Decrease Electricity Consumption Research Articles

Assessment of transit bus electricity consumption using a random parameters approach

The shift towards sustainable transportation emphasizes the crucial role of electric transit buses in promoting cleaner and more efficient public transit systems. This study conducts an explanatory analysis of electric bus electricity consumption, with a focus on the impacts of detailed driver behavior and vehicle operation. A random parameters ordered probit model is applied to an electric bus dataset collected from Guangzhou, China. Findings indicate that some factors exhibit consistent impacts on electricity consumption across bus fleets, such as the acceleration rate at bus stops and the number of stops induced by traffic conditions. However, variability exists within the bus fleet regarding the effects of other factors, such as the average speed and handbrake usage. These results underscore the need for targeted strategies, such as maintenance, route optimization, driver training, and policy adjustments in bus operations, to decrease electricity consumption and improve the efficiency of public transit systems.

APPLICATION OF THE PRINCIPLES OF GREEN CHEMISTRY IN THE PLASTIC RECYCLING INDUSTRY: A CASE STUDY

The subject of this research wasto verify the feasibility of implementing green chemistry principles within the business company „Omorika Reciklaža“ Ltd. situated in Johovac near Doboj, Bosnia and Herzegovina. The objective of this study wasto conduct a detailed assessment of the company's facilities and operations, using environmental audits, to identify technological processes (production lines), energy and waste flows, capacities, product range, and other pertinent factors crucial for theapplication of green chemistry principles. Special emphasis was placed on analyzing each substance that constitutes a raw material, whether used individually or as part of mixtures.The assessment of safety data sheets involvedutilizing the CAS registration numbers of substances from the Chemical Abstracts Service, cross-referenced with the ECHA database (European Chemicals Agency). The outcomes, attained through an exhaustive analysis of each substance, were presented as a "chemical inspection" of the company. Through the analysis of all substances and mixtures in the technological process (chemical inspection), as well as the capacity of production flows, energy and resource flows, wastewater, and waste, the potential for enhancing the technological process wasidentified. This involvedreducing dust levels in the workspace, decreasing electricity consumption (utilizing renewable sources), and substituting particularly hazardous chemicals used in the technological process. KEYWORDS:green chemistry; chemical safety; SVHC;environmentalaudit

Biphasic pretreatment excels over conventional sulfuric acid in pinewood biorefinery: An environmental analysis

This study assesses the environmental impact of pine chip-based biorefinery processes, focusing on bioethanol, xylonic acid, and lignin production. A cradle-to-gate Life Cycle Assessment (LCA) is employed, comparing a novel biphasic pretreatment method (p-toluenesulfonic acid (TsOH)/pentanol, Sc-1) with conventional sulfuric acid pretreatment (H2SO4, Sc-2). The analysis spans biomass handling, pretreatment, enzymatic hydrolysis, yeast fermentation, and distillation. Sc-1 yielded an environmental impact of 1.45E+01 kPt, predominantly affecting human health (96.55%), followed by ecosystems (3.07%) and resources (0.38%). Bioethanol, xylonic acid, and lignin contributed 32.61%, 29.28%, and 38.11% to the total environmental burdens, respectively. Sc-2 resulted in an environmental burden of 1.64E+01 kPt, with a primary impact on human health (96.56%) and smaller roles for ecosystems (3.07%) and resources (0.38%). Bioethanol, xylonic acid, and lignin contributed differently at 22.59%, 12.5%, and 64.91%, respectively. Electricity generation was predominant in both scenarios, accounting for 99.05% of the environmental impact, primarily driven by its extensive usage in biomass handling and pretreatment processes. Sc-1 demonstrated a 13.05% lower environmental impact than Sc-2 due to decreased electricity consumption and increased bioethanol and xylonic acid outputs. This study highlights the pivotal role of pretreatment methods in wood-based biorefineries and underscores the urgency of sustainable alternatives like TsOH/pentanol. Additionally, adopting greener electricity generation, advanced technologies, and process optimization are crucial for reducing the environmental footprint of waste-based biorefineries while preserving valuable bioproduct production.

