A new evaluation system for energy-saving effect based on extended energy consumption and extended energy efficiency

2012 ◽  
Author(s):  
Kaixiang Huan ◽  
Yongqiang Zhu ◽  
Huiqi Shen
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Saving ◽  
Evaluation System ◽  
Saving Effect

Study on the Problems and Solutions of Building Energy Efficiency

2014 ◽  
Vol 525 ◽  
pp. 439-442
Author(s):  
Ling Jiao
Keyword(s):  
Energy Efficiency ◽  
Sustainable Development ◽  
Energy Consumption ◽  
Energy Saving ◽  
Evaluation System ◽  
Green Building ◽  
Building Energy ◽  
Green Energy ◽  
Building Energy Efficiency ◽  
Building Energy Consumption

With the development of economy, the progress of the times, the city continued to expand the scale of construction, building energy consumption is more and more serious, and the green energy-saving buildings are paid more and more attention in society. Building energy efficiency can fundamentally promote the savings and the rational use of energy and resources, Building energy efficiency is the needs to guarantee the sustainable development of national economy. With problems in building energy efficiency as the point of penetration, this paper analyses the present situations of building energy consumption and the major energy-saving issues in China. On the basis, in order to promote the green building of sustainable development, from thinking, evaluation system, design and other aspects some suggestions and measures are proposed .

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.

The Establishment of Exergy Consumption Evaluation Index in Heated Oil Pipeline Transportation

2013 ◽  
Vol 401-403 ◽  
pp. 2143-2146 ◽  
Author(s):  
Qing Lin Cheng ◽  
Zhe Li ◽  
Shuai Shao ◽  
Wei Sun ◽  
Xu Xu Wang
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Evaluation System ◽  
Index Set ◽  
Oil Pipeline ◽  
Heated Oil ◽  
Consumption Index ◽  
Exergy Consumption ◽  
Exergy Transfer ◽  
Set Up

The exergy consumption during the transportation of heated oil includes four items: valid and invalid pressure exergy consumption, valid and invalid heat exergy consumption. These four parts are taken as the same loss in traditional evaluation systems of pipeline energy consumption, which somewhat hinders the further energy-conservation study. So establishing a scientific exergy consumption evaluation system is an important basis work of energy efficiency management. Based on the index system of energy efficiency for pipeline proposed by predecessors, the meaning of energy quality for exergy and the categories of exergy flow, the energy consumption index set of exergy transfer is set up in this article. Moreover, by computing exergy consumption index of exergy transfer for an oil pipeline in Daqing Oilfield, a part of representative indexes are selected by analyzing the obtained data with correlation coefficient method. Finally, the exergy consumption evaluation system is constructed.

Energy Consumption Analysis on Office Building Ventilation

2012 ◽  
Vol 516-517 ◽  
pp. 1139-1143
Author(s):  
Ke Chun Sun ◽  
Wei Jun Zhang
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Air Conditioning ◽  
Room Temperature ◽  
Simulation Analysis ◽  
Simulation Software ◽  
Energy Simulation ◽  
Office Building ◽  
Saving Effect ◽  
Night Ventilation

Chongqing weather conditions as the representative, energy simulation software DesT-c Chongqing office building energy simulation analysis, simulated natural building under different ventilation conditions at room temperature, the energy consumption of building cooling load and air-conditioning system changes, with an emphasis on energy-saving effect of the night ventilation; The study showed that in Chongqing reasonable use of ventilation reduce building natural room temperature to a certain extent; Sensitive indicators of building air conditioning energy consumption than the heating energy consumption of ventilation was significantly; Night ventilation when the number of ventilators is less than 5 times / h, the energy saving effect is very significant.

ФОРМУВАННЯ МЕРЕЖІ ЦЕНТРІВ ЕНЕРГОХАБА ЗНАНЬ ДЛЯ ПРОГНОЗУВАННЯ ПРІОРИТЕТНОГО НАПРЯМУ РОЗВИТКУ ПРОГРАМ ЕНЕРГОЕФЕКТИВНОСТІ ТА ЕНЕРГОЗБЕРЕЖЕННЯ В ЗАКЛАДАХ ВИЩОЇ ОСВІТИ

2022 ◽  
pp. 35-44
Author(s):  
Ivan M. Gryshchenko ◽  
Mykhailo O. Verhun ◽  
Andrii S. Prokhorovskyi
Keyword(s):  
Higher Education ◽  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Saving ◽  
Higher Education Institutions ◽  
Action Plan ◽  
Energy Sources ◽  
Energy Supply System ◽  
Depth Analysis ◽  
The University

