scholarly journals Analysis of the Impact of Residential Property and Equipment on Building Energy Efficiency and Consumption—A Data Mining Approach

2020 ◽  
Vol 10 (10) ◽  
pp. 3589 ◽  
Author(s):  
Mahsa Nazeriye ◽  
Abdorrahman Haeri ◽  
Francisco Martínez-Álvarez
Keyword(s):  
Data Mining ◽  
Energy Efficiency ◽  
Energy Consumption ◽  
Large Scale ◽  
Building Energy Efficiency ◽  
Data Set ◽  
Residential Homes ◽  
Improve Energy Efficiency ◽  
Data Mining Approach ◽  
The Impact

Human living could become very difficult due to a lack of energy. The household sector plays a significant role in energy consumption. Trying to optimize and achieve efficient energy consumption can lead to large-scale energy savings. The aim of this paper is to identify the equipment and property affecting energy efficiency and consumption in residential homes. For this purpose, a hybrid data-mining approach based on K-means algorithms and decision trees is presented. To analyze the approach, data is modeled once using the approach and then without it. A data set of residential homes of England and Wales is arranged in low, medium and high consumption clusters. The C5.0 algorithm is run on each cluster to extract factors affecting energy efficiency. The comparison of the modeling results, and also their accuracy, prove that the approach employed has the ability to extract the findings with greater accuracy and detail than in other cases. The installation of boilers, using cavity walls, and installing insulation could improve energy efficiency. Old homes and the usage of economy 7 electricity have an unfavorable effect on energy efficiency, but the approach shows that each cluster behaved differently in these factors related to energy efficiency and has unique results.

scholarly journals A Study on the Impact of Nodes Density on the Energy Consumption of LoRa

2021 ◽  
Vol 15 (14) ◽  
pp. 157
Author(s):  
Aizat Faiz Ramli ◽  
Muhammad Ikram Shabry ◽  
Mohd Azlan Abu ◽  
Hafiz Basarudin
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Low Power ◽  
Large Scale ◽  
Sensor Nodes ◽  
Delivery Ratio ◽  
Area Network ◽  
Wide Area Network ◽  
Consumption Ratio ◽  
The Impact

LoRaWAN is one of the leading Low power wide area network (LPWAN) LPWAN technologies that compete for the formation of big scale Internet of Things (IoT). It uses LoRa protocol to achieve long range, low bit rate and low power communication. Large scale LoRaWAN based IoT deployments can consist of battery powered sensor nodes. Therefore, the energy consumption and efficiency of these nodes are crucial factors that can influence the lifetime of the network. However, there is no coherent experimental based research which identifies the factors that influence the LoRa energy efficiency at various nodes density. In this paper, results on measuring the packet delivery ratio, packet loss, data rate and energy consumption ratio ECR to gauge the energy efficiency of LoRa devices at various nodes density are presented. It is shown that the ECR of LoRa is inversely proportional to the nodes density and that the ECR of the network is smaller at higher traffic indicating better network energy efficiency. It is also demonstrated that at high node density, spreading factor SF of 7 and 9 can improve the energy efficiency of the network by 5 and 3 times, respectively, compare to SF 11.

scholarly journals An Advanced Decision Support Platform in Energy Management to Increase Energy Efficiency for Small and Medium Enterprises

2020 ◽  
Author(s):  
Gheorghe Grigoraș ◽  
Bogdan-Constantin Neagu
Keyword(s):  
Data Mining ◽  
Energy Efficiency ◽  
Decision Support ◽  
Energy Consumption ◽  
Production Scheduling ◽  
Small And Medium Enterprises ◽  
Small Enterprise ◽  
Data Mining Techniques ◽  
Medium Enterprises ◽  
The Impact

