженерно-технического персонала на обслуживание скважин. Все представленные алгоритмы способны увеличить энергоэффективности добычи нефти, что является важной задачей при разработке месторождений на поздних стадиях. The relevance of the study lies in the need to improve the energy efficiency of oil production in fields that are in the late stages of development. The essence of the work lies in the integration of peripheral oilfield equipment, including metering units, sediment control devices, into a single system with wells - an intelligent control station. Currently, the dynamics of well operation does not affect the operation parameters of these units. When they are integrated into the system and the corresponding algorithms are written, it is possible to increase the energy efficiency of oil production, reduce the cost of well maintenance and, in the future, intellectualize their work. Purpose: to determine the control algorithms for peripheral equipment, the operation of which can be optimized based on the dynamics of changes in the parameters of the operation of an oil well. Methods: hydraulic modeling of a well cluster operation, numerical determination of a well pressure characteristic, review of scientific sources and analysis of parameters for combating organic deposits. Results. The paper introduces the scenarios for optimizing the operation of oil wells when integrating peripheral devices into an intelligent control station. Thus, the integration of a wellhead reagent supply unit, a tubing string cleaning device or a heating cable control station, upon identification of the formation of paraffin deposits, can change the operating mode, which will allow optimizing the processes of controlling deposits and increasing the cleanup period of the well. Calculation of the change in wellhead pressure, with a significant short-term change in the flow rate of one or several wells, will allow changing the diameter of the choke in the well, which will save the intersection point of the pressure characteristic of the well and the characteristics of the electric submersible pump. According to the technological calculation, this will avoid unstable operation of the pump and maintain the optimal value of the efficiency factor, the drop of which can exceed 2 %. The third algorithm describes a way to reduce the cost of engineering and technical personnel for well maintenance when receiving substandard production data. When they are received, it is proposed to launch an algorithm for estimating the well flow rate based on indirect data - the «Virtual Flow Meter» technology. Based on the results of the check, the system will automatically start a re-measurement or inform the engineering and technical staff about violations in the operation of the downhole pumping equipment. Conclusions. The resulting algorithms can be integrated into control stations. This will optimize the operation of downhole pumping equipment, increase the cleanup period of the well, and also reduce the time spent by engineering and technical personnel on well maintenance. All presented algorithms are able to increase the energy efficiency of oil production, which is an important task in the development of deposits at later stages.

This version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post- acceptance improvements, or any corrections. The Version of record can be accessed at: https://rdcu.be/c99WF &nbsp

Fenestrations of the buildings are playing an important role in the building’s energy efficiency for the tropical climate. The energy that comes from the glass window into the building can be restricted by providing shading on the windows. So, to provide the shading on the window, the most common way is fixed shade like overhang and fin. Shading devices are very helpful to control the SHGC and light transmittance through the fenestrations of the building. Most of the studies analyze the impact of WWR, shadings, and SHGC on a building’s energy demand but did not consider the combined effect of these parameters. By considering all the parameters of the building envelope in the analysis like WWR, orientation, shading devices, projection factor, and type of glass, the energy demand in the building can be significantly reduced. The goal of this paper is to analyze the variation of residential envelope transmittance value with the window-wall ratio, projection factor, and fixed shading devices and also to optimize the energy from building envelope elements in residential buildings using a statistical method, namely the Taguchi method. The transmittance of energy through the building envelope is calculated in 8 cardinal directions by providing shading with the fin and overhang. Based on the result, the optimum energy saving achieved by selecting the optimum combination of the process parameters for minimizing the energy from the building envelope is A1B1C3D2 i.e. window to wall ratio 7%, triple glazing type of glass used, shading with the overhang fin, and orientation in the west direction. The result shows the most significant factor among the selected parameter is the window to wall ratio. Also, by focusing on the building envelope parameters, an architectural designer may reduce the building energy demand significantly and offer more alternatives to achieve energy-efficient buildings.

