Energy Cost Evaluation Research Articles

Wind energy cost evaluation based on a techno-economic assessment in the Algerian highlands

Wind energy is an important and growing source of renewable energy. It is becoming increasingly integrated into electricity markets around the world. In Algeria in particular, the integration of wind power into the electricity grid is being developed based on a government project to achieve a high penetration rate. In this context, this study is elaborated to analyse the techno-economic assessment of the electrical energy production from four selected wind turbines: Vestas V-80; Suzlon S-82; Enercon E-58 and Gamesa G-114, installed at three sites in the Algerian highlands, namely El Beidh, Sétif and Djelfa. The three highland sites are chosen due to their good wind potential. On the other hand, the Algerian transmission electrical network DZ-114 bus presents some technical problems in the highlands related to low voltage profiles. Therefore, wind farm integration in these three sites can be beneficial as voltage magnitude support. Besides, it can be an important tool to reduce fossil fuel consumption and pollutant gases from conventional plants. Wind potential assessment and economic analysis were carried out for the three selected sites using wind speed data measured 10 m above ground level over 10 years. The results obtained confirm that the Gamesa G114 wind turbine is the most suitable for all the sites and in particular for El Bayadh, as it offers both the highest annual energy production (AEP) and capacity factor (CF) values in all the selected sites and guarantees the lowest unit energy cost (UEC) compared to other types of wind turbines.

Evaluation of rational energy costs for liquid dispersion in piston compressors with a two-phase working fluid

Evaluation of rational energy costs for liquid dispersion in piston compressors with a two-phase working fluid

Evaluation of Performance, Energy, and Computation Costs of Quantum-Attack Resilient Encryption Algorithms for Embedded Devices

Evaluation of Performance, Energy, and Computation Costs of Quantum-Attack Resilient Encryption Algorithms for Embedded Devices

Energizing Inventory Management to Optimize Energy Consumption of Handling Shortages by Neutrosophic Fuzzy Trapezoidal Number

Embarking on the exploration of integrating environmental sustainability principles and neutrosophic fuzzy theory in inventory management, this study aims to effectively tackle shortages. It underscores the vital balance between economic efficiency and ecological responsibility in contemporary inventory management practices. Neutrosophic fuzzy theory emerges as a robust tool for navigating the inherent uncertainties in inventory optimization, offering a versatile framework for modelling intricate problems. Strategies for optimizing resource consumption and minimizing waste generation within inventory management are scrutinized, emphasizing the imperative of harmonizing economic objectives with environmental concerns. Introducing a novel framework that melds neutrosophic fuzzy with environmental metrics, the research aims to optimize inventory management processes while mitigating environmental impacts. Furthermore, it delves into the challenges of managing energy consumption, advocating for innovative approaches to address fluctuating energy prices, data limitations, and evolving regulatory requirements. Neutrosophic sets are introduced for energy consumption analysis and cost evaluation, showcasing their efficacy in managing uncertainty and variability in real-world scenarios. The study concludes with a Python-based analysis of neutrosophic mean in energy consumption, offering insights into central tendencies and uncertainties associated with energy-related costs. Utilizing visualization techniques to enhance comprehension and decision-making in energy management, this research contributes to advancing inventory management practices by integrating environmental sustainability principles and sophisticated mathematical techniques, thereby fostering more resilient and sustainable supply chain operations.

Leveraging Larger AES Keys in LoRaWAN: A Practical Evaluation of Energy and Time Costs.

Internet of Things (IoT) devices increasingly contribute to critical infrastructures, necessitating robust security measures. LoRaWAN, a low-power IoT network, employs the Advanced Encryption Standard (AES) with a 128-bit key for encryption and integrity, balancing efficiency and security. As computational capabilities of devices advance and recommendations for stronger encryption, such as AES-256, emerge, the implications of using longer AES keys (192 and 256 bits) on LoRaWAN devices' energy consumption and processing time become crucial. Despite the significance of the topic, there is a lack of research on the implications of using larger AES keys in real-world LoRaWAN settings. To address this gap, we perform extensive tests in a real-world LoRaWAN environment, modifying the source code of both a LoRaWAN end device and open-source server stack to incorporate larger AES keys. Our results show that, while larger AES keys increase both energy consumption and processing time, these increments are minimal compared to the time on air. Specifically, for the maximum payload size we used, when comparing AES-256 to AES-128, the additional computational time and energy are, respectively, 750 ms and 236 μJ. However, in terms of time on air costs, these increases represent just 0.2% and 0.13%, respectively. Our observations confirm our intuition that the increased costs correlate to the number of rounds of AES computation. Moreover, we formulate a mathematical model to predict the impact of longer AES keys on processing time, which further supports our empirical findings. These results suggest that implementing longer AES keys in LoRaWAN is a practical solution enhancing its security strength while not significantly impacting energy consumption or processing time.

