Energy Consumption Parameters Research Articles

A new clustering and visualization method to evaluate urban heat energy planning scenarios

Spatial visualization is a very useful tool to help decision-makers in the urban planning process, i) to define future energy transition pathways, ii) to implement energy efficiency strategies and iii) to integrate renewable energy technologies in the context of sustainable cities. There is thus a need to develop new tools to understand the energy consumption patterns across cities. Statistical methods are often used to understand the driving parameters of energy consumption but rarely used to evaluate future urban refurbishment scenarios. Simulating whole cities using energy demand softwares can be very extensive in terms of computer resources and data collection. A new methodology, using city archetypes, is hence proposed to simulate the energy consumption of urban areas and to evaluate urban energy planning scenarios. The objective of this paper is to present a solid framework and innovative solution for the computation and visualization of energy saving at the city scale. The energy demand of cities, as well as the microclimatic conditions, are calculated by using a 3D model designed as function of the real city urban geometrical and physical characteristics. Data are extracted from a GIS database. We demonstrate how the number of buildings to be simulated can be drastically reduced thereby significantly decreasing the computational time and without compromising the accuracy of the results. This model is then used to evaluate the influence of two sets of refurbishment solutions. The energy consumption are then integrated back in the GIS to identify the areas in the city where refurbishment works are needed more rapidly. The city of Settimo Torinese (Italy) is used as a demonstrator for the proposed methodology, which can be applied to medium-sized cities worldwide with limited amount of information.

Improvement of the Dynamic Priority Scheduling Algorithm Based on a Heapsort

The earliest deadline first (EDF) scheduling algorithm is a typical representative of the dynamic priority scheduling algorithm. However, once the system is overloaded, the deadline miss rate increases and the scheduling performance deteriorates sharply, which causes a reduction in system resource utilization. To overcome this problem, we proposed an improved dynamic priority scheduling algorithm based on heap sorting. The task deadline, task value, energy consumption, and other parameters were introduced. The fuzzy analytic hierarchy process (FAHP) and the value density method were then used to determine the comprehensive priority of tasks. A heapsort algorithm with a lower time complexity was used to sort the comprehensive priority index so as to reduce the sorting overhead of the system. The system sorting overhead was then introduced to improve the decision condition of the priority scheduling subset and expand the schedulable range of the algorithm. The experimental results showed that the improved method reduced the deadline miss rate by an average of 0.1789, which improved the scheduling performance of the algorithm. The optimized scheduling algorithm can be applied to industrial control to improve system efficiency, and reasonable resource scheduling can reduce data center costs.

The use of combined convection-microwave processing line for drying fruits and vegetables

The article presents the experience of operating microwave drying plants, which are used in the technology of processing agricultural raw materials. The technological solutions for the development and use of microwave conveyor drying plants for drying plant materials were proposed. The obtained parameters of energy consumption and dynamics of the drying process allowed to determine close to the optimal transition boundary of the energy supply. The optimum value of transient humidity (at the boundary of the microwave and convective modules) is determined to be in the range from 28 to 35 %. The use of the combined energy supply method in drying technologies for fruits and vegetables allows to reduce the energy consumption of the process by 20-30 %. The examples of successful implementation of the proposed drying method in the food industry are given.

A Study about Energy Demand and Consumption in the Cement Industrial Sector in the Brazilian State of Minas Gerais

The Portland cement is one of the most important building materials and highly employed by mankind. Its high participation in human development, as a basic material for any type of construction, characterizes the cement industry as one of the main sectors for the economic and social development. It represents approximately 3% of energy consumption in Minas Gerais (MG), a Brazilian State. To perform this study, it was collected a set of energy consumption parameters and process data, besides economic indicators. Minas Gerais houses the majority of cement plants installed in Brazil. Each stage of production was identified and quantified as related to the energy consumption. Initially, the projection of the final consumption of the main energy sources was developed with the average growth method. Then, the future energy demand was calculated using the ENPEP-BALANCE model, for a 20-year analysis period. Results showed that the final energy demand of this sector in the State of Minas Gerais could vary from 1,475 to 2,642 thousand toe, which represents about 34% more or less 15% of the registered demand of the base year. Last, CO2 emissions were projected for the considered scenarios.