Recent improvements in nanotechnology and Internet of Things (IoT) have led to the emergence of the concept of Internet of Nano-Things (IoNT). This concept provided ease of access and communication facilities for the nano-devices in applications of different fields operating at the molecular level such as health, industry, agriculture, robotics and military. These distributed devices interconnect over the Wireless Nano-Sensor Networks (WNSNs) in nano-scale which have limited energy and capacity. Therefore, these devices need to use their energy efficiently when communicating with each other to ensure network continuity and maintain all processes of IoNT applications. In this paper, a novel energy-efficient distributed routing algorithm, namely DEEPNT, is proposed in order to extend the lifetime of WNSNs in IoNT applications. The communication backbone of WNSNs constructed by DEEPNT by selecting cluster head nodes can be used in all types of IoNT applications in nano-scale in order to provide continuous data flow in critical areas such as healthcare running in vivo. This novel energy-efficient distributed protocol is compared with the traditional flooding based method and with an energy aware routing algorithm. According to the results, DEEPNT prolongs the WNSNs average lifetime respectively up to 10.78 and 5.95 times compared to mentioned algorithms despite the larger network sizes in nano-scale. © 2022 Elsevier B.V.

Decarbonizing the national energy system by increasing the amount of non‐conventional renewable resources (NCRRs) is one of the strategies of the Colombian government to meet the compromises declared in the last conference of the parties (COP 26) (Glasgow 2021). Concretely, it is expected that at the end of 2023, the shares of NCRRs in the power grid will increase from

Cloud computing is formally known as an Internet-centered computing technique used for computing purposes in the cloud network. It must compute on a system where an application may simultaneously run on many connected computers. Cloud computing uses computing resources to achieve the efficiency of data centres using the virtualization concept in the cloud. The load balancers consistently allocate the workloads to all the virtual machines in the cloud to avoid an overload situation. The virtualization process implements the instances from the physical state machines to fully utilize servers. Then the dynamic data centres encompass a stochastic modelling approach for resource optimization for high performance in a cloud computing environment. This paper defines the virtualization process for obtaining energy productivity in cloud data centres. The algorithm proposed involves a stochastic modelling approach in cloud data centres for resource optimization. The load balancing method is applied in the cloud data centres to obtain the appropriate efficiency.

This article explains the necessity of complex energy audit as an alternative for another approaches to their technical and economical indicators improvement. By authors estimation, latest 20 years there weren’t nor new facility launches neither research on existing ones (at least open public). The article proves that using limited financial resources for facilities modernization, external complex examination (audit) is systematized, controlled and profitable way to prolong energy equipment use or to justify its’ replacement. While any regulation rules for HES energy audit services are absent, such activities’ reliability straightly depend on customers’ and executants’ mutual clarity. Further there are requirements for HES energy audit Customers and Executants defined as far as general methodology approaches and typical energy audit (chronological) order. Also the article suggests that success of Ukrainian HES modernization strongly depends on sectoral-level energy business clarity and demonopolization., В этой статье обосновывается необходимость проведения комплексного энергоаудита ТЕС, как альтернативы другим подходам к улучшению технико-экономических показателей. Оценивая состояние украинской тепловой энергетики, авторы отмечают, что в течение последних двух десятилетий новые мощности фактически не запускались в эксплуатацию, а действующие - тщательно не исследовались (по крайней мере, открыто и публично). В статье обобщается опыт проведения энергетического аудита энергохозяйств промышленных предприятий и инфраструктурных объектов. Доказывается, что в условиях ограниченных финансовых ресурсов на модернизацию промышленных объектов, внешнее комплексное обследование (аудит) - один из системных, контролированных, действенных способов продолжения сроков эксплуатации энергетического оборудования или его обоснованной замены. При отсутствии регламентированных правил на рынке услуг по энергоаудиту ТЭС, выгоды от результатов такой деятельности возможны только при условии прозрачных действий Заказчика и Исполнителя. На основе практического опыта определены требования к Заказчику и Исполнителю энергоаудита ТЭС, представлены общие методологические подходы и порядок энергетического аудита, а также предполагается, что успешная модернизация украинских ТЭС может быть реализована при условии прозрачности и демонополизации в отрасли., У цій статті обґрунтовується необхідність проведення комплексного енергетичного аудиту ТЕС, як альтернативі іншим підходам щодо покращення техніко-економічних показників. Оцінюючи стан української теплової енергетики, автори відзначають, що упродовж останніх двох десятиріч нові потужності фактично не запускалися в експлуатацію, а існуючі - ретельно не досліджувалися (принаймні, відкрито та публічно). В статті узагальнюється досвід проведення енергетичного аудиту енергогосподарств промислових підприємств та інфраструктурних об'єктів. Доводиться, що в умовах обмежених фінансових ресурсів на модернізацію промислових об’єктів, зовнішнє комплексне обстеження (аудит) є одним з системних, контрольованих, дієвих способів подовження /термінів експлуатації енергетичного обладнання або його обґрунтованої заміни За відсутності регламентованих правил на ринку послуг з енергоаудиту ТЕС, вигоди від результатів такої діяльності можливі лише за умов прозорих дій Замовника й Виконавця. На підставі практичного досвіду визначено вимоги щодо Замовників та Виконавців енергоаудиту ТЕС, представлені загальні методологічні підходи та порядок енергетичного аудитування, а також припускається, що успішна модернізація українських ТЕС може бути реалізована лише за умов прозорості та демонополізації у галузі.