Evaluation of Energy use Intensity and Cost of Institutional Buildings using Building Information Modelling

Evaluation of Energy use Intensity and Cost of Institutional Buildings using Building Information Modelling

Optimization of Power Dispatch With Load Scheduling for Domestic Fuel Cell-Based Combined Heat and Power System

This study proposes an optimization scheme of thermal power and electric power dispatch integrated with load scheduling for the domestic fuel cell-based combined heat and power (DFCCHP) system. The scheme is implemented in home energy management systems installed in smart homes. To provide accurate energy cost evaluation for the optimization scheme, the nonlinear electric efficiency characteristics of the fuel cell are approximated with a polynomial expression. Along with the inclusion of thermal power dispatch in the scheme, the nonlinear relationship between the thermal power and the electric power of the fuel cell is incorporated to design temperature constraints in the DFCCHP system. On top of the nonlinearity and complexity of the fuel cell, residential electric load scheduling and other energy sources including the power grid, PV panels, and battery energy storage are considered to ensure that the scheme takes a comprehensive energy management approach. Because of the nonlinearity that exists in the modeling of the DFCCHP system, a mixed-integer nonlinear programming formulation is utilized to solve the optimization problem. The scheme is tested in a day-ahead environment with time-varying electricity prices and natural gas prices. The optimization aims to minimize the electricity cost and natural gas cost. It is shown in the simulation that optimization scheme dispatches the electric power and thermal power in an optimal way so that the energy cost due to time-varying electricity prices and natural gas prices is minimized. The electricity cost optimization puts both power purchase and power selling into consideration. It is also shown in the simulation that the household loads are scheduled in an optimal way to the time slots with lower electricity prices in accordance with the optimal thermal and electric power dispatch.

Evaluation of energy use intensity (EUI) and energy cost of commercial building in India using BIM technology

Evaluation of energy use intensity (EUI) and energy cost of commercial building in India using BIM technology

Hull and Aerial Holonomic Propulsion System Design for Optimal Underwater Sensor Positioning in Autonomous Surface Vessels.

Acoustic Doppler Current Profiler (ADCP) sensors measure water inflows and are essential to evaluate the Flow Curve (FC) of rivers. The FC is used to calibrate hydrological models responsible for planning the electrical dispatch of all power plants in several countries. Therefore, errors in those measures propagate to the final energy cost evaluation. One problem regarding this sensor is its positioning on the vessel. If placed on the bow, it becomes exposed to flowing obstacles, and if it is installed on the stern, the redirected water from the boat and its propulsion system change the sensor readings. To improve the sensor readings, this paper proposes the design of a catamaran-like Autonomous Surface Vessel (ASV) with an optimized hull design, aerial propulsion, and optimal sensor placement to keep them protected and precise, allowing inspections in critical areas such as ultra-shallow waters and mangroves.

Comparative evaluation of energy costs at differ-entmethods of electrode wire supplyin mechanized arc welding processes

Problems of energy saving in all technological processes are always significant. In the processes of arc welding and surfacing, energy consumption is one of the main indicators of the profitability of using a particular implementation method, and therefore the search for reducing energy costs remains relevant. It is known that the pulsed feed of the electrode wire in mechanized and automatic welding-surfacing processes can reduce the specific power consumption for conducting processes in comparison with traditional arc welding-surfacing methods. Purpose of the work. The purpose of the work is to analyze the energy costs when using electrode wire feed systems of welding and surfacing equipment with the development of a mathematical description that allows you to select the characteristics of the welding process and parameters of the feed pulses to optimize the specified energy costs and the possibility of their reduction. Research methods. The main method for studying energy processes is to obtain a mathematical model that describes the levels of energy consumption when using the most characteristic forms of impulse actions in surfacing welding with a controlled pulse feed of an electrode wire. Obtaining and analysis of the obtained dependencies, including comparison with the results obtained with traditional methods of conducting arc processes, as well as the results of experimental studies using specially designed devices. Results. Mathematical models of the processes of electric arc welding with a pulse feed of an electrode wire have been obtained, in which the energy features of welding and surfacing with various, most well-known pulse shapes, time constants of welding current sources, as well as a number of other significant characteristics of the arc process are distinguished. A comparative assessment of the required power consumption for equipment with pulsed and conventional electrode wire feed systems with experimental natural fixation of the results has been made. Scientific novelty. For the first time, adequate mathematical models have been obtained that describe the dependences of energy costs in welding and surfacing with pulse algorithms for feeding an electrode wire with almost all the operating characteristics of the arc process with a special emphasis on the shape and parameters of the pulse movement of the wire. A comparative assessment of energy costs, including the costs of a conventional process, is made. Practical value. The main practical conclusions (results) of the work are analytical descriptions of electricity consumption for welding-surfacing when using a pulse feed with various pulse characteristics, taking into account a number of other characteristics, including the physicochemical characteristics of the process and materials, as well as the technical characteristics of the source. The results obtained can be used when choosing and setting the parameters of impulse action to ensure optimal energy consumption.