Assessing different glazing types for energy savings and CO2 reduction in a tropical climate: A comparative study

Energy efficiency in buildings and the mitigation of CO2 are key factors in the advancement of contemporary architecture, which includes aesthetic elements such as skylights, façades, and windows. Therefore, in this work the impact of different glazing types on energy savings and CO2 reduction was presented. A comparative analysis was conducted taking into account the climate-oriented approach in a specific climate context, Aw Köppen Climate Classification. Based on numerical results of the conjugate heat transfer in a two-dimensional geometry in a transient state, first, the glazing thermal performance under extreme weather conditions was evaluated, subsequently, an annual thermal evaluation was conducted. Triple glazing was highlighted as an effective option as it reduced heat loss by 56.5 % on the coldest day and reduced heat gain by 31.0 % on the warmest day in Mérida, Yucatán. Triple glazing also showed efficiency in reducing the total heat flux per unit area by 32.7 % under extreme temperature and solar radiation conditions, coldest day – south orientation and warmest day – west orientation. While glazing orientation showed a significant role in overheating, triple glazing decreased electricity consumption and CO2 emissions by 29 % per year, making it a leading choice for sustainable architecture.

The plant growth, water and electricity consumption, and nutrients uptake are influenced by different light spectra and nutrition of lettuce

The aim of this study was to investigate the effect of different replacement methods of nutrient solution (complete replacement, electrical conductivity (EC)- based replacement, and replacing based on the plant needs) and different LED light spectra (monochromic white, red, blue, and a combination of red/blue) on the uptake of mineral nutrients, water and electricity consumption and biomass production of two varieties of lettuce (Lollo Rossa and Lollo Bionda; Lactuca sativa var. crispa) in the hydroponic systems. The results showed that replacement methods based on the plant needs and based on EC increased shoot fresh mass and yield index in the NFT system. Also, results showed that the combination of red/blue light increased shoot fresh mass and yield index in the NFT system and in the plant factory under treatment by replacement method based on plant needs. Increasing the concentrations of N, K, and Zn and loss of Fe in nutrient solution were observed in all three replacement methods of nutrient solution in the NFT system. Water consumption was decreased under plant nutrition based on plant needs and based on EC. In the plant factory, the application of LED light spectrum also decreased electricity consumption and cost against fluorescent lamps. In general, it is concluded that nutrient solution replacement based on the plant needs and based on EC and the use of different LED light spectra (especially the combination of red and blue light) can be used to reduce the consumption of water and nutrients in the hydroponic cultivation of lettuce.

Dynamic modeling and experimental validation of household refrigerators/freezers equipped with phase change materials towards improved energy efficiency

Phase change materials (PCMs) have significantly impacted domestic refrigeration systems' energy efficiency. By reducing the compressor On/Off frequency and decreasing electricity consumption, utilizing PCMs can substantially improve overall energy performance. This research aimed to evaluate a household freezer equipped with PCM for its thermal behavior and energy consumption. To achieve this, a dynamic model for household refrigerators and freezers with PCMs was developed, incorporating thermodynamics, heat transfers, mass and heat balances, and a control algorithm that specifically determined the PCM temperature and melted mass fraction over time. The proposed model introduces a new approach to the refrigeration cycle simulation by utilizing pressure-based hydraulic calculations, departing from the conventional method of relying only on thermodynamics. Furthermore, the model incorporates a dynamic PCM component into the refrigerator model. To validate the model, the simulator was compared to experimental data with and without PCM in the freezer cabinet; the results showed relative errors of 5.5% and 5.1% in power consumption, respectively. The developed model is fast enough to be used as an internal model for dynamic simulation and analysis, optimization, and control problems.

CONTROL SYSTEM OF PARAMETERS OF ELECTRICAL CURING OF CAST-IN-SITU REINFORCED CONCRETE STRUCTURES

At the moment in house-building industry cases of increase of efficiency of cast-in-situ concrete structures electrical curing are insufficiently studied. Development and implementation of control systems of parameters of electrical curing can be solve of current concerns. Development sequence of this control system included: collection of initial data; development of virtual model of considered structures, using ELCUT; analysis of rate of simulation parameters, depend on ambient conditions; fixation of values of simulation parameters; development of mathematical model of correlation between transformer voltage and temperatures of concrete, ambient air and time of electrical curing; development and description of circuit diagram of proposed control system.
 The control system, developed by the authors, can be the basis for creation of automated complex of electrical curing of cast-in-situ reinforced concrete structures. Application of this system will significantly allow to decrease electricity consumption and labor costs, connected with electrical curing of structures.

