Case Study Of Energy Consumption Research Articles

Fluid flow and heat transfer of the two-phase solid/liquid mixture at the equilibration phase structure via MD method: Atomic value effects in a case study of energy consumption and absorbed energy

This computational work was conducted to describe the atomic behavior of Ar atoms in the presence of Cu, Fe, and Cu/Fe nanoparticles via the molecular dynamics (MD) approach. The results of our simulations on the atomic behavior of various structures were reported by calculating physical quantities, such as temperature, total energy, aggregation time, and density/velocity/temperature profile. Computational results revealed that the total energy, the solar energy for instance, converged to a negative value after t = 5 ns. This calculation estimates the atomic stability of nanostructures. Numerically, by adding Cu/Fe nanoparticles to Ar base fluid, the aggregation time in atomic structures increased to 4.59 ns; this atomic improvement could be used for heat/mass transfer aims.

Impact of the new Saudi energy conservation code on Saudi Arabia residential buildings

ABSTRACT Air conditioning systems are the most viable source to avoid heat waves. Unfortunately, this puts a massive burden on the total electrical load. To deal with this critical issue, the Saudi Building Code National Committee has initiated the Saudi energy conservation code (SBC-602). This paper investigated the role of SBC-602 on the reduction of energy consumption in residential buildings. Furthermore, it also proposes the most effective building element to be insulated. A case study of energy consumption was modelled using SketchUp and analysed using OpenStudio Software. Inconsequence, three scenarios of U-values as an input in this work were suggested which are; building without thermal insulation, building with thermal insulation using Saudi electricity company (SEC) requirement, and using SBC-602 requirement. The study was conducted in three different cities Riyadh, Hail, and Abha, representing three climate zones in Saudi Arabia. Design of experiment (DOE) method was utilised to analyse the significant effects of the input factors. The result indicates that the decrease of the walls U-value is the most effective way to reduce the total electrical energy consumption. Moreover, decreasing roof U-value and increasing setpoint temperature were the following effective factor.

Evaluation of School Building Energy Performance and Classroom Indoor Environment

Existing building stock represents potential for energy saving renovations. Energy savings and indoor climate comfort are key demands for sustainable building refurbishment. Especially in schools, indoor comfort is an extremely important issue. A case study of energy consumption in selected school buildings in temperate climatic conditions of Central Europe region was performed. The studied buildings are representatives of various school premises constructed throughout the last century. The evaluation was based on data analysis of energy audits. The goal was aimed at assessment of the school building envelopes and their influence on energy consumption. One of the studied schools was selected for detailed evaluation. The school classroom was monitored for indoor thermal and visual environments. The monitoring was performed to compare the current state and renovation scenarios. Results of the evaluation show that the school buildings are highly inefficient even if renovated. Indoor climate in classrooms is largely influenced by windows. Solar gains affect interior thermal stability and daylighting. Thermal insulation quality of building envelopes and efficient solar shading systems appear to be fundamental tasks of school renovation strategies.

Extended Yearly LMDI Approaches: A Case Study of Energy Consumption

Although the logarithmic mean Divisia index (LMDI) approach has been widely used in the field of energy and environmental research, it has a shortcoming. Since the LMDI approach only focuses on the base year and reporting year, in situations in which the research period is long, the annual changes during the research period may be difficult to capture. In particular, if there were huge fluctuations in the indicators (such as the energy consumption and carbon emissions) or their drivers during the middle of a research period, a substantial amount of information about the fluctuations will be ignored. Therefore, we propose four extended yearly LMDI approaches, including pure LMDI, weighted LMDI, comprehensive LMDI, and scenario LMDI approaches to better capture fluctuations and compensate for the original LMDI approach’s shortcomings. Additionally, we found that there are mathematical relationships among the four extended LMDI approaches. We further compare these four approaches’ advantages, disadvantages, and applicable situations and analyze a case study on China’s energy consumption based on the four proposed approaches.

