Analysis Of Energy Usage Research Articles

Enhancing sustainability of urban waste management through data envelopment analysis for municipal solid waste composting in Tehran, Iran

The critical necessity of decreasing energy consumption and environmental effects is vital in various facets of urban life, particularly in urban waste management. This research aimed to evaluate the energy flow, CExD, and Life Cycle of a composting system for Municipal Solid Waste (MSW) in Tehran province, Iran. The initial phase entailed assessing the energy flow and effectiveness of the composting system, while the subsequent phase focused on enhancing energy efficiency through the application of Data Envelopment Analysis (DEA) to determine an optimal energy consumption strategy for conserving energy and reducing environmental impacts in Tehran's MSW composting system. Over a 90-day period, the analysis of energy usage revealed an energy input and output of 417.30 GJ (8500 t MSW)−1, with 227.02 GJ (8500 t MSW)−1 linked to transportation and 190.28 GJ (8500 t MSW)−1 related to composting activities. The overall energy consumption in the composting system was determined to be 6424.77 GJ (8500 t MSW)−1. By applying DEA optimization, energy savings of 14.45 GJ (8500 t MSW)−1 were accomplished in the composting process, with a significant reduction in electricity usage contributing to these savings. The environmental impact of the energy consumption patterns identified by DEA was notably lower compared to current energy practices. The most notable decrease in impact was observed in the Photochemical Oxidation category. By following the energy usage pattern recommended by DEA, the Global Warming Potential impact reduced by 500 kg CO2 eq. per 8500 t MSW. Additionally, the optimization of energy use through DEA led to a decrease in fossil energy resource depletion by around 4 GJ (8500 t MSW)−1 in the composting process.

Analyzing the Energy Usage of a Community and the Benefits of Energy Storage

Understanding the energy usage of a community is crucial for policymaking, energy planning, and achieving sustainable development. The advent of the smart grid has made it feasible to gather fine-grain energy usage data at large-scales, providing us with new opportunities to understand demand patterns at different spatial and temporal scales. In this paper, we conduct a large-scale empirical study of energy usage of 14,849 residential and commercial energy consumers from a small city in the United States. We conduct a wide ranging analysis of energy usage at multiple granularities—citywide, transformer-level, and individual home levels. In doing so, we demonstrate how city-wide smart meter datasets can answer a variety of questions on energy consumption, such as the impact of weather on energy usage. For example, we show that extreme weather events significantly increase energy usage, e.g., by 36% and 11.5% on hot summer and cold winter days, respectively. As another example, we show 19.2% of transformers in the grid get overloaded during peak load periods. Finally, we evaluate the impact of incorporating varying amounts of energy storage within the distribution grid and the impact such deployments will have on the peak demand patterns seen by the grid as well as the ability to reduce overloads seen by distribution transformers during peak periods.

Energy audit on lighting system for 7-storey educational building – Energy saving opportunity

An energy audit is an important process for determining a building’s energy efficiency. This process includes verification, monitoring and analysis of energy usage and recommending ways to improve energy consumption. This paper presented a study on energy balance, utility system description, methodology to calculate the energy consumption, load apportioning and room data survey on luminance for a 7-storey educational building. The resulting data is then analysed to assess energy performance, identify opportunities for improvement without compromising safety, usability and comfort levels, and suggest potential energy savings measures that can be implemented later. As a result, it shows that the building consumed a total of 669,840.84 kWh of energy over the year of 2016 and 53.64% of the energy usage comes from lighting system. The proposed energy saving measure on lighting system for this building were expected to give 167,873.28 kWh reduction of energy per year by retrofitting an 18 watt and 36 watt of fluorescent lamp to 10 watt and 18 watt of light emitting diode lamp. The room data survey on luminance measurement also shows that 69% of the interior space is overlit, and delamping can result in a total energy savings of 45,550.08kWh per year. Lastly, the total energy saving can also contribute to 116.50 ton/year of CO2 reduction.

