Energy Metrics Research Articles

Technological pathways to decarbonisation and the role of renewable energy: A study of European countries using consumption-based metrics

To decarbonise Europe in the post-COP26 era, current policies must be adjusted to account for the cross-border consequences of its consumption pattern. Using consumption-based Kaya identity metrics adjusted for emissions and energy embodied in traded goods and services, this study examines the nexus between technological factors defining energy transition progress, specifically energy and carbon intensities of the consumption mix, and carbon dioxide (CO2) emissions, in a sample of 20 European countries from 1995 to 2019. The empirical steps rely on panel-data estimators that are robust to cross-sectional dependence and allow for heterogeneous slope coefficients. The results show that energy and carbon intensities of the consumption mix have a positive relationship with CO2 emissions but a negative relationship with renewable energy consumption. The findings also verify an inverted U-shaped relationship between affluence and CO2 emissions through the energy and carbon intensity metrics. Additional tests show a unidirectional causality from carbon intensity of the energy mix to CO2 emissions and from renewable energy to the carbon intensity. Also, bidirectional causality exists between CO2 emissions and per capita GDP and energy intensity, and between renewable energy and energy intensity. By implication, renewable energy provides the technological path to mitigating consumption-induced emissions in Europe.

Energy audit, techno-economic, and environmental assessment of integrating solar technologies for energy management in a university residential building: A case study

This study presents the results of an energy audit and management performed on a university residential building in Borg El-Arab City, Egypt. The building’s energy consumption, areas of energy wastage, and energy-saving opportunities were investigated, and the corresponding energy metrics were quantified accordingly. Firstly, an energy consumption is estimated based on the building's electricity bills, meter measurements, and survey. Then, the energy consumption is analyzed and evaluated. Subsequently, the feasibility of integrating solar technologies (i.e., photovoltaics and domestic water heating) into buildings is appraised from techno-economic and environmental perspectives. The study employs ASHRAE Level 1 and 2 guidelines for conducting energy audits. The results show that electricity consumption is highest in air conditioning units (which consume ∼62%), followed by socket loads (∼25%), and lastly, lights (∼13%). Detailed analysis of the energy-use characteristics of the building revealed the mismanagement of electricity. Through light retrofits such as replacing the incandescent bulbs with LED bulbs, adopting sensory lights, and delamping, the building would save 4,432.6 kWh annually. Additionally, changing the AC unit type from non-inverter to inverter type would save approximately 61,194 kWh/year, representing 22.96% energy savings, with a payback period of 8.6 years. Overall, the proposed energy conservation measures will mitigate 30.8 tons of CO2 per year. Furthermore, incorporating PV and SWH systems will lead to annual energy contributions of 79,820 kWh and 38,048 kWh, with payback periods of 3.77 years and 2.49 years, respectively. Notably, the solar technologies will altogether abate approximately 91.5 tons of CO2 and provide a carbon credit gain of $1,830 annually.

Sustainability of building-integrated bioclimatic design strategies depending on energy affordability

Bioclimatic design strategies have proven their efficiency in improving the sustainability of buildings. However, their economic benefits, regarded as the main incentive for building owners to incorporate such strategies into buildings, are still unclear since they depend on several factors including the countries' energy accessibility level. This study explores the role of energy affordability level and climatic conditions in incorporating bioclimatic design strategies. Therefore, the effectiveness of integrating seven bioclimatic approaches into a common residential building in six different locations worldwide with disparate climatic conditions, gross domestic products and electricity prices is assessed. The outcomes of each strategy are generated using EnergyPlus software and evaluated based on key energy, economic and environmental metrics. The findings reveal that, for most bioclimatic design strategies, the highest economic profits are achieved in regions where the electricity price to gross domestic product (EPGDP) ratio is high (i.e., where energy is unaffordable). Indeed, the shortest discounted payback period is obtained by using suitable glazing size in hot/moderate climates with higher EPGDP ratio (0.04/0.13 years) and thermal insulation in cold ones (1.17 years). Moreover, the greatest net present values are acquired by integrating thermal insulation in hot/cold zones with up to k$14.04/k$76.73, and window opening design in moderate climates (k$7.32). Additionally, the investigated strategies exhibit significant energy savings and carbon emissions mitigation. This study confirms the benefits of bioclimatic design; nevertheless, awareness campaigns and incentive programs are also essential in motivating households to integrate sustainable strategies into their buildings, especially in regions where energy is affordable.