This paper presents a novel approach to distinguishing driving styles with respect to their energy efficiency. A distinct property of our method is that it relies exclusively on the global positioning system (GPS) logs of drivers. This setting is highly relevant in practice as these data can easily be acquired. Relying on positional data alone means that all features derived from them will be correlated, so we strive to find a single quantity that allows us to perform the driving style analysis. To this end we consider a robust variation of the so-called "jerk" of a movement. We give a detailed analysis that shows how the feature relates to a useful model of energy consumption when driving cars. We show that our feature of choice outperforms other more commonly used jerk-based formulations for automated processing. Furthermore, we discuss the handling of noisy, inconsistent, and incomplete data, as this is a notorious problem when dealing with real-world GPS logs. Our solving strategy relies on an agglomerative hierarchical clustering combined with an L-term heuristic to determine the relevant number of clusters. It can easily be implemented and delivers a quick performance, even on very large, real-world datasets. We analyse the clustering procedure, making use of established quality criteria. Experiments show that our approach is robust against noise and able to discern different driving styles.

The heterogeneity of historic buildings and environmental conditions, as well as the variety of possible technical solutions, introduce great challenges to the decision-making process for the definition and implementation of energy retrofit projects. The variety of stakeholders involved in the process, each bringing specific skills and goals, further add to this complexity. How can the decision be finalised when multiple and often conflicting objectives and different stakeholders are involved?In this context, the European Standard EN 16883:2017 provides guidelines to improve the energy performance of historic buildings while respecting their heritage significance. It presents a normative working procedure to select conservation-compatible retrofit solutions, which is based on a step-by-step investigation, analysis and documentation of the building. However, the recommendations provided in the Standard remain at a general level and it is the task for the stakeholders to tailor the intervention to the specific case.This paper investigates how the implementation of the EN 16883:2017 can be enabled by adopting a selection of existing computer-based tools to support the identification, assessment, and selection of retrofit solutions in historic buildings. To this end, a number of tools were analysed, highlighting their advantages, input data, outcomes and main limitations, in relation to their possible use in support of the implementation of the Standard procedure (or steps of it). The heterogeneity of historic buildings and environmental conditions, as well as the variety of possible technical solutions, introduce great challenges to the decision-making process for the definition and implementation of energy retrofit projects. The variety of stakeholders involved in the process, each bringing specific skills and goals, further add to this complexity. How can the decision be finalised when multiple and often conflicting objectives and different stakeholders are involved?In this context, the European Standard EN 16883:2017 provides guidelines to improve the energy performance of historic buildings while respecting their heritage significance. It presents a normative working procedure to select conservation-compatible retrofit solutions, which is based on a step-by-step investigation, analysis and documentation of the building. However, the recommendations provided in the Standard remain at a general level and it is the task for the stakeholders to tailor the intervention to the specific case.This paper investigates how the implementation of the EN 16883:2017 can be enabled by adopting a selection of existing computer-based tools to support the identification, assessment, and selection of retrofit solutions in historic buildings. To this end, a number of tools were analysed, highlighting their advantages, input data, outcomes and main limitations, in relation to their possible use in support of the implementation of the Standard procedure (or steps of it).

This brief presents a 10.5-bit 10 MS/s successive-approximation-register (SAR) analog-to-digital converter (ADC) with 1.5times input range (IR). By pre-setting and resetting the most significant bit (MSB) of the digital-to-analog converter (DAC) to shift the input signal accordingly, the input range of the ADC is enhanced by a factor of 1.5. This effectively relaxes the noise requirement and thus improves the power efficiency of the ADC. The prototype implemented in 65-nm CMOS technology achieves a signal-to-noise-and-distortion ratio (SNDR) of 60.37 dB and a spurious-free dynamic range (SFDR) of 82.2 dB. It consumes 18.65~mu text{W} at 10 MS/s with a 0.8V supply and only occupies an area of 0.0013 mm2. The resulting Walden figure of merit (FoM _{W} ) is 2.2 fJ/conversion-step.