A two-tiered attribution structural decomposition analysis to reveal drivers at both sub-regional and sectoral levels: A case study of energy consumption in the Jing-Jin-Ji region

Structural decomposition analysis (SDA) is a very commonly used method for exploring the driving forces of environmental pressure (EP). Enhanced with attribution analysis, SDA can further decompose the driving forces of EP into economic sectors or sub-regions and provide more detailed evidence-based policymaking. However, current studies of SDA with attribution analysis have not been sufficiently developed and are only one-tiered, i.e., they decompose the driving forces of EP into either a sub-regional or an economic sectoral level. In this study, we introduce a method of SDA with a two-tiered attribution analysis, which is capable of 1) exploring the driving force of environmental pressure at a multi-regional level and 2) further decomposing the driving forces of EP into both sub-regions and economic sectors. Based on this method, we explore the driving forces for the change of energy consumption in the Jing-Jin-Ji region during the period of 2007–2012. Results of this case study indicate that technological change, final demand structure, and final demand composition respectively contributed −129%, 12%, and −3% while affluence, production structure, total population, and population structure respectively contributed 129%, 77%, 38%, and 2% to energy consumption change in the region. In terms of sub-regional and economic sectoral level contributions, Hebei province and the chemical and smelting and rolling of metals industries were the most prominent contributors. Through this case study, we situate the strengths and limitations of the two-tiered attribution SDA method and propose key policy suggestions and future research directions.

Analysis of Causality Relationship Energy Consumption and CO2 Emissions to Economic Growth based on the LEAP Model Case Study of Energy Consumption in Indonesia 2010-2025)

This study discusses scenarios and analyzes the causal relationship of energy consumption and CO2 emissions to economic growth in Indonesia period 2010-2025. The modeling scenario is divided into 6 sections, namely BAU scenario, High scenario, Low scenario, High-Low scenario, Low-High scenario and Policy scenario. The result of scenario data is processed by performing statistical data modeling and econometric period 2010-2025. The research method used interpolation method and causality testing method. The tools are used in this research is LEAP and EViews. LEAP is used for energy modeling as well as CO2 emissions and EViews is used to manage data, analyze econometrics and statistics. The results of this study show that economic growth, energy consumption and CO2 emissions at 6 scenario indicate fluctuated competitive growth. This study proves that only 1 scenario has direct causality relationship that is only energy consumption which statistically significant influence economic growth in Policy scenario. For economic growth and CO2 emissions there are 4 scenarios that have direct causality (BAU, High, High -Low, Low-High scenario), 1 scenario has no causality relationship (Low scenario) and 1 scenario has two -way causality relationship (Policy scenario).

Database engines: Evolution of greenness

AbstractInformation technology consumes up to 10% of the world's electricity generation, contributing to CO2 emissions and high energy costs. Data centers, particularly databases, use up to 23% of this energy. Therefore, building an energy‐efficient (green) database engine could reduce energy consumption and CO2 emissions. The goal of this study is to understand the factors driving databases' energy consumption and execution time throughout their evolution. We conducted an empirical case study of energy consumption by 2 MySQL database engines, InnoDB and MyISAM, across 40 releases. We examined the relationships of 4 software metrics to energy consumption and execution time to determine which metrics reflect the greenness and performance of a database. Our analysis shows that database engines' energy consumption and execution time increase as databases evolve. Moreover, the lines of code (LOC) metric is correlated moderately to strongly with energy consumption and execution time in 88% of cases. Our findings provide insights to practitioners and researchers. Database administrators may use them to select a fast, green release of the MySQL database engine. MySQL developers may use LOC to assess products' greenness and performance. Researchers may use our findings to further develop new hypotheses or build models predicting greenness and performance of databases.