Kinetics and removal pathwayof basic fuchsin by electrochemical oxidization

Abstract In present paper Basic Fuchsin was decomposed by electrochemical oxidization (EO).Kinetic parameters, dominant reaction routes, intermediates, energy cost evaluation and biotoxicity were also discussed systematically.Decolorization of Basic Fuchsin by potentiostatic experiments was fitted to be pseudo first-order reaction. The apparent rate constants were obtained as 7.33 × 10−4, 1.46 × 10−3, 1.71 × 10−3, 2.29 × 10−3 and 3.9 × 10−3 min−1 at temperatures of 293, 303, 313, 323 and 333 K, respectively. The apparent activation energy was calculated as 30.82 kJ·mol−1 at 1.2 Vvs.SCE. The diffusion coefficient D, electron transfer number and the transfer coefficientβwere 1.66 × 10−7 cm2/s, 1 and 0.775, respectively. The current-time integral curve manifested that the total electric quantity consumed was only 3.37C compared with theoretical full oxidation electrical charge quantity 140C in anode cell. Sediments of Basic Fuchsin largely decreased the electrical energy consumption. According to Xevo-G2-Qtof-MS, the main reaction process included electropolymerization reaction,oxidation cleavage reaction, free radical reaction and open ring reaction. OH and Cl were the main free radicals. They attacked Basic Fuchsin to form di-polymer or tri-polymer precipitates. Furthermore, the acute toxicity assessment showed that this degradation process could greatly reduce the eco-toxicity of Basic Fuchsin.

Degradation of anticancer drug capecitabine in aquatic media by three advanced oxidation processes: Mechanisms, toxicity changes and energy cost evaluation

Degradation of capecitabine was conducted using electrochemical oxidation, UV/H2O2 oxidation, and ozonation. Capecitabine was efficiently degraded by three advanced oxidation processes. The degradation rates of capecitabine achieved approximately 99.0% after 4 min of ozonation, 12 min of electrochemical oxidation, and 30 min of UV/H2O2 oxidation. The mineralization rate obtained was merely 10.3% for ozonation at 60 min, compared to 91.7% for electrochemical oxidation and 55.3% for UV/H2O2 oxidation. Capecitabine was degraded by oxidation, defluorination, hydrogenation, hydrolysis, ring and bond cleavage. Thus, multiple intermediates were generated during the degradation process, such as F-, formic acid, acetic acid, oxalic acid, and other intermediate metabolites with lager molecules. A total of eighteen metabolites, except for F- and carboxylic acids, were identified by QTOF-HRMS, where six of them could only be detected by the electrochemical oxidation process, two of them were by the UV/H2O2 oxidation process, and one of them by the ozonation process. Electrochemical oxidation was the only process that could achieve over 90% removal of cytotoxicity and genotoxicity, and the metabolites were non-genotoxic after 60 min of reaction. The number of live cells decreased with the increasing reaction time in ozonation, demonstrating the higher toxicity of the intermediates in ozonation. Energy cost evaluation results suggested that the lowest energy consumption was achieved at 1.8 kWh/m3 for 90% of capecitabine degradation with the O3 dosage of 250 mg/h. Energy consumptions for 50% removal of cytotoxicity were 21.3 and 6.3 kWh/m3 in electrochemical oxidation and UV/H2O2 oxidation, respectively. The highest energy cost for 50% of genotoxicity removal was observed in electrochemical oxidation, while ozonation was identified as the most cost-effective process.