This article attempts to verify the relevance of building a network of energy knowledge hub centres to tackle the priority objective in enhancing energy efficiency and energy saving management in higher education institutions. It is emphasized that the issues of careful and wise use of fuels and energy resources challenge more government efforts, active use of advanced projects to manage energy saving and energy efficiency through the integrated use of different energy sources. The study argues that to identify the potential for energy saving, setting regulatory indicators of energy consumption, determining the key energy saving measures and target objects in the public sector where energy saving programs are planned to be implemented, there is a need to conduct energy surveys with further developing of energy passports for buildings. In the frameworks of this study, the following research methods were used: abstract and logical analysis – to interpret the essence of energy saving concepts for universities; systemic approach – to identify the specifics of energy saving projects implementation in universities; in-depth analysis and synthesis – to forecast the university development priority area of the "Energy efficiency and energy saving"; system, structural, comparative and statistical analyses – to assess the energy consumption in universities; economic and statistical methods – to evaluate the level and the dynamics of the energy sources use before and after the implementation of project activities; graph-based and analytical methods – to facilitate visual representation and schematic presentation of forecasts for further development of energy efficiency and energy saving systems. The study offers a mechanism to shape a network of energy knowledge hub centres to forecast a priority development area of energy efficiency and energy saving programs in higher education institutions along with providing an overview on the process of energy saving based on energy knowledge hub centres by carrying out the following tasks: project identification, scanning, energy audit, implementation of an action plan, and monitoring. It has been verified that to enhance the energy supply system in the university buildings, the following objectives should be attained: using the energy knowledge hub to forecast the university energy efficiency and energy saving programme, implementing an automated individual heating station with weather regulation and installing new radiator heaters.

Application of BIM Technology on Energy Efficiency Building Design

2014 ◽  
Vol 587-589 ◽  
pp. 283-286 ◽  
Author(s):  
Mei Zhang
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Saving ◽  
Design Method ◽  
Building Design ◽  
Building Energy ◽  
Information Modeling ◽  
Building Energy Consumption ◽  
Analysis Software ◽  
Building Model

According to the current application situation and domestic energy of our current building energy efficiency design analysis software, in view of the current traditional energy-saving design method can't meet the need of practical problems, put forward the BIM (building information modeling) analysis technology and building energy consumption are combined, anew design method for energy saving building. Application of BIM technology to create virtual building model contains all the information architecture, the virtual building model into the building energy analysis software, identification, automatic conversion and analyzing a large number of construction data information includes in the model, which is convenient to get the building energy consumption analysis.

scholarly journals DQN-based energy-efficient routing algorithm in software-defined data centers

2020 ◽  
Vol 16 (6) ◽  
pp. 155014772093577
Author(s):  
Zan Yao ◽  
Ying Wang ◽  
Xuesong Qiu
Keyword(s):  
Energy Consumption ◽  
Load Balancing ◽  
Energy Saving ◽  
Heuristic Algorithm ◽  
Data Center ◽  
Energy Efficient ◽  
Data Centers ◽  
Routing Algorithm ◽  
Energy Efficient Routing ◽  
Saving Effect

With the rapid development of data centers in smart cities, how to reduce energy consumption and how to raise economic benefits and network performance are becoming an important research subject. In particular, data center networks do not always run at full load, which leads to significant energy consumption. In this article, we focus on the energy-efficient routing problem in software-defined network–based data center networks. For the scenario of in-band control mode of software-defined data centers, we formulate the dual optimal objective of energy-saving and the load balancing between controllers. In order to cope with a large solution space, we design the deep Q-network-based energy-efficient routing algorithm to find the energy-efficient data paths for traffic flow and control paths for switches. The simulation result reveals that the deep Q-network-based energy-efficient routing algorithm only trains part of the states and gets a good energy-saving effect and load balancing in control plane. Compared with the solver and the CERA heuristic algorithm, energy-saving effect of the deep Q-network-based energy-efficient routing algorithm is almost the same as the heuristic algorithm; however, its calculation time is reduced a lot, especially in a large number of flow scenarios; and it is more flexible to design and resolve the multi-objective optimization problem.

scholarly journals HEMS-IoT: A Big Data and Machine Learning-Based Smart Home System for Energy Saving

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1097 ◽  
Author(s):  
Isaac Machorro-Cano ◽  
Giner Alor-Hernández ◽  
Mario Andrés Paredes-Valverde ◽  
Lisbeth Rodríguez-Mazahua ◽  
José Luis Sánchez-Cervantes ◽  
...  
Keyword(s):  
Machine Learning ◽  
Energy Efficiency ◽  
Big Data ◽  
Energy Consumption ◽  
Energy Saving ◽  
Smart Home ◽  
User Preferences ◽  
The Internet ◽  
Automation Systems ◽  
Home Energy Management

Energy efficiency has aroused great interest in research worldwide, because energy consumption has increased in recent years, especially in the residential sector. The advances in energy conversion, along with new forms of communication, and information technologies have paved the way for what is now known as smart homes. The Internet of Things (IoT) is the convergence of various heterogeneous technologies from different application domains that are used to interconnect things through the Internet, thus allowing for the detection, monitoring, and remote control of multiple devices. Home automation systems (HAS) combined with IoT, big data technologies, and machine learning are alternatives that promise to contribute to greater energy efficiency. This work presents HEMS-IoT, a big data and machine learning-based smart home energy management system for home comfort, safety, and energy saving. We used the J48 machine learning algorithm and Weka API to learn user behaviors and energy consumption patterns and classify houses with respect to energy consumption. Likewise, we relied on RuleML and Apache Mahout to generate energy-saving recommendations based on user preferences to preserve smart home comfort and safety. To validate our system, we present a case study where we monitor a smart home to ensure comfort and safety and reduce energy consumption.

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