The paper presents a new vision on the energy consumption management in the case of the Small and Medium Enterprises (SMEs), integrated into an advanced decision support platform, with technical and economic benefits on increasing the energy efficiency, which contains modules for database management, profiling, forecasting, and production scheduling. Inside each module, Artificial Intelligence and Data Mining techniques were proposed to remove the uncertainties regarding the dynamic of technological flows. Thus, the data management module includes the Data Mining techniques, that extract the technical details on the energy consumption needed in the development of production scheduling strategies, the profiling module uses an original approach based on clustering techniques to determine the typical energy consumption profiles required in the optimal planning of the activities, the forecasting module contains a new approach based on an expert system to forecast the total energy consumption of the SMEs, and production scheduling module integrates a heuristic optimization method to obtain the optimal solutions in flattening the energy consumption profile. The testing was done for a small enterprise from Romania, belonging to the domain of trade and repair of vehicles. The obtained results highlighted the advantages of the proposed decision support platform on the decrease in the intensity of energy consumption per unit of product, reduction of the purchase costs, and modification of the impact whom the energy bills have on the operational costs.

scholarly journals The Energy Efficiency and Public Health in the ASEAN Plus Three Cooperation

2020 ◽  
Vol 57 ◽  
pp. 004695802093566
Author(s):  
Ching-Cheng Lu ◽  
Xin Wu ◽  
Xiang Chen ◽  
Chih-Yu Yang
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Dynamic Network ◽  
Well Being ◽  
Environmental Conservation ◽  
Data Envelopment ◽  
Improve Energy Efficiency ◽  
Energy Technologies ◽  
The Impact ◽  
Health Efficiency

This study pays more attention to the energy consumption saving, environmental pollution, and health efficiency improvement. We employ the Slack-based measure of Dynamic network Data Envelopment Analysis (DEA) model (DNSBM) to assess the impact of forestry area on annual and overall energy and health efficiency in 2 intertemporal stages, and also put forward on direction and magnitude to be improved respect to the slack variables. For the empirical study, this study employs the 13 countries in the Association of Southeast Asian Nations Plus Three Cooperation (hereinafter referred to as APT) during 2011-2015. From the empirical evidence, it is not easy to raise gross domestic product while reducing energy consumption and PM2.5 emissions to improve energy efficiency. What makes people neglect is the impact of reduced forestry area on health efficiency. Optimistically, all economies are able to adopt measures from policy and technical perspectives, for instance, appropriately adjust energy-related policies, energetically develop innovative energy technologies, and preserve forestry areas, to create a harmonious atmosphere featuring economic development, environmental conservation, and national health and well-being.

scholarly journals Measures to improve energy efficiency of building utility systems

2021 ◽  
Vol 48 (2) ◽  
pp. 73-80
Author(s):  
A. S. Gavrilov ◽  
A. E. Sergeev
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Systems Engineering ◽  
The State ◽  
Hot Water ◽  
Water Supply Systems ◽  
Technical Equipment ◽  
Building Energy Efficiency ◽  
Improve Energy Efficiency ◽  
Utility Systems

Objective. The goal of the study is to identify ways to improve energy efficiency by conducting a comprehensive analysis of engineering systems of a house, taking into account the existing model of energy supply and by monitoring the indicators of influence on the efficiency of engineering and technical equipment. Methods. The main method is based on a survey of the level of energy efficiency of heating and hot water supply systems. Results. The article discusses the concept of energy efficiency of a building, energy efficiency class, main utility systems of a residential building, indicators of influence on the state of systems, engineering component and ways to improve it. The article addresses issues related to a full analysis of existing systems in order to assess the implementation of necessary energy-saving measures, as well as their risks and benefits. The possibilities of controlling energy consumption and efficiency of works carried out due to the reconstruction of utility systems of the building have been determined. The results of the analysis of energy-efficient measures, and the feasibility of implementing each of them have been determined in order to identify optimal solutions. Conclusion. Increasing the energy efficiency of building utility systems is one of the priority tasks for creating comfortable living conditions. The energy efficiency class of building utility systems is established according to the state of a system, takes into account all quality indicators for energy consumption, and the energy certificate fully shows the level of energy efficiency.