Control mechanism of electricity consumption in a transport company

To reduce electricity consumption in hierarchical management of fabrication, it is necessary to take into account the activity of managers associated with the presence of their own targets. A three-level model of managing electricity consumption in production is considered. At its top level is the superior who evaluates the executive who is at the middle level. At the bottom of the system is the director of fabrication. The superior must to manage the consumption of the executive in such a way as to save electricity. But the executive knows own electricity-saving opportunities better than the superior. In turn, the director knows his own electricity-saving capabilities better than the executive. So, both the executive and the director can manipulate their electricity consumption to gain more incentives. To avoid this, a control system for electricity consumption management in fabrication is proposed. This system includes procedure for machine learning of the superior and procedure for grading of the executive. Sufficient conditions of the optimality of this system are found, in which random opportunities of decreasing electricity consumption are used. With such a system, the executive is interested in minimizing electricity consumption. The Theorem is proved that for this it is sufficient to use linear procedures of adaptive standardization and stimulation of the director. The proposed approach to control of electricity consumption is illustrated by the example of railcars repairing in the Russian Railways company.

Life Cycle Energy Consumption and Greenhouse Gas Emissions Analysis of Primary and Recycled Aluminum in China

Aluminum production is a major energy consumer and important source of greenhouse gas (GHG) emissions globally. Estimation of the energy consumption and GHG emissions caused by aluminum production in China has attracted widespread attention because China produces more than half of the global aluminum. This paper conducted life cycle (LC) energy consumption and GHG emissions analysis of primary and recycled aluminum in China for the year 2020, considering the provincial differences on both the scale of self-generated electricity consumed in primary aluminum production and the generation source of grid electricity. Potentials for energy saving and GHG emissions reductions were also investigated. The results indicate that there are 157,207 MJ of primary fossil energy (PE) consumption and 15,947 kg CO2-eq of GHG emissions per ton of primary aluminum ingot production in China, with the LC GHG emissions as high as 1.5–3.5 times that of developed economies. The LC PE consumption and GHG emissions of recycled aluminum are very low, only 7.5% and 5.3% that of primary aluminum, respectively. Provincial-level results indicate that the LC PE and GHG emissions intensities of primary aluminum in the main production areas are generally higher while those of recycled aluminum are lower in the main production areas. LC PE consumption and GHG emissions can be significantly reduced by decreasing electricity consumption, self-generated electricity management, low-carbon grid electricity development, and industrial relocation. Based on this study, policy suggestions for China’s aluminum industry are proposed. Recycled aluminum industry development, restriction of self-generated electricity, low-carbon electricity utilization, and industrial relocation should be promoted as they are highly helpful for reducing the LC PE consumption and GHG emissions of the aluminum industry. In addition, it is recommended that the central government considers the differences among provinces when designing and implementing policies.

Techno-Economic Analysis as a Driver for Optimisation of Cellobiose Lipid Fermentation and Purification.

Cellobiose lipids (CL) are glycolipids synthesized by Ustilaginaceae species with potential application as detergents or in cosmetics. This study identified process optimisation potential for CL fermentation based on process modelling and techno-economic analysis. Using a stoichiometric equation based on laboratory data, we calculated the maximum possible CL yield YP/S of 0.45 gCL·gglucose −1 at the biomass yield of 0.10 gBiomass·gglucose −1 with an Ustilago maydis strain. Due to substrate inhibition that may occur at high glucose concentrations, a fed-batch process to increase biomass and CL concentrations was considered in our model. Simulation of different process scenarios showed that the choice of aeration units with high oxygen transfer rates and adaptation of power input to oxygen uptake can significantly decrease electricity consumption. We further assessed scenarios with different fermentation media and CL purification methods, suggesting additional process optimisation potential. Here the omission of vitamins from the fermentation medium proved to be a possible mean to enhance process economy, without compromising CL productivity.

Temperature regulation of a commercial space in building system optimized by genetic algorithm

ABSTRACT Heating systems are becoming an increasingly important research subject in the building field because, they are the main element used to improve occupants comfort. This work is being done to improve building comfort while also reducing energy consumption by employing a new proposed optimized neural network control approach for a commercial space's temperature regulation in building system optimized by genetic algorithm. The key control goal is to decrease electricity consumption while maintaining the occupants’ optimum thermal comfort. This approach’s originality may allow it to work in the face of disruptions such as occupancy profiles, electrical devices, inside temperature, outside temperature, and weather information. A combination of genetic algorithms and artificial neural networks is presented to benefit from the advantages of each approach to create a quick and strong controller, especially when the system lacks a mathematical and physical model. The suggested technique is effectively shown using an example of temperature regulation in a commercial space, under Matlab/Simulink environment using the SIMBAD toolbox (SIMulator of Buildings and Devices). In many cases, the effectiveness of the suggested control has been demonstrated using good performance indices. The simulation results demonstrated that a high level of temperature regulation is generated in the commercial space with an electrical radiator of 1000 W, , and a high degree of comfort. As a result, the validity and efficacy of this control technique have been demonstrated.