A novel performance measurement approach based on trust context using fuzzy T-norm and S-norm operators: The case study of energy consumption

In today’s economic environment, performance and efficiency assessment is essential for organizations in order to survive and raise their market share. Energy efficient consumption is a major issue in the energy planning of each country which is a big concern of managers, hence, exploitation of a strong approach for efficiency evaluation and assessment seems necessary in the energy section. In this study, a novel performance assessment model is proposed based on the concept of trust, using two popular fuzzy operators called T-norm and S-norm. The developed model is applied for a real case study of energy consumption efficiency assessment for 36 countries. An adaptive network based fuzzy inference system (ANFIS) is used to measure the efficiencies. Also, to predict efficiency rates of the future time periods, a regression model is applied as a time series model. The obtained results indicate the superiority and applicability of the proposed methodology. To the best of our knowledge, this is the first study that proposes a novel performance measurement approach based on trust context by using fuzzy T-norm and S-norm operators.

A dynamic multi-stage data envelopment analysis model with application to energy consumption in the cotton industry

Data envelopment analysis (DEA) is a non-parametric method for evaluating the relative efficiency of homogenous decision making units (DMUs) with multiple inputs and outputs. In this paper, we present a dynamic multi-stage DEA (DMS-DEA) approach to evaluate the efficiency of cotton production energy consumption. In the proposed model, the farms which consume resources (i.e., fertilizers, seeds, and pesticides) to produce cotton are assumed to be the DMUs. Inputs not consumed during a planning period are carried over to the next period in the planning horizon. Initially, a DMS-DEA model is used to determine the overall efficiency of the DMUs with dynamic inputs. Next, the efficiency score of each DMU is calculated for each time period in the planning horizon. We demonstrate the applicability of the proposed method and exhibit the efficacy of the procedures and algorithms with a real-life case study of energy consumption in the cotton industry.

Energy consumption during manufacturing of different dairy products in a commercial dairy plant: A case study

The purpose behind the energy optimization and management for dairy plant is to control the energy consumption for getting the overall maximum efficiency. For a case study of energy consumption in manufacturing of dairy products, a multi-product dairy plant was selected. The product technology and dairy operations of different dairy products were explored under batch process to identify the high energy consuming centers termed as critical control point (CCPs). Various equations for heat and mass transfer, flow rate, electrical consumption, were used to find the actual utilities consumption (steam, water, electrical energy) in dairy operations. The data of this case study was compared with previous study and found that the energy conserving status was declining. It is, therefore, essential that existing plant should be well instrumented and plant manufactures be encouraged to give more accurate service consumption figures so that energy audit can be made accurately.

Assessing the Replacement of Electrical Home Appliances for the Environment

SummaryTo evaluate whether replacing an existing product with a new, more energy‐efficient product is environmentally preferable, we used an assessment approach based on life cycle assessment. With this approach, consumers can assess various replacement products, including products of different sizes or environmental performance in addition to consideration of various conditions of product use. The approach utilizes a diagram in which replacement conditions of products are compared with iso‐environmental‐load lines to determine the appropriateness of replacement. The approach also allows the assessment of energy and resource consumption and environmental impacts not only during the use stage, but also at other product stages. Iso‐environmental‐load lines to assess delayed replacement were also examined and derived. We then applied the approach in a case study of energy consumption by replacing three types of electric home appliances in Japan: TVs, air conditioners, and refrigerators. The results of assessment showed that replacing refrigerators after 8–10 years of use was preferable even if the replacement product was larger. The appropriateness of replacing TVs and air conditioners based on energy consumption depended on the replacement product and on the duration of daily use, and in several cases, delayed replacement was preferable. Replacement of air conditioners after 8–10 years of use was not preferable if the consumer already owned the most energy‐efficient product at the time of the purchase. The necessity of accounting for a variety of available replacement products was confirmed.

Assessment of Energy Consumption in a Meat-Processing Plant—a Case Study

Meat-processing plants have their specific characteristics due to quantity of raw materials processed, production technology, degree of mechanisation of production and space utilization. These characteristics affect variability in consumption of energy carriers. This paper presents a case study of energy consumption in a small meat processing plant. It is attempting to identify and evaluate key factors which may be useful in conducting an in-depth analysis of energy consumption in the meat industry, and so this analysis may be important in selecting the best production techniques available. The results of the analysis are of critical importance for the selection of production technology selection assuming high plant efficiency.