A Statistical Analysis of Energy Usage for K- 12 School Facilities

The U.S. Department of Energy (DOE) recently announced investing $80M through the Bipartisan Infrastructure Law (BIL) to make K-12 schools more energy efficient and lower their energy costs, including some of the nation’s highest-need schools. The ideas is that funding will help resource high-need school districts with the training and tools needed to improve how their schools consume energy, improve health and learning outcomes for children and staff, and support bringing good-paying jobs to the community. (Department of Energy, 2022). Research is needed to contextualize this challenge in that it hard to improve what you can not measure. While K-12 schools have implemented different energy saving strategies DERs and DWTs could help them achieve significant water and energy savings [2], [3]. We seek to measure the statistics that may drive this opportunity. In this report we will be investigating two datasets and calculating their statistical quantities retrieved fromtwo major cities on energy usage of K-12 schools and its statistical implications.

Life Cycle Assessment of Electric Vehicle Batteries: Review and Critical Appraisal

The most environmentally damaging aspect of using electric vehicles is the batteries. The Life Cycle Assessment (LCA) approach has been widely used to conduct inventory analysis of energy usage and GHG emissions throughout battery production and assembly. There are many analytical frameworks and models for conducting LCA, but each method uses different results. This study aims to investigate numerous LCA studies on electric vehicle batteries using ISO 14040 and its derivatives. We propose the limits of a cradle-to-grave system so that LCA provides optimal results for comparative studies and potential for continuous improvement. A schematic overview of the electric car battery life cycle covers material extraction, material processing, product manufacture, product use, and end-of-life recovery measures. Global warming, eutrophication, acidification, ozone depletion, abiotic depletion, particulate matter, human toxicity, ecotoxicity, and Cumulated Energy Demand (CED) are all impact categories in LCA study.

A Systems Analysis of Energy Usage and Effectiveness of a Counter-Unmanned Aerial System Using a Cyber-Attack Approach

Existing counter-unmanned aerial system (C-UAS) defensive mechanisms rely heavily on radio frequency (RF) jamming techniques that require a large amount of energy to operate. The effects of RF jamming result in undesirable consequences, such as the jamming of other nearby friendly radio devices as well as the increase in RF footprint for local operators. Current cybersecurity analysis of commercial off-the-shelf (COTS) UASs have revealed multiple vulnerabilities that give rise to opportunities to conduct C-UAS operations in the cyber domain. This is achieved by performing cyber-attacks on adversarial UASs through hijacking the device-specific communication’s link on a narrow RF band and without the need for broad-spectrum RF energy bursts during C-UAS operations, which can result in lower energy usage to accomplish the same outcome. This article validates the cyber-attack C-UAS (CyC-UAS) concept through reviewing recent C-UAS operational experimental scenarios and conducting analysis on the collected data. Then, a simulation model of a defense facility is constructed to analyze and validate specific mission scenarios of interest and several proposed concepts of operation. A comparison of the energy requirements between CyC-UAS and existing C-UAS techniques is performed to assess energy efficiency and trade-offs of different C-UAS approaches. In this article, the comparison of energy requirements between the CyC-UAS prototype and existing C-UAS products that utilize RF jamming methods reveals that CyC-UAS achieves significant energy savings while not affecting other telecommunication devices operating at the same frequencies. While both the C-UAS techniques adopt the denial-of-service strategy, the CyC-UAS is able to achieve the same mission by consuming much less energy. Therefore, the CyC-UAS concept shows promise as a new, lower energy, and lower collateral damage approach to defending against UAS.