Energy Consumption Analysis of DBR and VBF Protocols in Underwater Sensor Networks Using Aqua-Sim at Network Simulator 2

For decades, there have been significant interests in monitoring the aquatic environment for scientific exploration, commercial exploitation, coastline protection, and even disasters prevention and mitigation such as tsunami warnings. Highly precise, real-time, and temporal-spatial continuous aquatic environment monitoring system is extremely important for underwater life. To support and simulate such monitoring system, underwater sensor networks (UWSN) have emerged as a very powerful technique for many applications on underwater environment, including monitoring, measurement, surveillance, and control by using Aqua-Sim. Aqua-Sim is a simulator for UWSN developed on Network Simulator 2 platform which effectively simulates the attenuation of underwater acoustic channels and the collision behaviors in long delay acoustic networks. Currently, there are several routing protocols for UWSN which are implemented in Aqua-Sim. On this research, we did a simulation on Aqua-Sim by performing Vector-based Forwarding (VBF) protocol and Depth-based Routing (DBR) protocol performance analysis based on energy consumption parameter. Based on the result, it can be concluded that the VBF routing protocol requires more energy consumption than the DBR routing protocol.

Assessing the energyperformance of existing buildings based on measurement data. Case study

Energy certification for existing buildings and selecting the most appropriate measures in order to classify these buildings as Near Zero EnergyBuildings (NZEB), and therefore complying with specific regulation requirements, implies accessible models and methodologies capable of accurately reflecting the actual energy behavior of buildings and to ensure the optimal quality.Methods based on real data processing, resulting from the monitoring of indoor / outdoor environmental parameters and energy consumption over time, provide results comparable with real scenarios as well as the possibility of validating models and methodologies complying with existing regulations.The method of total heat loss / energy signature, based on the linearity relationship between energy consumption and environmental parameters, is widely used due to its simplicity of application. This method has been used to assess the energy performance for a single-family dwelling designed with a high level of energy efficiency. Results of the analysis revealed an appropriate level of thermal insulation characteristic to the building, reflected in low energy consumption for heating, but also a relatively low thermal inertia, which negatively impacts the energy performance. Comparison between the energy consumption/annual energy demandsfor heating, determined through various methods, recommends the regression approach as a useful tool for validating the various methods used when estimating the energy performance of existing buildings.

Parameters optimization and control strategy of power train systems in hybrid hydraulic excavators

This paper studies on parameters matching and control strategy of power train systems for hybrid hydraulic excavators (HHEs). Load profiles of a 20-t excavator are measured and analyzed. Based on load profiles, considering working conditions, actual load and energy saving, a method which combines analysis method with model-based method together is proposed so as to give full play to the energy conservation and driving characteristics of hybrid power train system (HPTS) in HHE. Mechanical models and efficiency models of HPTS are built. Dynamic programming (DP) algorithm is used to control the HPTS in HHE under different system parameters. Genetic algorithm (GA) is employed to acquire HPTS parameters for optimal energy consumption. The simulation results show that the efficiency of the HHE is improved by 8.80% compared with that of traditional excavator. Experiments are carried out and a rule-based control method is used to validate the effectiveness of the designed parameters.

Effect of Density and Fiber Size on Porosity and Thermal Conductivity of Fiberboard Mats

The thermal conductivity and porosity of fiberboard mats are crucial parameters for efficient energy consumption of the hot-pressing process and for final panel quality. In this work, the effect of fiber size and mat density on porosity and thermal conductivity of the mat were investigated. The fiber size was characterized as fine, medium and coarse. The mat porosity was measured by image analysis using the black and white contrast method. The thermal conductivity was determined at different density levels with a temperature gradient of 1.6 °C mm−1 and 7.6% (s = 0.3) moisture content. The results showed that fiber size was a dominant variable governing heat conduction and mat porosity. The mats made with medium size fibers showed a higher resistance to compression. The thermal conductivity of coarse fiber mats decreased drastically between 700 kg m−3 and 810 kg m−3. This was likely due to a higher fracture frequency observed for coarse fibers in comparison to the other fiber sizes studied. Hence, the fine and medium fibers conducted heat more efficiently. Moreover, fiber bundles and fractured fibers were observed during the mat porosity measurements, principally in mats made with fine fiber size.