Multivariate Drought Monitoring, Propagation, and Projection Using Bias‐Corrected General Circulation Models

AbstractUnderstanding how droughts are characterized, propagated, and projected, particularly multivariate droughts, is necessary to explain the variability and changes in drought characteristics. This study aims to understand multimodel global drought monitoring, propagation, and projection by utilizing a multivariate standardized drought index (MSDI) during the historical (1959–2014) and future (2045–2100) periods under two socioeconomic pathways SSPs (370 and 585), derived from the bias‐corrected Coupled Model Intercomparison Project Phase 6 (CMIP6). Based on the energy metrics, the multivariate bias correction method outperformed other techniques in correcting the biases in the CMIP6 drought representation. The drought indicators demonstrate distinct categories for meteorological, hydrological, and multivariate droughts. There were significant high cross correlations between Heatwave Total Length (HWTL) and MSDI in Africa and South America for all lagged times. Europe and North America generally saw the maximum MSDI drought duration (228 months) during the historical period. For future projections, Africa recorded the maximum drought duration (197 months), while Europe witnessed the minimum drought duration for SSP 370 (171 months), and North America (149 months) for SSP 585. Furthermore, during the historical period in tropical Africa, the propagation of meteorological to hydrological drought was slower during the wet months than during the dry months. Under the SSP 370 future projection, there was a shift in the long period of meteorological‐hydrological propagation from the middle and late wet months to the beginning of the wet months in tropical Africa. Therefore, tracking and projecting drought characteristics is vital for understanding the risk of drought‐related consequences.

Energy in Robotics: An Interdisciplinary Challenge

Energy in Robotics: An Interdisciplinary Challenge

Investigation of building-integrated photovoltaic, photovoltaic thermal, ground source heat pump and green roof systems

Renewable and bioclimatic techniques play a major role in promoting the sustainability of buildings. Therefore, it is important to study the performance of these techniques in various climates to identify the best solutions with optimized configurations in each region for maximum effectiveness, leading to broader adoption of these strategies and a more energy-efficient built environment. The aim of this paper is to investigate the effectiveness of integrating photovoltaic (PV), photovoltaic thermal (PVT) and ground source heat pump (GSHP) systems, and green roof (GR) strategy into a typical residential building in six different Moroccan climates. The performance of these techniques is assessed using key energy, environmental and economic (3E) metrics. To this aim, several simulations are conducted using EnergyPlus software. Furthermore, the impact of carbon taxation on each technique's economic benefits is examined. The results reveal that the PV and PVT technologies exhibit the greatest outcomes for the 3E perspectives in all climates; the excellent performance is achieved in the desert climate while the lowest one is found in the Mediterranean climate. Moreover, GSHP and GR techniques show significant energy and environmental benefits, but they prove to be economically inefficient in all considered climatic zones. Generally, the carbon payback periods are found in the range of 0.59–0.84, 1.07–1.25, 0.67–3.71 and 3.66–6.22 years, whereas the levelized cost of energy are within the range of 0.027–0.039, 0.030–0.035, 0.209–1.149 and 0.226–0.383 $/kWh for PVT, PV, GSHP and GR, respectively. On the other hand, levying a carbon tax of $75/tCO2e could increase the savings-to-investment ratio, on average, by around 61.42%, 60.32%, 59.60% and 51.53%, sequentially, for PVT, PV, GSHP and GR. Besides, the results of this paper could be applied to other locations worldwide with similar climates, energy prices and CO2 emission factors.

Optimized modeling of energy and environmental metrics of mixed flow turbofan engine used regional aircraft.