Cost evaluation for a two-staged reverse osmosis and pressure retarded osmosis desalination process

This research provides an analysis of energy efficiency and cost evaluation for three types of two-staged reverse osmosis (RO) and hollow fibre pressure retarded osmosis (PRO) hybrid process; one without direct feed flow (Hybrid A), one with direct feed flow (Hybrid B) and one with direct feed flow and a turbine (Hybrid C). Firstly, models are built from first principles assuming multi-staged RO-PX (pressure exchanger) has equal stage recovery considering the effect of booster pumps and pressure drop in the RO system. Then, all simulations are implemented by MATLAB 2018b, and energy efficiencies are assessed based on the normalised specific energy consumption, NSEC. All hybrid processes are found to have higher total water prices (TWP) when the electricity price is 0.10 US$/kWh; however, they show certain advantages under different electricity prices when wastewater pretreatment and delivery of wastewater are neglected. Hybrid C is especially attractive even in countries where water prices are low, and electricity prices are high due to its insensitiveness to electricity prices. The requirement of wastewater pretreatment and wastewater pump and the further development of PRO membranes are the keys to practical operations.

Micropollutant elimination by O3, UV and plasma-based AOPs: An evaluation of treatment and energy costs

Over the last years, there has been a growing interest in the use of Advanced Oxidation Processes (AOPs) for the elimination of micropollutants. This work attempts to compare the efficiency of conventional UV, O3 and H2O2 based AOPs with a relatively new AOP based on plasma-ozonation, in terms of removal and energy efficiency. The experimental study is performed in a synthetic water matrix spiked with four different micropollutants: atrazine (ATZ), alachlor (ALA), bisphenol A (BPA) and 1,7-α-ethinylestradiol (EE2). For the different processes examined in this study, O3 – based AOPs are more effective compared to UV based techniques in terms of energy efficiency. Although the energy efficiency of plasma-ozonation falls between the energy cost of O3 and UV-based AOPs, the removal kinetics generally proceed faster compared to other AOPs, achieving complete elimination (>99.8% removal) of the target compounds within 20 min of treatment. Moreover, the results suggest that improvement in the mass-transfer in the plasma-ozonation setup permits to further decrease the energy cost of this process up to electrical energy per order (EE/O) values between 2.54 and 0.124 kWh m−³, which is already closer to the energy efficiency of ozonation (EE/O = 0.73–0.084 kWh m−³).

Energy-Efficient Clusters for Object Tracking Networks

Smart cities have hundreds of thousands of devices for tracking data on crime, the environment, and traffic (such as data collected at crossroads and on streets). This results in higher energy usage, as they are recording information persistently and simultaneously. Moreover, a single object tracking device, on a corner at an intersection for example has a limited scope of view, so more object tracking devices are added to broaden the view. As an increasing number of object tracking devices are constructed on streets, their efficient energy consumption becomes a significant issue. This work is concerned with decreasing the energy required to power these systems, and proposes energy-efficient clusters (EECs) of object tracking systems to achieve energy savings. First, we analyze a current object tracking system to establish an equivalent model. Second, we arrange the object tracking system in a cluster structure, which facilitates the evaluation of energy costs. Third, the energy consumption is assessed as either dynamic or static, which is a more accurate system for determining energy consumption. Fourth, we analyze all possible scenarios of the object’s location and the resulting energy consumption, and derive a number of formulas for the fast computation of energy consumption. Finally, the simulation results are reported. These results show the proposed EEC is an effective way to save energy, compared with the energy consumption benchmarks of current technology.

Optimization of RDM-UF for alfalfa wastewater treatment using RSM.

Rotating disk membrane (RDM) module with ultrafiltration (UF) was an effective alternative method to treat alfalfa wastewater and realize protein recovery and agricultural irrigation water production. A scientific investigation has been conducted to comprehend the effect of operation conditions (feed flow rate, shear rate, transmembrane pressure (TMP), and temperature) on alfalfa wastewater treatment with RDM-UF by central composite response surface methodology (CCRSM). First, the filtration behaviors of three types of UF membranes (PES20, UH030P, and PES50) were studied to select the optimized membrane (UH030P). Then, the effects and interactions of four operation conditions were studied and fitting models were established, while data on pollution reduction and protein recovery, membrane fouling behavior, and energy cost evaluation were collected. Furthermore, the optimized operation conditions calculated by CCRSM were Q=60Lh-1, γ=220×103s-1, TMP=5.61bar, and T=25°C. In addition, the concentration test was conducted with these parameters. This work may contribute to the potential application of RDM for membrane wastewater treatment. Graphical abstract Schematic diagram of UF process for alfalfa wastewater treatment and resource recovery.