Integration of Missing Parameters into a DES Tool

Products are usually made by accomplishing a series of manufacturing processes in a sequential flow line that is also known as a manufacturing system. Today, lean methods are widely adopted by many manufacturing plants as a popular model in designing, implementing, operating or managing a manufacturing system. It has been proved as a cost-effective approach to boost system efficiency and productivity by consistently seeking and removing any non-value added activities (i.e., wastes) during a production with a small or without any additional investment. Nevertheless, identification of these wastes using the traditional lean methods does not include such wastes as amounts of energy consumption and CO2 emissions. For human centered assembly lines, for instance, it is reported that applying highly skilled, flexible and dynamic workers into production lines is also a good practice for implementing a lean manufacturing system in which each worker performs multiple tasks amongst stations. On the other hand, most studies on manufacturing systems using the modelling simulation methods failed to consider parameters of energy consumption, CO2 emissions and human factors that may also impact the overall system performance. The simultaneous prediction, which relates to amounts of energy consumption and CO2 emissions and effects of human factors (or human performance) for a manufacturing system evaluation, is often overlooked by researchers or system designers partially due to a lack of existing DES (discrete event simulation) tools that enable incorporating these parameters into an established DES model. This paper presents a study by addressing these issues aiming to incorporate these missing parameters of energy consumption, CO2 emissions and human factors (age and experience) into a DES model.

A mathematical model and relevant index prediction for constant-temperature electric heating of dual-horizontal-well SAGD start-up

Through Laplace transform and Stehfest numerical inversion, this research established a mathematical model for constant temperature electric heating of dual-horizontal-well steam-assisted gravity drainage (SAGD) start-up. To verify the model, a finite element simulation based on a typical SAGD block was completed, which proved the excellent agreement between the model solution and simulation results. Moreover, by means of superposition principle, underground temperature distribution and energy-related parameters during the multiwell operation were obtained, as well as a computational method targeted at quantifying the conserved energy, water and fuel of electric heating against steam heating. A parametric sensitivity analysis of electric heating was undertaken, which proved that the start-up effect is most sensitive to heating temperature, featuring a nonlinear negative correlation. Additionally, start-up effect is positively linear-correlative to porosity, and negatively linear-correlative to wellbore radius and oil saturation. The proposed model can be employed to predict key indexes such as underground temperature distribution, energy-consumption parameters, and accumulated conserved amounts of energy, water and fuel versus steam heating. Under a specified terminal temperature, temporal and energy quantities required by the start-up can also be determined.

Global lower limb muscle coactivation during walking at different speeds: Relationship between spatio-temporal, kinematic, kinetic, and energetic parameters

Muscle coactivation is the mechanism that regulates the simultaneous activity of antagonist muscles around the same joint. During walking, muscle joint coactivation varies within the gait cycle according to the functional role of the lower limb joints. In the present study, we used a time-varying multi-muscle coactivation function (TMCf) with the aim of investigating the coactivation of 12 lower limb muscles and its relationship with the gait cycle, gait speed (low, self-selected, and fast), ground reaction force, gait variability, and mechanical energy consumption, and recovery in a sample of 20 healthy subjects. Results show that the TMCf is speed dependent and highly repeatable within and between subjects, similar to the vertical force profile, and negatively correlated with energy recovery and positively correlated with both energy consumption and balance-related gait parameters. These findings suggest that the global lower limb coactivation behavior could be a useful measure of the motor control strategy, limb stiffness, postural stability, energy efficiency optimization, and several aspects in pathological conditions.

Вплив нових регуляторів росту рослин — похідних n-оксид піридину на рухову активність і енергетичний стан інфузорій tetrahymena pyriformis w