International audience; Unmanned Aerial Vehicles (UAVs) have attracted much attention lately and are being used in a multitude of applications. But the duration of being in the sky remains to be an issue due to their energy limitation. In particular, this represents a major challenge when UAVs are used as base stations (BSs) to complement the wireless network. Therefore, as UAVs execute their missions in the sky, it becomes beneficial to wirelessly harvest energy from external and adjustable flying energy sources (FESs) to power their onboard batteries and avoid disrupting their trajectories. For this purpose, wireless power transfer (WPT) is seen as a promising charging technology to keep UAVs in flight and allow them to complete their missions. In this work, we leverage a multi-agent deep reinforcement learning (MADRL) method to optimize the task of energy transfer between FESs and UAVs. The optimization is performed by carrying out three essential tasks: (i) maximizing the sum-energy received by all UAVs based on FESs using WPT, (ii) optimizing the energy loading process of FESs from a ground BS, and (iii) computing the most energy-efficient trajectories of the FESs while carrying out their charging duties. Furthermore, to ensure highlevel reliability of energy transmission, we use directional energy transfer for charging both FESs and UAVs by using laser beams and energy beam-forming technologies, respectively. In this study, the simulation results show that the proposed MADRL method has efficiently optimized the trajectories and energy consumption of FESs, which translates into a significant energy transfer gain compared to the baseline strategies.

Preserving energy in households and office buildings is a significant challenge, mainly due to the recent shortage of energy resources, the uprising of the current environmental problems, and the global lack of utilizing energy-saving technologies. Not to mention, within some regions, COVID-19 social distancing measures have led to a temporary transfer of energy demand from commercial and urban centers to residential areas, causing an increased use and higher charges, and in turn, creating economic impacts on customers. Therefore, the marketplace could benefit from developing an internet of things (IoT) ecosystem that monitors energy consumption habits and promptly recommends action to facilitate energy efficiency. This paper aims to present the full integration of a proposed energy efficiency framework into the Home-Assistant platform using an edge-based architecture. End-users can visualize their consumption patterns as well as ambient environmental data using the Home-Assistant user interface. More notably, explainable energy-saving recommendations are delivered to end-users in the form of notifications via the mobile application to facilitate habit change. In this context, to the best of the authors' knowledge, this is the first attempt to develop and implement an energy-saving recommender system on edge devices. Thus, ensuring better privacy preservation since data are processed locally on the edge, without the need to transmit them to remote servers, as is the case with cloudlet platforms., 10 pages, 9 figures, 5 tables, IEEE Systems Journal, 2021

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. With adverse industrial effects on the global landscape, climate change is imploring the global economy to adopt sustainable solutions. The ongoing evolution of energy efficiency targets massive data collection and Artificial Intelligence (AI) for big data analytics. Besides, emerging on the Internet of Energy (IoE) paradigm, edge computing is playing a rising role in liberating private data from cloud centralization. In this direction, a creative visual approach to understanding energy data is introduced. Building upon micro-moments, which are time-series of small contextual data points, the power of pictorial representations to encapsulate rich information in a small twodimensional (2D) space is harnessed through a novel Gramian Angular Fields (GAF) classifier for energy micro-moments. Designed with edge computing efficiency in mind, current testing results on the ODROID-XU4 can classify up to 7 million GAF-converted data points with ~90% accuracy in less than 30 sec, paving the path towards industrial adoption of edge IoE.

In a system with energy-constrained sensors, each transmitted observation comes at a price. The price is the energy the sensor expends to obtain and send a new measurement. The system has to ensure that sensors' updates are timely, i.e., their updates represent the observed phenomenon accurately, enabling services to make informed decisions based on the information provided. If there are multiple sensors observing the same physical phenomenon, it is likely that their measurements are correlated in time and space. To take advantage of this correlation to reduce the energy use of sensors, in this paper we consider a system in which a gateway sets the intervals at which each sensor broadcasts its readings. We consider the presence of battery-powered sensors as well as sensors that rely on Energy Harvesting (EH) to replenish their energy. We propose a Deep Reinforcement Learning (DRL)-based scheduling mechanism that learns the appropriate update interval for each sensor, by considering the timeliness of the information collected measured through the Age of Information (AoI) metric, the spatial and temporal correlation between readings, and the energy capabilities of each sensor. We show that our proposed scheduler can achieve near-optimal performance in terms of the expected network lifetime. European Regional Development Fund through the SFI Research Centres Programme [13/RC/2077_P2 SFI CONNECT]; SFI-NSFC Partnership Programme [17/NSFC/5224]; Commonwealth Cyber Initiative at Virginia Tech Published version This work was funded in part by the European Regional Development Fund through the SFI Research Centres Programme under Grant No. 13/RC/2077_P2 SFI CONNECT and by the SFI-NSFC Partnership Programme Grant Number 17/NSFC/5224. It is also supported by the Commonwealth Cyber Initiative at Virginia Tech.