Influence of occupant presence patterns on energy consumption and its relation to comfort: a case study based on sensor and crowd-sensed data

BackgroundIn recent years, the monitoring of occupant presence patterns has become an imperative for building energy optimization. Very often, there is a significant discrepancy between the building energy performance predicted at the design stage and the actual performance rendered during the building operation. This stems from the difference in user occupancy. In spite of this, user interaction and feedback are rarely taken into account and evidence of the impact of occupant presence patterns on energy consumption is still scarce. Thus, the purpose of this study is to apply crowd-sensing techniques to understand how energy is consumed and how appropriate performance indicators should be defined to provide inputs for building operations regarding more efficient use of resources.MethodsMonitoring strategies were implemented in an office lab with controlled variables to collect quantitative data on occupancy patterns, ambient factors and energy consumption. In addition, crowd-sensing techniques were applied to model user activity in different ambient conditions over time and to contrast their occupancy with energy consumption patterns in combination with new inquiry tools to identify how occupants perceive their comfort level. In addition, a set of energy efficiency indicators was used to compare energy performance over different periods.ResultsIt was discovered that there is a strong relation between user occupancy patterns and energy consumption. However, more than 50% of energy was consumed when no user activity was registered. Energy performance indicators revealed that measuring energy efficiency in terms of kWh per surface area encourages a less efficient use of space and, therefore, including a coefficient of person hours is advisable. It was also discovered that users do not fully rely on feedback mechanisms and they prefer to take action to adapt the ambient conditions rather than simply expressing their opinion. Analysis of energy usage during the Covid-19 lock down revealed substantial use of energy contrary to what was expected. This was because home computers were used as terminals only, while the actual tasks were performed on the lab computers, using remote desktop connections, which were turned on 24/7. In addition, energy consumed by each employee at his/her home should be taken into account. Moreover, a set of practical recommendations was formulated.

Analysis of energy usage and cost management of mechanize grabber in oil palm plantation

The aim of this study was to evaluate the energy usage and total operation cost of the tractor grabber. The data was collected at FELCRA BERHAD Kawasan Titi Gantong, Bota, Perak. The total cost included all the operation in loading system and evacuation process of fresh fruit bunch (FFB). This study evaluated the energy usage of tractor grabber for three consecutive months using a newly purchased Mini Tractor Grabber Kubota L4400. This study was conducted based on the energy input-output methodology. Mathematical equations are used to determine the field capacity and examine energy usage. The result found that 153.38 MJha⁻¹ of input energy was required to produce 328.43 metric ton per month of FFB in June. The energy was dominated by fuel consumption, machinery and followed by labour. The total operating cost is based on the field capacity of the machine. This study was conducted and obtained the result, assumed that the total cost for a year is RM 47,444.24 and the cost per metric ton is RM 9.76 with energy consumption of 174.23 MJ. Conclusively, it means that the energy usage and cost of operation is efficiently and effectively used in oil palm productivity in FELCRA BERHAD Kawasan Titi Gantong.

Analysis of energy usage in mosques in urban area with tropical climate: case study in Yogyakarta, Indonesia

The Mosque is a prayer place for Muslims, which has daily usage. For urban communities in Indonesia, mosques play an important role in social life. The Muslims carry out various kinds of activities in mosques besides praying. With its various activities, the mosque also has unique energy use characteristics when compared to other types of buildings such as houses, offices, and commercials. This paper presents an analysis of energy use in mosques in urban areas with tropical climate. Data was collected through a survey of mosques during 2018 to 2019 in Yogyakarta, Indonesia. The results show that the use of energy in mosques in urban areas in Yogyakarta on average consumes 182.2 kWh per day. The highest use is for air conditioning by 29.16%. Overall, the mosque energy consumption intensity varies from 0.16 to 4.54 kWh per square meter monthly and all of them meets criteria as very efficient buildings. In the other side, only 6 out of 15 mosques meet the national standard for lighting. In the term of green building standard, there are 9 out of 15 mosques meet the criteria in energy consumption aspect. This paper concludes that energy consumption in mosques in urban area with tropical climate is dominated by the air conditioning purposes.