The study objective was to determine the functional state of infusoria Tetrahymena pyriformis W by parameters of motor activity and energy consumption for movements under acute effects of plant growth regulators — N-oxide pyridine derivatives, their complexes with organic acids and metal salts. Materials and methods. 2,6-dimethylpyridine-N-oxide, 2-methylpyridine-N-oxide and their complexes with organic acids (succinic, maleic) or metal salts (ZnCl2, ZnI2, CoCl2, MnCl2) — in total, 13 substances, synthesized at the Institute of Bioorganic Chemistry and Petrochemistry of the National Academy of Sciences of Ukraine have been used in the work. Studies have been carried out on the infusoria Tetrahymena pyriformis W in isotoxic doses — at the level of toxic concentrations — LC50, LC16 and inactive concentrations (LC0). Motor activity and energy state of infusoria using an automated laser Doppler spectrometer were evaluated. Results and conclusion. It was shown that the studied N-oxide pyridine derivatives and their complexes with organic acids or metal salts inhibit the motor activity of the infusoria and increase energy consumption for movements with the greatest effect in the concentrations of the corresponding LC50. 2,6-dimethylpyridine-N-oxide, 2-methylpyridine-N-oxide, and their complexes with succinic acid and metal salts of CoCl2 and ZnCl2 were the most toxic for the viability of infusoria. Therefore in order to assess the toxicity ofxenobiotics and viability of infusoria Tetrahymena pyriformis W, it is reasonable to recommend parameters of motor activity and energy consumption per unit of the rout that have the highest criterial significance. Key words: toxicity, plant growth regulators, N-oxide pyridine derivatives, Tetrahymena pyriformis W.

A Survey of Underwater Acoustic Sensor Network using R-MAC-MAC Layer Protocol and VBF-Routing Protocol

Objectives: Under-Water Sensor Network (UWSN) has many potential applications. For these applications it is necessary to have efficient and reliable communication. For efficient communication we need to develop efficient networking solutions to overcome the underwater environment challenges. Methods: To develop efficient solutions for networking we require to understand the potential applications for the underwater sensor network it is also necessary to understand the limitations of the environment. It is also essential to understand different architectures that are there in UWSN. Using these information\'s, we have designed a network with 6 nodes and simulated it using Aquasim software. We have selected one specific MAC layer and network layer protocol. For this we have simulated for the Packet Delivery Ratio (PDR), throughput and energy consumption parameters. Findings: Paper talks about the 2D UWSN architecture, the challenges in the implementation of UWSN, the MAC and Network layer used. We can anticipate the general energy consumption, through put and PDR for this combination of Radio Multiple ACcess (RMAC) and Vector-Based Forwarding (VBF) protocols. This simulation shows us that this combination follows the required trend and they are the suitable protocols to be used in UWSN implementations. Improvements: Applications of UWSN are fast gaining popularity to make it possible to monitor the ocean, surveillance of deep sea, various entities tracking of aquatic environment, etc. For all these applications the energy efficiency is ansignificant factor for communication. Comparative studies show that R-MAC is the most energy efficient MAC layer protocol and VBF has better PDR and throughput compared to other network layer protocols. Keywords: Data Throughput, Energy Consumption, Packet Delivery Ratio, Radio-Multiple ACcess (R-MAC), Under-Water Sensor Network (UWSN), Vector Based Forwarding

System-level energy consumption modeling and optimization for cellulosic biofuel production

As a promising alternative to fossil fuels, cellulosic biofuel has obtained considerable interest due to its potential for mitigating global climate change and enhancing energy security. However, the widespread adoption of cellulosic biofuel is taking place in a slower pace than expected. One major challenge is that the cellulosic biofuel production is still highly energy-intensive. In fact, the energy contained in cellulosic biofuel is less than the energy required for its production. To address this issue, in this paper, an analytical system-level energy model is proposed to characterize the fundamental relationships between total energy consumption and biofuel production parameters in cellulosic biofuel production systems. Furthermore, an optimization strategy based on Particle Swarm Optimization (PSO) is adopted to minimize the energy consumption of cellulosic biofuel production while maintaining the desired biofuel yield. A baseline case is implemented for analyzing energy consumption, and the results show that pretreatment consumes most energy among all processes and the water/biomass ratio is the most significant energy driver. In addition, the optimal solution results in a 21.09% reduction in the total energy consumption compared to the baseline case.