As a kind of gas turbine engines, turbofan engines have powered a number of aero-vehicles in aviation sector. The necessity of turbofan with higher energy efficiency has been greatly drawn attention since these are operating dependent to fossil fuels. In this study, energy and emission metrics of fifty-one mixed flow turbofan engines (MFTE) with different bypass ratio, overall pressure ratio and fuel flow are modeled with multi-regression (MR) method. The obtained models are subjected to metaheuristic approaches involving genetic algorithm (GA) and simulated annealing (SA) so as to decrease error of the models. According to MR findings, rated thrust of MFTEs is estimated with 1.4877 of minimum square error (MSE) whereas GA and SA make it lower as 1.3404 and 1.2524, respectively. On the other hand, NOx emission index of MFTEs is predicted with relatively low coefficient of determination (R2) as 0.8620. However, its accuracy is enhanced to 0.8633 (with GA) and 0.8655 (with SA). Finally, exergy efficiency of MFTEs is estimated the highest model correctness with GA. Namely, R2 of the model is computed as 0.9280 with GA and 0.9277 with SA. Without applying these methods, its R2 is obtained as 0.9263 with MR. When considering these outcomes, thanks to modeling and optimization methods, prediction of performance and emission indexes of mixed flow turbofan engines could be performed with lower error values. It is thought that the study helps in prediction of environmental effect regarding turbofan engines that are utilized at busy airports.

Leveraging Metaheuristic Unequal Clustering for Hotspot Elimination in Energy-Aware Wireless Sensor Networks

Wireless sensor networks (WSNs) are becoming a significant technology for ubiquitous living and continue to be involved in active research because of their varied applications. Energy awareness will be a critical design problem in WSNs. Clustering is a widespread energy-efficient method and grants several benefits such as scalability, energy efficiency, less delay, and lifetime, but it results in hotspot issues. To solve this, unequal clustering (UC) has been presented. In UC, the size of the cluster differs with the distance to the base station (BS). This paper devises an improved tuna-swarm-algorithm-based unequal clustering for hotspot elimination (ITSA-UCHSE) technique in an energy-aware WSN. The ITSA-UCHSE technique intends to resolve the hotspot problem and uneven energy dissipation in the WSN. In this study, the ITSA is derived from the use of a tent chaotic map with the traditional TSA. In addition, the ITSA-UCHSE technique computes a fitness value based on energy and distance metrics. Moreover, the cluster size determination via the ITSA-UCHSE technique helps to address the hotspot issue. To demonstrate the enhanced performance of the ITSA-UCHSE approach, a series of simulation analyses were conducted. The simulation values stated that the ITSA-UCHSE algorithm has reached improved results over other models.

A plan to build a net zero energy building in hydrogen and electricity-based energy scenario in South Korea

As net zero energy buildings (NZEBs) are attracting global attention, possible energy transition scenarios for NZEBs have been proposed in South Korea: (1) hydrogen-based or (2) electricity-based energy supply. Compared with a typical Korean residential building that uses a gas-fired boiler and air conditioner, the buildings in the two scenarios can significantly reduce energy consumption and emissions. In this context, this study aims to evaluate the performance of NZEBs in hydrogen- and electricity-based energy-supply scenarios based on simulation. An NZEB is constructed considering passive designs, active systems, and renewable energy systems. Subsequently, its performance is evaluated in terms of energy, environmental, and economic metrics, considering life cycle performance. The evaluation results confirm that the electricity-based energy scenario has better energy and environmental performance than the hydrogen-based energy scenario, with each scenario showing energy savings of 62% and 53%, respectively. In the electricity-based scenario, application of the passive design, active system, and renewable system accounts for savings of 48.2%, 21.2%, and 7.8%, respectively. Consequently, achieving NZEB requires more than 13 photovoltaic panels. In case of economic feasibility, all scenarios have positive operating cost savings. However, scenario 1 shows insufficient economic feasibility owing to high initial investment cost.