Memory-Reduced Network Stacking for Edge-Level CNN Architecture With Structured Weight Pruning

This paper presents a novel stacking and multi-level indexing scheme for convolutional neural networks (CNNs) used in energy-limited edge-level systems. Basically, the proposed scheme offers multiple accuracy modes by adopting a structured weight pruning method that enables a CNN to be trained once with multiple pruning ratios and thereby allows for adaptive energy-accuracy trade-offs. The memory overhead required to store several different networks is kept to a minimum by adopting a novel method for including smaller lower-accuracy networks as subnetworks of larger higher-accuracy networks and by using a unique multi-level indexing scheme that can effectively store compressed weight data for the proposed stacked-CNN architecture. Experimental results show that the proposed method successfully reduces the memory footprint by up to 33% when compared to a baseline CNN architecture. An FPGA-based multi-mode CNN accelerator that implements the proposed scheme has been designed. Energy usage analysis with a case study shows that the inference energy required for on-device CNN processing can be reduced by up to 1.94 times over the baseline design.

Economic Optimal Control for Minimizing Fuel Consumption of Heavy-Duty Trucks in a Highway Environment

This paper provides a comparative assessment of three economic optimal control strategies, aimed at minimizing the fuel consumption of heavy-duty trucks in a highway environment, under a representative lead vehicle model informed by traffic data. These strategies fuse a global, off-line dynamic programming (DP) optimization with online model predictive control (MPC). We then show how two of the three strategies can be adapted to accommodate the presence of traffic and optimally navigate signalized intersections using infrastructure-to-vehicular (I2V) communication. The MPC optimization, which is local in nature, makes refinements to a coarsely (but globally, subject to grid resolution) optimized target velocity profile from the DP optimization. The three candidate economic MPC formulations that are evaluated include a nonlinear time-based formulation that directly penalizes the predicted fuel consumption, a nonlinear time-based formulation that penalizes the braking effort as a surrogate for fuel consumption, and a linear distance-based convex formulation that maintains a tradeoff between energy expenditure and tracking of the coarsely optimized velocity profile obtained from DP. Using a medium-fidelity Simulink model, based on a Volvo truck’s longitudinal and engine dynamics, we analyze the optimization’s performance on four highway routes under various traffic scenarios. Results demonstrate 3.7%–8.3% fuel economy improvement on highway routes without traffic and 6.5%–10% on the same routes with traffic included. Furthermore, we present a detailed analysis of energy usage by “type” (aerodynamic losses, braking losses, and comparison of brake-specific fuel consumption), under each candidate control strategy.

Demographical Energy Usage Analysis of Residential Buildings

Residential energy consumption constitutes a significant portion of the overall energy consumption. There are significant amount of studies that target to reduce this consumption, and these studies mainly create mathematical models to represent and regenerate the energy consumption of individual houses. Most of these models assume that the residential energy consumption can be classified and then predicted based on the household size. As a result, most of the previous studies suggest that the household size can be treated as an independent variable which can be used to predict energy consumption. In this work, we test this hypothesis on a large residential energy consumption dataset that also includes demographic information. Our results show that other variables such as income, geographic location, house type, and personal preferences strongly impact energy consumption and decrease the importance of the household size because the household size can explain only 26.55% of the electricity consumption variation across the houses.

The energy usage and environmental impact assessment of spent coffee grounds biodiesel production by an in-situ transesterification process

Spent coffee grounds (SCG) waste has been drawing attentions in the biodiesel industry due to the promising of oil content. However, SCG sources is very disperse and requires a transportation system. Moreover, a complexity of oil extraction steps using hazardous n-hexane can hinder the SCG biodiesel promotion. Therefore, an alternative approach using in-situ transesterification (in-situ TE), an n-hexane free process, was introduced for producing biodiesel at an on-site SCG source. Life cycle assessment was performed to compare the energy usage and environmental impacts between a conventional process, which requires transportation and n-hexane, and an on-site in-situ TE process. Producing SCG biodiesel using conventional process required 43% less energy and produced fewer environmental impacts than those of the on-site in-situ TE. Much of the difference was attributable to 73% of the energy in the in-situ TE being consumed in methanol recovery. Nevertheless, the in-situ TE process gained better scores in terms of respiratory organs and land occupation. A sensitivity analysis of energy usage on transportation distances and fuel consumption rates suggested that an on-site in-situ TE process could be viewed as more favorable once the transportation distance is greater than 180km with 7km/L of fuel consumption rate.