scholarly journals An Advanced Decision Support Platform in Energy Management to Increase Energy Efficiency for Small and Medium Enterprises

2020 ◽  
Vol 10 (10) ◽  
pp. 3505
Author(s):  
Gheorghe Grigoraș ◽  
Bogdan-Constantin Neagu
Keyword(s):  
Data Mining ◽  
Energy Efficiency ◽  
Decision Support ◽  
Energy Consumption ◽  
Production Scheduling ◽  
Small And Medium Enterprises ◽  
Small Enterprise ◽  
Data Mining Techniques ◽  
Medium Enterprises ◽  
The Impact

The paper presents a new vision on the energy consumption management in the case of the small and medium enterprises (SMEs), integrated into an advanced decision support platform, with technical and economic benefits on increasing the energy efficiency, with four modules for database management, profiling, forecasting, and production scheduling. Inside each module, artificial intelligence and data mining techniques were proposed to remove the uncertainties regarding the dynamic of technological flows. Thus, the data management module includes the data mining techniques, that extract the technical details on the energy consumption needed in the development of production scheduling strategies, the profiling module uses an original approach based on clustering techniques to determine the typical energy consumption profiles required in the optimal planning of the activities, the forecasting module contains a new approach based on an expert system to forecast the total energy consumption of the SMEs, and production scheduling module integrates a heuristic optimization method to obtain the optimal solutions in flattening the energy consumption profile. The testing was done for a small enterprise from Romania, belonging to the domain of trade and repair of vehicles. The obtained results highlighted the advantages of the proposed decision support platform on the decrease in the intensity of energy consumption per unit of product, reduction of the purchase costs, and modification of the impact for which energy bills have on the operational costs.

scholarly journals ANALYSIS OF RESULTS OF MEASURES PERFORMED TO INCREASE ENERGY EFFICIENCY IN VASIL KARAGIOZOV HIGH SCHOOL OF YAMBOL, BULGARIA

2018 ◽  
Vol 6 (4) ◽  
pp. 306-310 ◽  
Author(s):  
Ivan Binev
Keyword(s):  
High School ◽  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Saving ◽  
Energy Use ◽  
Energy Savings ◽  
Climatic Conditions ◽  
Improve Energy Efficiency ◽  
Before And After ◽  
The Impact

The report analyzes the results of the implemented measures to improve energy efficiency in Vasil Karagiozov High school of Yambol, Bulgaria. Energy savings are determined by measuring and/or calculating energy consumption with previously adopted baseline levels, implementing a measure or program to improve energy efficiency by providing normalized corrections corresponding to the impact of specific climatic conditions on energy use. A reference heating energy consumption of 38.62 kWh/m2 was determined after the renovation of the building. Comparing the reference energy costs for heating before and after the implementation of the energy saving measures show a real decrease of the energy consumption for heating by 53.44%. Compared to the reference energy consumption for heating before and after the energy saving measures show an actual reduction of energy consumption for heating by 47.86%.

scholarly journals Multi-GPU approach to global induction of classification trees for large-scale data mining

2021 ◽  
Author(s):  
Krzysztof Jurczuk ◽  
Marcin Czajkowski ◽  
Marek Kretowski
Keyword(s):  
Data Mining ◽  
Large Scale ◽  
Real Life ◽  
Population Based ◽  
Tree Structure ◽  
Global Approach ◽  
Data Parallel ◽  
Large Scale Data ◽  
The Impact ◽  
Scale Data