The effects of acute Methylene Blue administration on cerebral blood flow and metabolism in humans and rats.

Methylene Blue (MB) is a brain-penetrating drug with putative neuroprotective, antioxidant and metabolic enhancing effects. In vitro studies suggest that MB enhances mitochondrial complexes activity. However, no study has directly assessed the metabolic effects of MB in the human brain. We used in vivo neuroimaging to measure the effect of MB on cerebral blood flow (CBF) and brain metabolism in humans and in rats. Two doses of MB (0.5 and 1 mg/kg in humans; 2 and 4 mg/kg in rats; iv) induced reductions in global cerebral blood flow (CBF) in humans (F(1.74, 12.17)5.82, p = 0.02) and rats (F(1,5)26.04, p = 0.0038). Human cerebral metabolic rate of oxygen (CMRO2) was also significantly reduced (F(1.26, 8.84)8.01, p = 0.016), as was the rat cerebral metabolic rate of glucose (CMRglu) (t = 2.6(16) p = 0.018). This was contrary to our hypothesis that MB will increase CBF and energy metrics. Nevertheless, our results were reproducible across species and dose dependent. One possible explanation is that the concentrations used, although clinically relevant, reflect MB's hormetic effects, i.e., higher concentrations produce inhibitory rather than augmentation effects on metabolism. Additionally, here we used healthy volunteers and healthy rats with normal cerebral metabolism where MB's ability to enhance cerebral metabolism might be limited.

A material social view on data center waste heat: Novel uses and metrics

Today's data centers use substantial amounts of the world's electrical supply. However, in line with circular economy concepts, much of this energy can be reused. Such reuse includes the heating of buildings, but also commodity dehydration, electricity production and energy storage. This multi-disciplinary paper presents several novel applications for data center waste heat. Next, the paper accounts for three case studies, taken from three different societal contexts: urban Malaysia, rural Costa Rica and semi-urban Sweden. A discussion on data center energy metrics leads to the development of a new metric, Datacenter Energy Sustainability Score (DESS), which is evaluated within the three use cases. Last, it is shown how a material social view on metrics provides a way past a problem that has haunted the data center industry for the last 15 years, whilst benefitting both data center owners who want to compete through sustainability as well as stakeholders from governments on local, regional and national levels. The paper makes clear that a sustainability strategy should be based on a material social view and stretch beyond the building itself. In fact, and as demonstrated by the relevance of DESS, modern data centers are so energy-efficient that data center sustainability is no longer mainly an engineering issue, but a matter requiring multi-disciplinary insights, approaches and collaboration.

Storing the future of energy: Navigating energy storage policy to promote clean energy generation

AbstractThe United States has experienced heightened interest in clean energy sources, with many states implementing renewable technologies for energy generation. These efforts are critical for moving states and the nation toward decarbonization and decreased emissions within the transportation and power industries. A challenge with renewable sources (particularly solar and wind) is the inherent variability of energy generation due to climate and geographic influences. Consequently, there is increased interest in addressing energy storage technologies to better capitalize on excess power from high‐production periods for use in times of low generation. Energy storage comes in many different forms with varying duration. Several forms of energy storage are explored in this report to demonstrate the variety of technology options. Following research of the current state of energy storage policy, this work proposes three areas of potential policy improvements for industry: (1) implementation of a policy framework for states to produce ambitious energy storage procurement metrics; (2) amending of the federal investment tax credit for energy storage technologies to be duration‐based; and (3) incentivization of sustainable battery practices. It is imperative for state legislatures to create informed energy storage goals alongside current renewable energy metrics. Amending the modern federal investment tax credit system to include duration‐based incentivization will encourage the deployment of long‐duration technologies to combat variation in electricity generation over the course of seasons. Finally, for the continued deployment of batteries, sustainable practices must be implemented to mitigate material and environmental challenges posed by them, including recycling practices and alternative chemistry utilization.