Industrial Electrification and Efficiency: Decomposition Evidence from the Korean Industrial Sector

For this study, we conducted a decomposition analysis of industrial electricity consumption based on the logarithmic mean Divisia index approach. An empirical dataset consisting of 11 industrial sectors in Korea from 2000 to 2018 was used. The three-factor decomposition equation was extended to include four factors by decomposing the energy intensity effect into electrification and electricity consumption efficiency effects. The empirical results are summarized as follows: The increase in electricity consumption in the Korean industrial sector from 2000 to 2018 is mostly caused by the production effect. While the structure effect decreases electricity consumption, the intensity effect increases it. The key findings indicate that the hidden electrification effect can be confusing to researchers with regard to the intensity effect. The empirical evidence suggests that the intensity effect has a positive effect on electricity consumption induced by the electrification effect, although the efficiency effect continuously decreased electricity consumption. The decomposition results of some sectors show that electrification, rather than the production effect, contributed the most to the increase in electricity consumption. This implies that while replacing fuel with electricity has been successfully achieved in several sectors, there are still challenges regarding increasing energy efficiency and expanding clean electricity generation.

Microwave Torrefaction of Oat Hull: Effect of Temperature and Residence Time

Microwave torrefaction of oat hull was conducted to enhance its physicochemical properties. A bench-top reactor with an internal stirrer was used for oat hull pretreatment at temperatures of 225 °C, 255 °C, and 285 °C, and residence times of 3, 6, and 9 min, respectively. Results showed that a high temperature level at 3 min residence time or severe torrefaction increased calorific values by up to 35% of its original value, while decreasing mass yield down to 60.77%. Severe torrefaction further decreased moisture absorption, moisture content, and grinding energy consumption but decreased energy yield and bulk density. Residence time had no significant effect on biomass physicochemical changes; however, production cost may be significantly increased by longer residence times. It was also concluded that increased microwave power levels from 400 to 650 W decreased energy consumption by shortening processing times, resulting in a positive economic impact of the process. Moderate and severe torrefaction significantly enhanced biomass fuel properties, and short residence times are recommended in order to decrease electricity consumption. In addition, microwave pretreatment enhances biomass in a similar way to conventional torrefaction, but at a faster processing time. Moreover, the liquid fraction as a by-product may represent a valuable product for the food industry.

Renewable Green Energy Resources for Next-Generation Smart Cities Using Big Data Analytics

Energy is now seen as a significant resource that develops abundant on the world economy, with short supply and development. A study found that renewable energy systems are needed to prevent shortages. Hence, all the focus in this study to decrease electricity consumption and reduce the overall completion times for a regular console in green technology networks was an efficient and scalable production genomic solution. A Renewable green energy resources smart city (RGER-SC) framework is proposed that used a multi-target evolutionary algorithm was hybridized to be effective and calculated arithmetically in this study. This work deals with fostering renewable energy incorporation by adjusting federal charges to increase the energy accounting practitioners. Besides, this report analyses the timely generation of delay-tolerant demands and the maintenance of district heating at network infrastructure. In comparison, capacity differentials between consumers and information centres are considered and evaluated using the Renewable green energy resources smart city (RGER-SC) framework for energy conservation and controlled task management at an industrial level.

How did the German and other European electricity systems react to the COVID-19 pandemic?

The first wave of the COVID-19 pandemic led to decreases in electricity demand and a rising share of Renewable Energy Sources in various countries. In Germany, the average proportion of net electricity generation via Renewable Energy Sources rose above 55% in the first half of 2020, as compared to 47% for the same period in 2019. Given these altered circumstances, in this paper we analyze how the German and other European electricity systems behaved during the COVID-19 pandemic. We use data visualization and descriptive statistics to evaluate common figures for electricity systems and markets, comparing developments during the COVID-19 pandemic with those of previous years. Our evaluation reveals noticeable changes in electricity consumption, generation, prices, and imports/exports. However, concerning grid stability and ancillary services, we do not observe any irregularities. Discussing the role of various flexibility options during the COVID-19 pandemic, a relatively higher grid capacity resulting from a decreased electricity consumption, in particular, may have contributed to grid stability.

Real-time feedback on electricity consumption: evidence from a field experiment in Italy

Smart meters can help citizens in optimizing energy consumption patterns. However, mixed evidence exists on their effectiveness in reducing energy demand and especially in levelling off the daily peaks of electricity load curves. Here, we evaluate the impact of providing real-time feedback on electricity consumption from a field trial in Italy. We combine standard regressions with machine learning techniques on high-frequency data to quantify impacts on both levels and patterns of electricity use. Results indicate that real-time feedback can moderately decrease electricity consumption (between 0.5 and 1.9% depending on model specification), but that it does not promote load shifting throughout the day by itself. Machine learning reveals evidence of significant household heterogeneity in the behavioral response.