Performance Evaluation of DV-HOP and Amorphous Algorithms based on Localization Schemes in Wireless Sensor Networks

In the field of high-risk observation, the nodes in Wireless Sensor Network (WSN) are distributed randomly. The result from sensing becomes meaningless if it is not known from where the originating node is. Therefore, a sensor node positioning scheme, known as the localization scheme, is required. The localization scheme consists of distance estimation and position computing. Thus, this research used connectivity as distance estimation within range free algorithm DV-Hop and Amorphous, and then trilateral algorithm for computing the position. Besides that, distance estimation using the connectivity between nodes is not needed for the additional hardware ranging as required by a range-based localization scheme. In this research compared the localization algorithm based on range free localization, which are DV-Hop algorithm and Amorphous algorithm. The simulation result shows that the amorphous algorithm have achieved 13.60% and 24.538% lower than dv-hop algorithm for each parameter error localization and energy consumption. On node density variations, dv-hop algorithm gained a localization error that is 26.95% lower than amorphous algorithm, but for energy consumption parameter, amorphous gained 14.227% lower than dv-hop algorithm. In the communication range variation scenario, dv-hop algorithm gained a localization error that is50.282% lower than amorphous. However, for energy consumption parameter, amorphous algorithm gained 12.35%. lower than dv-hop algorithm.

Electrochemical Decontamination Process an Effective Alternative to Treat Textile Effluents

Keeping in view the growing concern regarding aquatic pollution by effluent water from textile industries containing complex compounds, the present study was under taken with the view to study the efficiency of the removal by electrochemical oxidation. In recent year the use of electrochemistry for the investigation of environmental pollution is being thoroughly investigated. Reactive dye mainly composed of complex organic molecules are highly stable to decomposition in normal condition. Textile industry wastewater containing dyes poses a chronic and synergistic effects to environment. This study examines the electrochemical oxidation of the organic dyes. All the experiments were performed using a Filter Press Flow Cell Reactor containing Ti/Ti0.7Ru0.3O2 anode and stainless steel as cathode in which impact of the current density (5 – 20 mA cm-2), electrolytes (NaCl, Na2SO4, H2SO4), Sodium chloride concentration (0.02 – 0.10 mol L-1) were studied. The electrode used were characterized by the cyclic voltammetry experiments. The Reaction Kinetics and energy consumption parameters were studied of the electrochemical process. Results obtained in this research clearly demonstrated that the effect of the electro generated strong oxidant species active chlorine, depends on electro catalytic mechanism followed on surface of Ti/Ti0.7Ru0.3O2 resulting in the improvement of the color. Results also confirmed a high removal efficiency according to environment and electrolyte used in the process. However, there is a limit of NaCl for treating real effluents avoiding the formation of organochloride compounds; and it is a subject of critical importance, from the environmental point of view, to apply this alternative treatment. Keyword: textile effluents, contaminants, electrochemical process, Kinetics

Carbon footprint of integrated waste management systems with implications of food waste diversion into the wastewater stream

This paper introduces a comprehensive model developed to assess the carbon footprint of integrated solid waste management systems including the diversion at source of the food waste component into the wastewater/sludge management systems using household food waste disposers. In addition to the current state of practice in developed economies, the model includes emissions from waste management processes still practiced in developing economies (such as open dumping, open burning, poorly operated landfills with flaring systems and auxiliary fuel needed to satisfy the low heating value (LHV) during incineration) commonly not considered in most life cycle assessment (LCA)-based models. It can disaggregate emissions by source (from collection to final disposal), or type (direct-operating, indirect-upstream, indirect-downstream), or gas (CH4, CO2, N2O) and offers users the flexibility to select processes or modify input parameters while examining their impact on uncertainty in model simulations. Equally important is a clarity in deriving and applying emission factors used to quantify emissions from waste management systems. The model was tested in the context of developed and developing economies to assess the impact of waste composition, management processes, energy consumption and other parameters on variations in emissions. The results demonstrated that best practices through material recycling, biological treatment, food waste diversion, and/or energy recovery can contribute to significant savings in emissions that ranged between 24 and 95%, depending on the tested systems. In closure, we argue the benefits of the model application in providing guidelines for policy planning and decision making about process viability for investing in carbon credit.