Analysis of energy usage for RTG cranes

The purpose of this paper is to study and analyse the energy that is used by the various motors of a crane of the Rubber Tyred Gantry type. For this reason a single Rubber Tyred Gantry (RTG) crane has been instrumented at port of Felixstowe and data has been collected during normal operation for eight days. This data has been analysed in terms of active and idle modes and also in terms of energy usage by the various motors. From this analysis it is possible to determine that on average about half of the energy consumed is potentially recoverable. It is also estimated that the recovery of this proportion of energy could lead to savings of 32,600 L of fuel and 8100 tonnes of CO2 per year at Port of Felixstowe.

Low Cost Disaggregation of Smart Meter Sensor Data

This paper proposes a novel load disaggregation algorithm, based on non-intrusive appliance monitoring that provides accurate results without the need of the reactive power component. The proposed technique requires the minimum possible number of sensor meters within the smart meter hardware and reduces the data traffic of the advanced metering infrastructure network, since it processes the only low-frequency smart meter data of the active power component of a residential unit. We propose a three-stage process for energy usage analysis, based on pulse extraction, pulse clustering and classification, and pulse to appliance association. The smart meter data are decomposed into a discrete set of pulses, and each pulse is associated with the operation of the appliances. The outcome of the algorithm is a pulse to appliance association that creates a daily load disaggregation map for the residential unit. In addition, this paper presents an overview and comparison of existing solutions that will help the reader obtain a good overview of the landscape of load disaggregation from smart meter sensor readings.

Analysis of energy usage in Nd–Fe–B magnet to magnet recycling

The recycling of Nd–Fe–B-type sintered magnets has received a great deal of attention over the past 15 years, but commercially viable and environmentally friendly solutions have remained elusive, until now. Here we report on the recycling of waste magnets using a novel “magnet-to-magnet” approach and show that it can work on a commercial scale. As part of the study, we have evaluated material supply, energy consumption, and the overall environmental and economic benefits of magnet-to-magnet recycling, compared to the traditional manufacturing of “virgin” magnets. We also demonstrate how the magnet-to-magnet recycling approach can reduce energy consumption by more than 45%, during magnet production, with overall savings exceeding 90% when we also consider raw-materials production.

Design of an Embedded Sensor Network for Application in Energy Monitoring of Commercial and Industrial Facilities

The deployment of energy monitoring systems is well established for industrial facilities and commercial buildings, however these systems are insufficient where large variations in activity level (production variation, one-off events) are common. In such cases, accurate analysis of energy usage requires the deployment of a flexible embedded sensor network that can capture data at the required level of accuracy and granularity and can associate the energy usage data with the context and activity that has caused it. This research proposes an approach and a set of hardware and software tools for the monitoring of energy usage in technical building services and the association of that data with real-time production information in advanced manufacturing facilities.The system developed incorporates an embedded controller with sensors to monitor the physical environment, an integrated energy analyser to monitor electricity consumption and a visualisation interface that associate events in the physical world with the actual energy consumption recorded. The creation of a detailed time-stamped energy profile for the process can then be used in the identification of energy saving opportunities. A case study from a pharmaceutical facility was used to validate the operation of the system.