Beyond building certification: The impact of environmental interventions on commercial real estate operations

Abstract We extend the commonly-studied definition of investment in sustainable and energy efficient real estate beyond environmental building certification to include three additional types of environmentally-focused building interventions: environmentally-focused capital expenditure (capex); monitoring; and, tenant engagement. Appealing to behavioral economics and finance theory, we test for a connection between changes in tenant and property management behavior and electricity consumption. Through a partnership with a global institutional investment manager, this study examines ten years of asset-level operating statement and electricity consumption data in Canadian and U.S. office buildings, measuring both the initial impact of such interventions as well as any adjustments observed over time. Analysis of the proprietary intervention data allows us to better understand the impact of varied environmental interventions on the electricity consumption of commercial real estate. We find that all four intervention categories, including building certification, are associated with decreased electricity consumption, with tenant engagement providing an immediate decrease that is maintained over time. Environmentally-focused capex is also associated with decreased electricity consumption in both Canada and the U.S. Taken together the results indicate that utility consumption and its associated costs are only minimized when multiple environmental interventions are implemented.

Legislative support for improving sustainable and smart electricity consumption in polish residential sector

Reducing energy consumption is a way to make the energy sector less invasive for the natural environment. Energy policy is essential to motivate consumers to decrease electricity consumption and should take into account the specificity of each sector (industry, households, transport). The energy policy of the member states of the European Union should consider the factors of increased demand for electricity and support solutions such as smart metering and prosumer energy.This paper provides an overview of the pro-efficiency policy of households in Poland, affecting the residential sector, and assesses the regulations implemented so far. The evaluation of the policy uses an econometric approach (congruent modelling). The impact of energy policy was determined by giving weights to individual regulations taking into account their variability in time.The created models showed a significant impact of the introduced regulations on the reduction of energy consumption and confirmed their changeable influence over time. Their time-limited impact on reducing energy consumption forces taking further actions motivating consumers to electricity saving. The review of Polish energy regulations revealed a lack of sufficient provision in the field of developing smart technology limited use of energy policy tools such as informative billing and information campaigns.

Estimation of residential electricity demand in Hong Kong under electricity charge subsidies

Over the past decade, the Hong Kong (HK) government provided electricity charges subsidies for residential accounts to alleviate the burden of inflation and, later, the burden of economic downturn. In this study, we estimate an econometric model of residential electricity demand and test the existence of a stable long-run relationship for the period 1980–2016, while accounting for the relief measures set out by the HK government since 2008. Empirical results suggest that there exists a long-run relationship among residential electricity consumption, electricity price, income per capita, and weather variables (temperature or cooling degree days). In the absence of electricity charge subsidies, the demand is found to be both price and income inelastic. On the other hand, HK's residential electricity consumers are unresponsive to price and income changes when electricity subsidies are in place. Following its new carbon reduction plan, HK is gradually phasing out coal for electricity generation to replace it mainly with natural gas. Our results suggest that new residential electricity charge subsidies can lessen the effectiveness of6 climate policies aimed at reducing electricity consumption through increases in the electricity price. • Econometric estimation of residential electricity demand • Inelastic price and income elasticities; smaller short-run (absolute) elasticities • Perfectly inelastic demand when electricity charge relief measures are in place • Environmental policies to decrease electricity consumption and carbon emissions through higher tariffs can have minimal impact

Assessing the effect of non-financial information intervention on promoting group-level energy savings

Increasing attention has been paid to information intervention in stimulating household energy conservation. However, for group-level energy users who have no financial motivation to save energy, little is known about which types of non-financial information intervention (NFII) strategies can effectively motivate group-level energy conservation. A 14-week controlled field experiment was conducted to test the energy-saving effect of 4 types of NFII strategies. The results show that compared with the control group, the experimental group receiving normative information and group-contrast feedback decreased electricity consumption by 24.23%. Followed by the group receiving normative information and self-contrast feedback and the group receiving environmental education information and group-contrast feedback. The group receiving environmental education information and self-contrast feedback showed no significant energy savings. Analysis of variance further showed that normative information had a better energy-saving effect than environmental education information, and the energy-saving effects produced by group-contrast feedback were better than that of self-contrast feedback. These conclusions provide insights and recommendations on how to use NFII to motivate group-level energy conservation.