scholarly journals Research on Charging Combination Based on Batch Weight Fit Rule for Energy Saving in Forging

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Zhu Baiqing ◽  
Lu Haixing ◽  
Tong Yifei ◽  
Li Dongbo ◽  
Xia Yong
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Energy Saving ◽  
High Energy ◽  
Forging Process ◽  
Proposed Model ◽  
Energy Consuming ◽  
Reduce Energy Consumption ◽  
Batch Weight ◽  
Holding Temperature

As a traditional high energy-consuming industry, the forging industry consumes a lot of energy. The activity consuming the highest energy during forging process is the heating. The problem regarding how to separate workpieces with the same holding temperature and holding time and combine them for charging in forging was analyzed and a model based on batch weight fit rule for optimizing the charging combination with the goal of energy saving was proposed. A genetic algorithm was adopted to optimize and solve the model in order to reduce energy consumption in forging. In addition, an instance was given to prove the effectiveness of the proposed model.

Research on the Energy Saving Potential of Official Cars in China

2011 ◽  
Vol 128-129 ◽  
pp. 1217-1221
Author(s):  
Quan Le Liu ◽  
Wei Chen
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Fuel Efficiency ◽  
High Energy ◽  
Maintenance Cost ◽  
Strategy Method ◽  
Energy Saving Potential ◽  
Energy Consuming

The quantity of official cars increased with the speed exceeding 20% every year which need much more energy be consumed to meet the official car needs. To investigate the energy saving potential of official cars in China, This paper introduced the strategy method with systemic viewpoint to reduce official cars energy consumption through analyzing the reason of high energy consuming of official cars. The resulted showed that only reduce the quantities and maintenance cost, and decline the displacement and using frequency can realize fuel efficiency of official cars.

Energy Saving Design Method for Large Weak Electronic Circuit

2014 ◽  
Vol 513-517 ◽  
pp. 4127-4130
Author(s):  
Bo Yu ◽  
Li Song ◽  
Zhong Ming Wu
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Circuit Design ◽  
Large Scale ◽  
Electronic Circuit ◽  
Design Method ◽  
High Energy ◽  
Proposed Model ◽  
Consumption Situation ◽  
High Energy Consumption

This paper mainly discusses the energy-saving design method for large weak electronic circuit. In large scale electronic circuit, there is no direct relevance between every two element modules. The traditional weak element circuit design concentrates in a single module, while ignoring module dependencies in energy-saving design, resulting in high energy consumption in large-scale electronic circuits. This paper proposes to establish the relevance energy-loss model for each model in the large-scale weak electronic circuit to obtain the energy consumption situation, and consider the energy consumption in module coordination to saving energy. The simulation results show that the proposed model used for large-scale energy weak circuit design can effectively reduce the energy consumption in weak circuit application.

Approaches and Countermeasures for Development of Energy-Saving Technology Service Industry in Tangshan City

2013 ◽  
Vol 368-370 ◽  
pp. 1332-1337
Author(s):  
Xiao Chun Liu ◽  
Li Na Zhou ◽  
Jie Bai
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Industrial Structure ◽  
Service Industry ◽  
Energy Performance ◽  
High Energy ◽  
Total Energy Consumption ◽  
Energy Service ◽  
Energy Consuming ◽  
Energy Saving Technology

Energy-saving service industry becomes a new force suddenly rises, and will be the largest energy-saving industry in the world. Tangshan City, adjacent to Beijing and Tianjin, is a typical resource-based city. Because its industrial structure is based on iron and steel, petrochemical and other resources, while energy-consuming structure based mainly on coal, that made Tangshan become one of China's high energy-consuming cities. In 2011 the city's total energy consumption was 95.5282 million tons of standard coal, accounting for 32.4% of Hebei province's energy consumption, and 2.7% of the whole state's respectively, while Tangshan City's GDP accounting for 22.5% of Hebei province and 1.2% of the nation.The huge energy consumption promotes vigorous development of energy-saving industry.The scale of Tangshan's energy service industry increases rapidly currently, for example, the output value of energy service industry in 2009 reached 32 billion RMB, and then its scale is continues to expand, and EPC(Energy Performance Contracting) is implemented gradually. However, it also shows a lot of problems, such as samll amount of energy-saving enterprises, lack of core competitive companies, shortage of funds, financing difficulties, lack of leading enterprises, irrational personnel structure, and the market system has not formed yet. If Tangshan's energy-saving services industry wants to achieve a good development, it must concentrate on that the publicity of industrial policy, creating a favorable environment for its development, speeding up development and applications of energy-saving technology, establishing industrial norms, strengthening self-discipline, innovating financial system, improve the financing environment, establishing credit publicity system, and promoting construction of industrial credit system.