AbstractThis paper concerns the evolutionary induction of decision trees (DT) for large-scale data. Such a global approach is one of the alternatives to the top-down inducers. It searches for the tree structure and tests simultaneously and thus gives improvements in the prediction and size of resulting classifiers in many situations. However, it is the population-based and iterative approach that can be too computationally demanding to apply for big data mining directly. The paper demonstrates that this barrier can be overcome by smart distributed/parallel processing. Moreover, we ask the question whether the global approach can truly compete with the greedy systems for large-scale data. For this purpose, we propose a novel multi-GPU approach. It incorporates the knowledge of global DT induction and evolutionary algorithm parallelization together with efficient utilization of memory and computing GPU’s resources. The searches for the tree structure and tests are performed simultaneously on a CPU, while the fitness calculations are delegated to GPUs. Data-parallel decomposition strategy and CUDA framework are applied. Experimental validation is performed on both artificial and real-life datasets. In both cases, the obtained acceleration is very satisfactory. The solution is able to process even billions of instances in a few hours on a single workstation equipped with 4 GPUs. The impact of data characteristics (size and dimension) on convergence and speedup of the evolutionary search is also shown. When the number of GPUs grows, nearly linear scalability is observed what suggests that data size boundaries for evolutionary DT mining are fading.

scholarly journals Effectiveness of a Power Factor Correction Policy in Improving the Energy Efficiency of Large-Scale Electricity Users in Ghana

Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2582 ◽  
Author(s):  
Samuel Lotsu ◽  
Yuichiro Yoshida ◽  
Katsufumi Fukuda ◽  
Bing He
Keyword(s):  
Energy Efficiency ◽  
Power Factor ◽  
Large Scale ◽  
Regression Discontinuity ◽  
Power Factor Correction ◽  
Energy Crisis ◽  
Regression Discontinuity Design ◽  
The Government ◽  
Power Factor Improvement ◽  
The Impact

Confronting an energy crisis, the government of Ghana enacted a power factor correction policy in 1995. The policy imposes a penalty on large-scale electricity users, namely, special load tariff (SLT) customers of the Electricity Company of Ghana (ECG), whose power factor is below 90%. This paper investigates the impact of this policy on these firms’ power factor improvement by using panel data from 183 SLT customers from 1994 to 1997 and from 2012. To avoid potential endogeneity, this paper adopts a regression discontinuity design (RDD) with the power factor of the firms in the previous year as a running variable, with its cutoff set at the penalty threshold. The result shows that these large-scale electricity users who face the penalty because their power factor falls just short of the threshold are more likely to improve their power factor in the subsequent year, implying that the power factor correction policy implemented by Ghana’s government is effective.

scholarly journals Technological Energy Efficiency Improvements in Cement Industries

2021 ◽  
Vol 13 (7) ◽  
pp. 3810
Author(s):  
Alessandra Cantini ◽  
Leonardo Leoni ◽  
Filippo De Carlo ◽  
Marcello Salvio ◽  
Chiara Martini ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Descriptive Analysis ◽  
Cement Industry ◽  
Cement Plant ◽  
Improve Energy Efficiency ◽  
Energy Needs ◽  
Industrial Energy ◽  
Industrial Energy Consumption ◽  
Alternative Solutions

The cement industry is highly energy-intensive, consuming approximately 7% of global industrial energy consumption each year. Improving production technology is a good strategy to reduce the energy needs of a cement plant. The market offers a wide variety of alternative solutions; besides, the literature already provides reviews of opportunities to improve energy efficiency in a cement plant. However, the technology is constantly developing, so the available alternatives may change within a few years. To keep the knowledge updated, investigating the current attractiveness of each solution is pivotal to analyze real companies. This article aims at describing the recent application in the Italian cement industry and the future perspectives of technologies. A sample of plant was investigated through the analysis of mandatory energy audit considering the type of interventions they have recently implemented, or they intend to implement. The outcome is a descriptive analysis, useful for companies willing to improve their sustainability. Results prove that solutions to reduce the energy consumption of auxiliary systems such as compressors, engines, and pumps are currently the most attractive opportunities. Moreover, the results prove that consulting sector experts enables the collection of updated ideas for improving technologies, thus giving valuable inputs to the scientific research.

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