Sediment Microbial Fuel Cells: Opinion of the Factors Impeding the Deployment

This article explores the potential and limitations of Sediment Microbial Fuel Cells (SMFCs) and their deployment for sustainable energy production and environmental remediation. SMFCs use naturally occurring redox gradients in sediments to produce bioelectricity, making them advantageous over conventional energy sources due to their affordability, simplicity, and ability to operate in various environments with minimum maintenance requirements. However, their low power output density restricts their practical applicability. The article discusses the controllable and uncontrollable factors that affect SMFC performance and their influence on SMFC functionality, electrode material, external resistance, electrode spacing, electrode design, electrode immersion dimensions, and catalyst. The article highlights the challenges facing SMFC deployment, particularly in large-scale businesses, such as the need for more scientific literature on SMFCs and inadequate focus on energy metrics.

A comprehensive study on the effect of variation of flow rate of fluid and N on energy metrics of N similar photovoltaic thermal flat plate collectors integrated single slope solar still

A comprehensive study on the effect of variation of flow rate of fluid and N on energy metrics of N similar photovoltaic thermal flat plate collectors integrated single slope solar still

Cross-Tier Interference Mitigation in 3D HetNets for LTE and Wi-Fi Access

Due to the unprecedented rate of transformation in the field of wireless communication industry, there is a need to prioritise the coverage, network power and throughput as preconditions. In Heterogeneous Networks (HetNets) the low power node inclusion like Femto and Pico cells creates a network of Multi-Tier (M-Tier) which is regarded as the most significant strategy for enhancing the coverage, throughput, 4G Long Term Evolution (LTE) ability. This work mainly focuses on M-Tier 3D Heterogeneous Networks Energy Efficiency (EE) based Carrier Aggregation (CA) scheme for streaming real-time huge data like images. At first, M-Tier 3D HetNets scheme was made for investigating Signal to Noise Interference Ratio (SNIR) on assessing the collective Pico-tier and Femto-tier interference. Next, the scheme of channel allocation is scrutinised so as to estimate throughput from the multiple tiers. Additionally, with the use of CA technique, the problem of energy efficiency for M-Tier 3D Heterogeneous Network (HetNet) in relation to energy metrics and throughput was evaluated with the use of LTE and Wireless Fidelity (Wi-Fi) coexistence. The simulation is carried out in a MATLAB setting, and the outcomes reveal a huge impact on EE. The simulation is carried in terms of EE, transmission time, throughput, packet success rate, convergence probability, and coverage region. The analysis from simulation shows that on improving the output of the device, interference among small cell base stations is reduced on increasing EE. The outcomes attained aid in the effective creation of M-Tier 3D HetNets for enhancing EE by employing Multi-Stream Carrier Aggregation (MSCA) in HetNets.

System Dynamics and Tradeoffs in Radio Astronomical Data Transport of an Integrated Satellite Communication and Radio Astronomy System

This paper considers an integrated mega-constellation non-geostationary orbit satellite system which provides both communication and radio astronomical observation (RAO) services. We focus on RAO data transport from the RAO-conducting satellites (called source satellites) to the ground gateways where each gateway is directly connected to a certain number of satellites (called destination satellites). We introduce a generalized inter-satellite link (ISL) connection model which extends the existing approach of adjacent-only ISL connections to include non-adjacent ISL connections. This model is implemented with an upper limit on the ISL distance which can be adjusted for performance tradeoffs. Next, we develop analytical expressions to study two impacts of satellite dynamics on the RAO data transport. The first one concerns with the beam misalignment of individual ISL hops. The second one corresponds to whether destination satellites move outside the gateway coverage during the end-to-end delay interval of a data packet transport. Furthermore, we introduce delay, energy, and spectrum usage performance metrics and evaluate them to yield performance tradeoff guidelines. A simplified data transport path model is also presented to facilitate analytical performance evaluation and initial system design settings. Then, we present a new RAO data transport design which incorporates system dynamics and desired performance tradeoffs. Finally, analytical and simulation results and discussions are presented.