The Research of Measuring Approach and Energy Efficiency for Hadoop Periodic Jobs

2015 ◽  
Vol 8 (1) ◽  
pp. 206-210 ◽  
Author(s):  
Yu Junyang ◽  
Hu Zhigang ◽  
Han Yuanyuan
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Energy Saving ◽  
Energy Estimate ◽  
Cloud Platform ◽  
Periodic Tasks ◽  
Current Consumption ◽  
Reduce Energy Consumption

Current consumption of cloud computing has attracted more and more attention of scholars. The research on Hadoop as a cloud platform and its energy consumption has also received considerable attention from scholars. This paper presents a method to measure the energy consumption of jobs that run on Hadoop, and this method is used to measure the effectiveness of the implementation of periodic tasks on the platform of Hadoop. Combining with the current mainstream of energy estimate formula to conduct further analysis, this paper has reached a conclusion as how to reduce energy consumption of Hadoop by adjusting the split size or using appropriate size of workers (servers). Finally, experiments show the effectiveness of these methods as being energy-saving strategies and verify the feasibility of the methods for the measurement of periodic tasks at the same time.

scholarly journals Assessing a Multi-Objective Genetic Algorithm with a Simulated Environment for Energy-Saving of Air Conditioning Systems with User Preferences

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 344
Author(s):  
Alejandro Humberto García Ruiz ◽  
Salvador Ibarra Martínez ◽  
José Antonio Castán Rocha ◽  
Jesús David Terán Villanueva ◽  
Julio Laria Menchaca ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Energy Saving ◽  
User Satisfaction ◽  
Air Conditioning ◽  
State Of The Art ◽  
User Preferences ◽  
The State ◽  
Nsga Ii ◽  
Air Conditioning System

Electricity is one of the most important resources for the growth and sustainability of the population. This paper assesses the energy consumption and user satisfaction of a simulated air conditioning system controlled with two different optimization algorithms. The algorithms are a genetic algorithm (GA), implemented from the state of the art, and a non-dominated sorting genetic algorithm II (NSGA II) proposed in this paper; these algorithms control an air conditioning system considering user preferences. It is worth noting that we made several modifications to the objective function’s definition to make it more robust. The energy-saving optimization is essential to reduce CO2 emissions and economic costs; on the other hand, it is desirable for the user to feel comfortable, yet it will entail a higher energy consumption. Thus, we integrate user preferences with energy-saving on a single weighted function and a Pareto bi-objective problem to increase user satisfaction and decrease electrical energy consumption. To assess the experimentation, we constructed a simulator by training a backpropagation neural network with real data from a laboratory’s air conditioning system. According to the results, we conclude that NSGA II provides better results than the state of the art (GA) regarding user preferences and energy-saving.

scholarly journals Study on Energy-saving Insulation Materials in the Building’s Exterior

2015 ◽  
Vol 4 (1) ◽  
pp. 4
Author(s):  
Yang Zhang ◽  
Yazhi Hu
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Construction Industry ◽  
New Technologies ◽  
High Energy ◽  
Insulation Material ◽  
Curtain Wall ◽  
Construction Engineering ◽  
Technology Application ◽  
Insulation Materials

<p>Construction industry has been one of China's energy guzzlers, if we can reduce the energy consumption of the building industry through the use of new materials or new technologies, which will have a significant impact on the development of economy and society. The status quo of China's construction industry, high energy consumption, paper use energy-saving technologies in the field of construction works to expand the analysis, discusses the necessity of the construction industry currently uses energy-saving insulation materials and analyzes the current energy field of construction engineering technology application status, on the basis of focus on the application of energy-saving insulation materials in construction, particularly in the new system and the new glass curtain wall insulation material in construction applications, which further enhance the energy-saving technology within the field of construction engineering the application level has a certain reference.</p>

Multi-Criteria Decision Support System for Green Commercial Space Design

2018 ◽  
Vol 43 (4) ◽  
pp. 5-15
Author(s):  
Hao-Cheng Huang ◽  
Yeng-Horng Perng
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Energy Saving ◽  
Support System ◽  
Human Life ◽  
Evaluation Model ◽  
High Energy ◽  
Commercial Space ◽  
Proposed Model ◽  
Commercial Spaces

Commercial space features essential characteristics of attracting clients and creating profits; thus, the exterior and interior designs of conventional commercial space were often made to look grandiose and overdecorated. Over time, according to commercial attributes, operator preferences, and style of the designer, commercial spaces have constantly undergone renovation into varied styles. However, the physical renovation processhas caused multiple and composite types of environmental pollution, such as waste and noise pollution caused by breaking of walls or partitions, anddecorative paint pollution, as well as the use of high-energy-consuming lighting equipment, air-conditioning systems, and decorative materials. Global pollution has caused climate change, endangering living organismsand human life. Furthermore, no effective method exists to control the problem of high greenhouse gas emissions. Therefore, this study used energy-saving design concerns of a garden-type commercial space to propose an energy-saving evaluation model. The study combined three methodologies, the Delphi method, analytic hierarchy process, and fuzzy logic theory, to construct a multi-criteria decision support system for designing green commercial spaces, and used the green spatial design of a garden café as an example to illustrate the high objectivity and adaptability of the proposed model in practical application. The study also used an international award-winning case to validate that the proposed model had practical value as a reference to support key design decisions.