The influence of biopreparations on the reduction of energy consumption and CO2 emissions in shallow and deep soil tillage

The application of innovation in agriculture technologies is very important for increasing the efficiency of agricultural production, ensuring the high productivity of plants, production quality, farm profitability, the positive balance of used energy, and the requirements of environmental protection. Therefore, it is a scientific problem that solid and soil surfaces covered with plant residue have a negative impact on the work, traction resistance, energy consumption, and environmental pollution of tillage machines. The objective of this work was to determine the dependence of the reduction of energy consumption and CO2 gas emissions on different biopreparations. Experimental research was carried out in a control (SC1) and seven different biopreparations using scenarios (SC2–SC8) using bacterial and non-bacterial biopreparations in different consistencies (with essential and mineral oils, extracts of various grasses and sea algae, phosphorus, potassium, humic and gibberellic acids, copper, zinc, manganese, iron, and calcium), estimating discing and plowing as the energy consumption parameters of shallow and deep soil tillage machines, respectively. CO2 emissions were determined by evaluating soil characteristics (such as hardness, total porosity and density). Meteorological conditions such average daily temperatures (2015–20.3 °C; 2016–16.90 °C) and precipitations (2015–6.9 mm; 2016–114.9 mm) during the month strongly influenced different results in 2015 and 2016. Substantial differences between the averages of energy consumption identified in approximately 62% of biological preparation combinations created usage scenarios. Experimental research established that crop field treatments with biological preparations at the beginning of vegetation could reduce the energy consumption of shallow tillage machines by up to approximately 23%, whereas the energy consumption of deep tillage could be reduced by up to approximately 19.2% compared with the control treatment. The experimental research results reveal the reduction of CO2 emissions in shallow tillage to approximately 20.14% (and that in deep tillage to approximately 19.16%) when works were performed by different biological preparation usage scenarios. This experimental research demonstrates the efficient use of the special adaptation of a new biotechnological method for the reduction of the energy consumption and CO2 gas emissions of agricultural machinery.

Biodiesel production from waste cooking oil using heterogeneous catalysts and its operational characteristics on variable compression ratio CI engine

In the present work, the optimum biodiesel conversion from waste cooking oil to biodiesel through transesterification method was investigated. The base catalyzed transesterification under different reactant proportions such as the molar ratio of alcohol to oil and mass ratio of catalyst to oil was studied for optimum production of biodiesel. The optimum condition for base catalyzed transesterification of waste cooking oil was determined to be 12:1 and 5 wt% of zinc doped calcium oxide. The fuel properties of the produced biodiesel such as the calorific value, flash point and density were examined and compared to conventional diesel. The properties of produced biodiesel and their blend for different ratios (B20, B40, B60, B80 and B100) were comparable with properties of diesel oil and ASTM biodiesel standards. Tests have been conducted on CI engine which runs at a constant speed of 1500 rpm, injection pressure of 200 bar, compression ratio 15:1 and 17.5, and varying engine load. The performance parameters include brake thermal efficiency, brake specific energy consumption and emissions parameters such as Carbon monoxide (CO), Hydrocarbon (HC), Oxides of Nitrogen (NOx) and smoke opacity varying with engine load (BP). Diesel engine's thermal performance and emission parameters such as CO, HC, and NOx on different biodiesel blends demonstrate that biodiesel produced from waste cooking oil using heterogeneous catalyst was suitable to be used as diesel oil blends and had lesser emissions as compared to conventional diesel.

Actual energy and environmental savings on energy retrofit works at the Lakes Estate, Milton Keynes

The EU 2020 package sets three legally binding climate and energy targets: 1) a 20% cut in greenhouse gas emissions (from 1990 levels); 2) 20% of EU energy from renewables; and 3) a 20% improvement in energy efficiency. In the UK, the Milton Keynes Council has sought to an implement energy performance retrofit of their building stock to achieve these targets.This research study was conducted to determine whether the abovementioned targets could be achieved, and in order to gain further understanding over the impact of the energy retrofits on the environmental conditions at each property and the behaviour of tenants. Therefore, a sample of eight council-owned properties on the Lakes Estate, representative of 70% of the council’s stock, were monitored from January 2015 to April 2016. Energy consumption and environmental parameters were measured before and after refurbishment. Building fabrics were tested pre- and post-retrofit, and a Standard Assessment Procedure (SAP) evaluation was completed. Further, occupancy behaviour surveys were conducted before and after to understand occupant energy demand and habits.On average, total gas usage was reduced by 24%, despite the average internal temperatures for the equivalent periods in pre- and post-retrofit being higher post-retrofit while the total energy demand was reduced by 14%. At the same time energy efficiency ratings improved by an average of 19% (10 SAP points).