Optimization of key energy and performance metrics for drug product manufacturing

During the development of pharmaceutical manufacturing processes, detailed systems-based analysis and optimization are required to control and regulate critical quality attributes within specific ranges, to maintain product performance. As discussions on carbon footprint, sustainability, and energy efficiency are gaining prominence, the development and utilization of these concepts in pharmaceutical manufacturing are seldom reported, which limits the potential of pharmaceutical industry in maximizing key energy and performance metrics. Based on an integrated modeling and techno-economic analysis framework previously developed by the authors (Sampat et al., 2022), this study presents the development of a combined sensitivity analysis and optimization approach to minimize energy consumption while maintaining product quality and meeting operational constraints in a pharmaceutical process. The optimal input process conditions identified were validated against experiments and good agreement resulted between simulated and experimental data. The results also allowed for a comparison of the capital and operational costs for batch and continuous manufacturing schemes under nominal and optimized conditions. Using the nominal batch operations as a basis, the optimized batch operation results in a 71.7% reduction of energy consumption, whereas the optimized continuous case results in an energy saving of 83.3%.

Making energy justice work for women in rural sub-Saharan Africa: A qualitative diagnostic from Benin, Senegal, and Togo

A carbon neutral world by 2050. Few would oppose the idea of embedding justice in the energy systems painted in the emerging net zero scenario. However, how does the lofty ideal of justice translate for communities distant from elite centers of knowledge and power? Focusing on women from rural communities in Benin, Senegal, and Togo, this paper applies the double lens of gender and capability to energy justice principles and addresses the following questions: 1) How do these rural women currently experience energy justice principles? And 2) What energy interventions could enhance these women's capabilities in the future? The findings from our field interviews offer a diagnostic of energy justice for rural women, connecting the limited availability and affordability of energy sources to sustainability concerns in a vicious cycle of resource scarcity and impaired capabilities. We then propose interventions to apply justice principles in the local context and argue that operationalizing energy justice requires making gender equity a cross-cutting dimension in the energy justice framework. We contend that building just energy systems by 2050 would be best achieved by focusing on human capabilities, i.e., promoting people's opportunities to live the life they value over allegedly universal energy metrics.

Energy efficient two-stage capacity allocation scheme for WBAN healthcare applications

Co-channel interference occurs in coexisting Wireless Body Area Networks (WBANs) and has an impact on the capacity allocation of the networks. The proposed Two Stage Capacity Allocation (TSCA) mitigates interference and maximizes the capacity of poor channel quality WBANs with high priority data. It uses traditional interference mitigation schemes such as transmission power level control, channel switching and relay-aided transmission in each instant of pause time. The proposed work introduces a metric called Emergency Residual Index (ER-Index) and chooses any one of the mitigation schemes. The ER Index value provides a trade-off between residual energy, emergency factor and channel metrics. Further, TSCA executes a two-stage capacity allocation method. The TSCA scheme is a combination of the Nash bargaining solution and the Min-Max algorithm. The mitigated interference is 45% compared to Dynamic link quality-based Sub Channel Allocation (DSCA) and 60% compared to Traffic Aware Medium Access Control (TA-MAC). The average energy consumption is decreased up to 37.82% compared to TA-MAC and 25.59% compared to the DSCA algorithm.

A parametric approach to identify synergistic domains of process intensification for reactive separation

Process intensification aims to combine multiple tasks within multi-functional units to drastically improve economic, energy or sustainability metrics of a chemical process. Limited work exists to systematically identify the synergistic domains where intensification outperforms its nonintensified counterpart. In this work, we computationally derive the synergistic domains of a reactive separation system. Specifically, we first postulate general models for both intensified and nonintensified systems. We use these models to generate data to train a ReLU-type artifical neural network (ANN). The trained ReLU-NN model is formulated as a multi-parametric mixed-integer linear program (mp-MILP), and the critical regions of this mp-MILP define the synergistic feasible domains of intensification. We have derived these synergistic domains of vapor–liquid equilibrium (VLE)-based reactive separation for several industrial applications. These synergistic domains enable quick screening of properties that favor intensification.