Energy consumption is expected to be reduced while maintaining high productivity for container handling. This paper investigates a new energy-efficient scheduling problem of automated container terminals, in which quay cranes (QCs) and lift automated guided vehicles (AGVs) cooperate to handle inbound and outbound containers. In our scheduling problem, operation times and task sequences are both to be determined. The underlying optimization problem is mixed-integer nonlinear programming (MINLP). To deal with its computational intractability, a customized and efficient genetic algorithm (GA) is developed to solve the studied MINLP problem, and lexicographic and weighted-sum strategies are further considered. An $\epsilon $ -constraint algorithm is also developed to analyze the Pareto frontiers. Comprehensive experiments are tested on a container handling benchmark system, and the results show the effectiveness of the proposed lexicographic GA, compared to results obtained with two commonly-used metaheuristics, a commercial MINLP solver, and two state-of-the-art methods.

The importance of renewable energy compared to fossil fuels is increasing due to growing energy demand and environmental challenges. Multi-generation systems use one or more energy sources and produce several useful outputs. The present study aims at investigating and comparing solar energy based multi-generation systems with and without once -through MSF desalination unit from the thermodynamic point of view. Firstly, hydrogen, electricity, and hot water for space heating and domestic usage are produced using the system, which consists of a parabolic trough collector, an organic Rankine cycle (ORC) and a PEM electrolyzer and heat exchanger as sub-systems. The performance of the entire system is evaluated from the energetic and exergetic points of view. Various parameters affecting hydrogen production rate and efficiency values are also investigated with the thermodynamic model implemented in the Engineering Equation Solver (EES) package. The system can produce hydrogen at a mass flow rate of 20.39 kg/day. The results of the study show that the energy and exergy efficiency values of the ORC are calculated to be 16.80% and 40% while those for the overall system are determined to be 78% and 25.50%, respectively. Secondly, once-through MSF desalination unit is integrated to the system between ORC evaporator and heat exchanger producing domestic hot water in the solar cycle in order not to affect hydrogen production rate while thermodynamic values are compared. Fresh water production capacity of the system is calculated to be at a volumetric flow rate of 5.74 m(3)/day with 10 stages. (C) 2022 Published by Elsevier Ltd on behalf of Hydrogen Energy Publications LLC.

This paper proposes a novel train trajectory optimization approach for high-speed railways. We restrict our attention to single train operation scenarios with different scheduled/rescheduled running times aiming at generating optimal train recommended trajectories in real time, which can ensure punctuality and energy efficiency of train operation. A learning-based approach deep deterministic policy gradient (DDPG) is designed to generate optimal train trajectories based on the offline training from the interaction between the agent and the trajectory simulation environment. An allocating running time and selecting operation modes (ARTSOM) algorithm is proposed to improve train punctuality and give a series of discrete operation modes (full traction, cruising, coasting, full braking), and thus to produce a feasible training set for DDPG, which can speed up the training process. Numerical experiments show that an optimized speed profile can be generated by DDPG within seconds on a realistic railway line. In addition, the results demonstrate the generalization ability of trained DDPG in solving TTO problems with different running times and line conditions.

The energy needs of a Net Zero Energy Building (NZEB) are fully met by renewable energy sources. Nevertheless, the time span of the energy balance can affect the effective energy self-sufficiency of the building. The aim of this paper is to demonstrate the lack of reliability that a yearly energy balance has in characterizing an NZEB. At this scope, comparisons between two different photovoltaic systems (fixed and tracking) and two kinds of energy balance (yearly and monthly) are made for a real NZEB building located in South-Italy. The investigation was carried out through dynamic energy simulations after validating the building model. The results show that the PV surface which attains the NZEB target on yearly basis not always achieves the same objective as the monthly balance. Furthermore, considering a monthly balance, the size of the photovoltaic system with biaxial solar tracking is 50% minor than the fixed one, thanks to a steadier energy production. Also, solar tracking systems show a significantly lower reduction of operational and embodied CO2 emissions. A final technical-economic analysis shows, however, that design solutions that satisfy NZEB target not always can meet the financial interest of the private stakeholder, showing a high discounted payback period.