A Comparative Analysis of Energy Usage and Energy Efficiency Behavior in Low- and High-Income Households: The Case of Kitwe, Zambia

Energy efficiency has been an important topic since the latter part of the last century. This is because adoption of energy efficiency measures has been acknowledged as one of the key methods of addressing the negative impact of climate change. In Zambia, however, the need to adopt energy efficiency measures has not just been driven by the imperative to mitigate the negative effects of climate change but also by a critical shortage of energy. This research looks at households’ energy consumption behavior in low- and high-income areas of Kitwe. Recent studies on the relationship between household energy consumption and behavioral lifestyle have been descriptive, with limited emphasis on the relationships between various variables. In this study, descriptive and inferential statistics have been used to investigate relationships between the two income groups and various energy consumption-related variables such as knowledge about energy reduction measures, energy saving strategies, barriers to the use of energy saving strategies, and the motives for using energy reduction strategies. Methodologically, the study was largely quantitative in nature, with questionnaires administered to a combined total of 56 households. However, key interviews were also conducted that helped us to get a clearer understanding of some of the issues covered in the research. Key findings are that whereas the descriptive statistics show that there are behavioral differences between the two income groups, the inferential statistics show that there is no relationship between income level and the energy efficiency variables. This has been found to be consistent with results from studies done elsewhere. The key lesson is that there is low usage of energy efficiency measures in both low- and high-income areas and that the authorities need to change the way information is disseminated to consumers from the current method of advertising to social diffusion.

Energy usage analysis of digital modulations in wireless sensor networks with realistic battery model

A wireless sensor network is a collection of tiny sensor nodes that are deployed to monitor a physical environment. These sensor nodes are generally powered by non-renewable batteries and maybe deployed in harsh environment. Thus, energy resource is precious that makes protocols design for this kind of networks a crucial challenge. Especially, in physical layer, orthogonal modulations as PPM or FSK are suitable. The commonly used models to investigate the network lifetime are based on a linear battery discharge. Really, the battery discharge is closely bonded to the discharge current, and typically is non-linear. This paper presents a performance analysis of both PPM and FSK modulations used in battery powered wireless sensor node. A Rakhmatov---Vrudhula---Wallach model is used to evaluate the used battery charge for a given instantaneous current load. By numerical results, it is proved that PPM modulation outperforms FSK one in term of battery charge use for different network density and for different M-ary signaling schemes.

Development of Emission Control Devices for Petrol Engines (Catalytic Convertor)

Petrol power inevitably finds a very important role in the development of the plant’s economy and technical growth. Inspite of their high thermal efficiency, one cannot ignore the fact about the effect of their exhaust, in the atmosphere. It is a well-known fact that the toxic gases emitted in petrol engines are less than the engines. Due to high cost of petrol, petrol engines are more in use. Anticipating the use of petrol engines, even more in the near future; this system developed can be used to control the toxic gases, coming out of the petrol engines. These toxic gases are harmful not only to the atmosphere, but also to the human & animal race. Objective of this project is to design & fabricate a simple system, where the toxic levels are controlled through chemical reaction to more agreeable level. This system acts itself as a silencer; there is no need to separate the silencer. The whole assembly is fitted in the exhaust pipe; it does not give rise to any complications in assembling it. This system is Very cost effective and more economical. The automobiles play an important role in the transport system. With an increase in population and living standard, the transport vehicles as well as car population is increasing day by day. In addition to this there is a steep increase in the number of two wheelers during the last two decades. All these are increasing exhaust pollution and particularly in metros as density of these vehicles in metros are very high. The main pollutants contributed by I.C. engines are CO, NOX unburned hydrocarbons (HC) and other particulate emissions. Other sources such as Electric power stations, industrial and domestic fuel consumers also add pollution like NOX, SO2 and particulate matters. In addition to this, all fuel burning systems emit CO2 in large quantities and this is more concerned with the Green House Effect, which is going to decide the health of the earth. Lot of efforts is made to reduce the air pollution from petrol and diesel engines and regulations for emission limits are also imposed in the USA and in a few cities of India. An extensive analysis of energy usage and pollution shows that alternative power systems are still a long way behind the conventional ones. Further developments in petrol and diesel engines, combined with improvements in the vehicles, will make fuel consumption reduction of 40% or more in the future cars.This, in turn, will reduce the CO2 emissions, a gas which is responsible for the greenhouse effect.