Performance and energy cost evaluation of an integrated NH3-based CO2 capture-capacitive deionization process

A capacitive deionization (CDI) device was proposed for NH3-based CO2 absorption-desorption process, to reduce the stripper regeneration energy. A rate-based model, RateFrac, was developed for the absorber, along with an equilibrium-based model, RadFrac, for the stripper. The model was verified, and the results have shown good agreement with experimental data. The CO2 capture process, which is integrated with CDI, was simulated and compared with a non-CDI CO2 capture process based on regeneration energy. Operating parameters such as flow rate, lean CO2 loading, and ammonia concentration in the lean solvent were used to analyze the integrated model. Stripper regeneration energy can be reduced by as much as 37.5% by using the CDI setup. Moreover, energy cost estimation was performed using two heat sources (natural gas and coal). CDI saved a maximum of 31% of the energy costs for a natural gas–fired boiler and 12.3% of the energy costs for a coal-based boiler.

A Computational Tool for Comparative Energy Cost Analysis of Multiple-Crop Production Systems

Various crops can be considered as potential bioenergy and biofuel production feedstocks. The selection of the crops to be cultivated for that purpose is based on several factors. For an objective comparison between different crops, a common framework is required to assess their economic or energetic performance. In this paper, a computational tool for the energy cost evaluation of multiple-crop production systems is presented. All the in-field and transport operations are considered, providing a detailed analysis of the energy requirements of the components that contribute to the overall energy consumption. A demonstration scenario is also described. The scenario is based on three selected energy crops, namely Miscanthus, Arundo donax and Switchgrass. The tool can be used as a decision support system for the evaluation of different agronomical practices (such as fertilization and agrochemicals application), machinery systems, and management practices that can be applied in each one of the individual crops within the production system.

无线传感网多参数路由均衡机制研究

无线传感器网络能够实时监测覆盖区域内各种物理量的动态变化情况，在军事、环境监测等领域获得了广泛应用。由于无线链路的时变特性、网络结构的动态变化等因素，使得无线传感网的路由设计一直是研究的热点和难点。当前的路由算法主要是基于单目标的性能优化，算法性能随着应用的差异产生很大的不同。针对多参数系统在实际情况中的应用需求，以传包率、时延、抖动、吞吐量、能耗等为衡量指标，结合模糊理论，提出一种基于GRC的多参数均衡的路由机制。实验结果表明，基于GRC的方法可以有效选择最优化算法，依据评估结果动态选择最优化算法，在中等流量情况下，系统能够获得32%的整体性能增益。方法实现了算法性能的定量分析、性能排序，结果可以为无线传感网性能评估提供一定的理论依据，也可以为算法优化提供方向。 Wireless Sensor Network (WSN) is capable of measuring parameters within its coverage area. It gains wide applications in the areas such as military fields, environment monitoring for the sake of safety, efficiency as well as on-time nature. Nevertheless, factors such as time dependent nature of wireless links, dynamic topology make it different for proliferation of wireless sensor network. Routing is a key but the most difficult part in the design as well as optimization of wireless sensor networks. Specific speaking, routing in WSN is designed to improve one or at most two performance metrics, leading to its performance deterioration when the application fields change. An adaptive routing mechanism based on GRC, with five metrics considered, is proposed, targeting at multiple parameters such as packet delivery ratio, delay, jitter, throughput and energy cost evaluation, in this paper to rank the alternative protocols and thus rank them accordingly using fuzzy logics. Competing metrics are balanced and therefore our method is able to obtain the optimal routing algorithm. Simulation results show that a 32% gain may be achieved by using the proposed method in terms of middle traffic flow. Our method is able to provide a quantitative method for performance evaluation for wireless sensor network. It also aims at providing benchmark for algorithm optimization.

Thermal load at workstations in the underground coal mining: Results of research carried out in 6 coal mines

Statistics shows that almost half of Polish extraction in underground mines takes place at workstations where temperature exceeds 28°C. The number of employees working in such conditions is gradually increasing, therefore, the problem of safety and health protection is still growing. In the present study we assessed the heat load of employees at different workstations in the mining industry, taking into account current thermal conditions and work costs. The evaluation of energy cost of work was carried out in 6 coal mines. A total of 221 miners employed at different workstations were assessed. Individual groups of miners were characterized and thermal safety of the miners was assessed relying on thermal discomfort index. The results of this study indicate considerable differences in the durations of analyzed work processes at individual workstations. The highest average energy cost was noted during the work performed in the forehead. The lowest value was found in the auxiliary staff. The calculated index of discomfort clearly indicated numerous situations in which the admissible range of thermal load exceeded the parameters of thermal load safe for human health. It should be noted that the values of average labor cost fall within the upper, albeit admissible, limits of thermal load. The results of the study indicate that in some cases work in mining is performed in conditions of thermal discomfort. Due to high variability and complexity of work conditions it becomes necessary to verify the workers' load at different workstations, which largely depends on the environmental conditions and work organization, as well as on the performance of workers themselves. Med Pr 2016;67(4):477-498.