Every major event on a national or global scale influences the environment, and scientists are always looking for new solutions to decrease ecological destruction. Throughout the preceding decade, professionals offered and executed policy ideas for energy adaptation and integration, such as the use of renewable energy. Between 1980 and 2021, the study looks at the relationship between environmental innovation, energy efficiency, and institutional quality in low-income nations. Autoregressive distributed lag (ARDL), cross-sectional ARDL, and Dumitrescu-hurling models were used to investigate the empirical connection. Following the identification of the initial difference, the stationary variables were combined due to commonalities in their dynamics. The panel counteraction test revealed that long-term relationships between variables exist. Including renewable energy sources and environmental innovation improves the long-term sustainability of low-income economies. The ARLD and CS-ARDL variable coefficients have a greater effect on environmental policy when their institutions are strong, ecologically aware, and resourceful. A well-established feedback loop connects renewable energy with environmental sustainability. Institutional excellence and environmental sustainability are inextricably linked. According to the report, governments and policymakers should increase the usage of renewable energy sources and invest in environmental innovation to attain environmental sustainability.

To lessen the residential sector environmental burdens from the energy consumption of household appliances, notable efforts have been directed to replace existing energy-consuming appliances by new energy-efficient equipment. However, less attention has focused to understand the optimum operating period of households so reduced greenhouse gas emissions can be achieved. Conventional household appliances should be preferably replaced with new designs featuring improved energy efficient models, along with reduced environmental burdens associated with the manufacturing of the new products. Such studies, to the best of our knowledge, have not been extensively investigated. To address this gap, the global warming potential during the life cycle of three representative household appliances, a microwave oven, a dishwasher and a washing machine is analyzed using a cradle-to-grave life cycle assessment. To provide guidelines towards impact reduction, the current situation and four new scenarios focused on material efficiency, recycled material, renewable electricity and responsible consumption are analyzed. Depending on the scenario, impacts of 84-261, 317-1330, and 533-1375 kg.CO2 eq/lifetime are obtained for a microwave, a dishwasher and a washing machine, respectively. Balancing energy efficiency and life- time when replacing a class A appliance, operating periods of 3.4-30, 2.7-26.2 and 4.6- 33.9 years for microwaves, dishwashers, and washing machines, render the lowest CO2 footprint. These results may assist manufacturers, policymakers and citizens to promote environmentally sustainable production and consumption patterns. (C)22 The Authors. Published by Elsevier Ltd on behalf of Institution of Chemical Engineers. The authors are grateful for the support provided through the Basque Government (IT-1365-19) and the University of the Basque Country (GIC-18/22) grants.

In the last few decades, the environmental degradation, global warming, and climate change remained the life-threatening issues across the globe. Specifically, the use of non-renewable fossil fuels is regarded as the most significant reason of such inclined issues. However, the policy-makers and scholars are now more concerned about the recovery of environmental quality, where renewable energy is considered as the primary solution to the existing issue. The developed economies and environment related international organizations rapidly enhances the use and promotion of renewable energy after the taking pledge in the Kyoto Protocol Agreement (1997). Nonetheless, the scholars are participating in analyzing the key drivers of renewable energy. Still, the proper drivers of renewable energy are not properly addressed in the existing literature. To fill this gap, current study analyzed the group of seven (G7) economies over the period 1990-2020. Using various panel data techniques such as slope heterogeneity, crosssection dependence, unit root, and cointegration test, the results indicates that the slopes are heterogeneous, and the cross-section dependence, as well as cointegration exists among the panel economies. Besides, the irregular distribution of data leads to the adoption of novel Method of Moments Quantile Regression accommodating four quantiles, i.e., (Q0:25, Q0:50, Q0:75, and Q0:90). The examined results asserted that economic growth and energy efficiency negatively and significantly affects renewable energy consumption (REC). Whereas, developed environmental related technologies, environmental taxes, and composite risk index are positively affecting REC in the study panel. Besides, improved energy efficiency (energy efficiency squared) also contributed to the promotion of renewable energy consumption. The Granger causality test estimates reveals bidirectional and unidirectional causal association between the variables. Based on the empirical results, policies are provided that could help developed economies in the promotion of renewable energy consumption, improve economic growth, and enhances environmental sustainability.