Energy Aware Grid Scheduling for Dependent Task Using Genetic Algorithm

2016 ◽  
Vol 7 (2) ◽  
pp. 18-36
Author(s):  
Shiv Prakash ◽  
Deo Prakash Vidyarthi
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Job Scheduling ◽  
Computing System ◽  
Computational Grid ◽  
Task Execution ◽  
Energy Aware ◽  
Optimal Energy ◽  
Proposed Model ◽  
Dynamic Voltage

Consumption of energy in the large computing system is an important issue not only because energy sources are depleting fast but also due to the deteriorating environmental conditions. A computational grid is a large heterogeneous distributed computing platform which consumes enormous energy in the task execution. Energy-aware job scheduling, in the computational grid, is an important issue that has been addressed in this work. If the tasks are properly scheduled, keeping the optimal energy concern, it is possible to save the energy consumed by the system in the task execution. The prime objective, in this work, is to schedule the dependent tasks of a job, on the grid nodes with optimal energy consumption. Energy consumption is estimated with the help of Dynamic Voltage Frequency Scaling (DVFS). Makespan, while optimizing the energy consumption, is also taken care of in the proposed model. GA is applied for the purpose and therefore the model is named as Energy Aware Genetic Algorithm (EAGA). Performance evaluation of the proposed model is done using GridSim simulator. A comparative study with other existing models viz. min-min and max-min proves the efficacy of the proposed model.

Thinking of Comprehensive Energy-Saving System Construction for Urban Rail Transit

2014 ◽  
Vol 505-506 ◽  
pp. 405-409
Author(s):  
Jun Ke Liang ◽  
Zhi Gang Liu ◽  
Yuan Chun Huang
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Optimization Design ◽  
High Efficiency ◽  
High Energy ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
System Construction ◽  
Planning Period ◽  
Urban Rail

The High Energy Consumption of the Current Urban Rail Transit Industry, High Efficiency Energy Saving Measures must be Taken. this Paper Entity from the Traction Energy Consumption, Building Structure and Operating Equipment Aspects of the Current Situation, Described the Energy Saving Strategies. Aiming at the Present Problems Existing in Energy Saving Practice, this Article Puts Forward the Comprehensive Energy Saving System which Contains Optimization Design in Planning Period, Low Resource Consumption in Construction Period, Energy Saving Work in Operation Period. above all, Implement Energy Saving Practice at Every Concrete Work of Reaching.

An intelligent system for energy management in smart cities based on big data and ontology

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zaoui Sayah ◽  
Okba Kazar ◽  
Brahim Lejdel ◽  
Abdelkader Laouid ◽  
Ahmed Ghenabzia
Keyword(s):  
Big Data ◽  
Energy Consumption ◽  
Energy Saving ◽  
Intelligent System ◽  
Smart Cities ◽  
Semantic Integration ◽  
Saving Energy ◽  
Content Type ◽  
Multi Agent ◽  
Reduce Energy Consumption

PurposeThis research paper aims at proposing a framework based on semantic integration in Big Data for saving energy in smart cities. The presented approach highlights the potential opportunities offered by Big Data and ontologies to reduce energy consumption in smart cities.Design/methodology/approachThis study provides an overview of semantics in Big Data and reviews various works that investigate energy saving in smart homes and cities. To reach this end, we propose an efficient architecture based on the cooperation between ontology, Big Data, and Multi-Agent Systems. Furthermore, the proposed approach shows the strength of these technologies to reduce energy consumption in smart cities.FindingsThrough this research, we seek to clarify and explain both the role of Multi-Agent System and ontology paradigms to improve systems interoperability. Indeed, it is useful to develop the proposed architecture based on Big Data. This study highlights the opportunities offered when they are combined together to provide a reliable system for saving energy in smart cities.Practical implicationsThe significant advancement of contemporary applications (smart cities, social networks, health care, IoT, etc.) requires a vast emergence of Big Data and semantics technologies in these fields. The obtained results provide an improved vision of energy-saving and environmental protection while keeping the inhabitants’ comfort.Originality/valueThis work is an efficient contribution that provides more comprehensive solutions to ontology integration in the Big Data environment. We have used all available data to reduce energy consumption, promote the change of inhabitant’s behavior, offer the required comfort, and implement an effective long-term energy policy in a smart and sustainable environment.

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