Method Research on Assessment of Regional Energy Consumption and Air Pollutants Emission – A Case Study

2010 ◽  
Vol 113-116 ◽  
pp. 616-622
Author(s):  
Xue Liang Yuan ◽  
Qing Song Wang ◽  
Rui Min Mu ◽  
Chun Yuan Ma
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Saving ◽  
Air Pollutants ◽  
Limiting Factors ◽  
Average Level ◽  
Regional Energy ◽  
Industrial Dust ◽  
Pollutants Emission

Low energy efficiency, energy shortage and energy related environmental issues are the important limiting factors for the development of China. As a developed province, high economic growth has had huge implications for great energy consumption and produced significant air pollutants in Shandong. REPI model is introduced to analyze the evolution of the performance of energy consumption, emissions of SO2, soot and industrial dust in Shandong over the past 12 years. Energy saving index of Shandong kept going up since 1997 and surpassed 1 in 2002, which means the obvious decrease of energy efficiency. SO2 saving index was greater than 1 in 1997-2002 then less than 1 in 2003-2008, which shows SO2 control in Shandong is significant. The saving index of soot and industrial dust kept much less than 1, which means the reduction of these two air pollutants are much better than China average level in the study period. Though the saving indexes of SO2, soot and industrial dust are all less than 1 after 2002, which show the reduction of these pollutants are above China average level, we should still be aware for the massive emissions of these pollutants. To balance economic development, energy saving as well as pollutants reduction, Shandong is faced with huge pressure.

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 Evaluation of CO2 emissions and energy use with different container terminal layouts

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Muhammad Arif Budiyanto ◽  
Muhammad Hanzalah Huzaifi ◽  
Simon Juanda Sirait ◽  
Putu Hangga Nan Prayoga
Keyword(s):  
Energy Efficiency ◽  
Sustainable Development ◽  
Energy Consumption ◽  
Statistical Analysis ◽  
Energy Use ◽  
Container Terminal ◽  
Container Terminals ◽  
Future Planning ◽  
Container Handling

AbstractSustainable development of container terminals is based on energy efficiency and reduction in CO2 emissions. This study estimated the energy consumption and CO2 emissions in container terminals according to their layouts. Energy consumption was calculated based on utility data as well as fuel and electricity consumptions for each container-handling equipment in the container terminal. CO2 emissions were estimated using movement modality based on the number of movements of and distance travelled by each container-handling equipment. A case study involving two types of container terminal layouts i.e. parallel and perpendicular layouts, was conducted. The contributions of each container-handling equipment to the energy consumption and CO2 emissions were estimated and evaluated using statistical analysis. The results of the case study indicated that on the CO2 emissions in parallel and perpendicular layouts were relatively similar (within the range of 16–19 kg/TEUs). These results indicate that both parallel and perpendicular layouts are suitable for future ports based on sustainable development. The results can also be used for future planning of operating patterns and layout selection in container terminals.

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.

Study on Energy-Saving Product Concept Design Based on TRIZ and Function Analysis

2010 ◽  
Vol 156-157 ◽  
pp. 123-126 ◽  
Author(s):  
Fu Ying Zhang ◽  
Hong Chao Zhang ◽  
Hui Zheng ◽  
Qing Qing Zhang
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Function Analysis ◽  
New Product ◽  
Concept Design ◽  
Energy And Environment ◽  
Product Concept ◽  
Product Function ◽  
And Function

The energy consumption and environmental impacts of a product are largely determined during concept design. It is the core for energy saving product development to integrate energy saving into product concept design process. In this paper, a framework for energy-saving product concept design based on TRIZ/function analysis is proposed, the energy flow chart is built based on the analysis of product function. By eliminating the harmful function associated with energy and environment, resolving the conflict parameter and attributes of components in energy and function, the new product that satisfy user needs while minimizing energy consumption is obtained. A case study is also presented to illustrate the effectiveness of the proposed design framework.

scholarly journals CO2 and Air Pollutants Emissions under Different Scenarios Predicted by a Regional Energy Consumption Modeling System for Shanghai, China

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 1006
Author(s):  
Jing Wang ◽  
Yan Zhang ◽  
Libo Wu ◽  
Weichun Ma ◽  
Limin Chen
Keyword(s):  
Carbon Dioxide ◽  
Energy Consumption ◽  
Urban Areas ◽  
Air Pollutants ◽  
Energy Demand ◽  
Carbon Tax ◽  
Model Simulation ◽  
Energy System ◽  
Energy Supply System ◽  
Regional Energy

About 75% energy demand and emissions all concentrate in urban areas, especially in the metropolises, placing a heavy burden on both the energy supply system and the environment system. To explore low emission pathways and provide policy recommendations for the Shanghai energy system and the environmental system to reach the carbon dioxide (CO2) peak by 2030 and attain emission reduction targets for local air pollutants (LAPs), a regional energy–environment optimization model was developed in this study, considering system costs, socio-economic development and technology. To verify the reliability of the model simulation and evaluate the model risk, a historical scenario was defined to calculate the emissions for 2004–2014, and the data were compared with the bottom-up emission inventory results. By considering four scenarios, we simulated the energy consumption and emissions in the period of 2020–2030 from the perspective of energy policies, economic measures and technology updates. We found that CO2 emissions might exceed the amount of 250 million tons by the end of 2020 under the current policy, and carbon tax with a price of 40 CNY per ton of carbon dioxide is an imperative measure to lower carbon emissions. Under the constraints, the emissions amount of SO2, NOx, PM10, and PM2.5 will be reduced by 95.3–180.8, 207.8–357.1, 149.4–274.5, and 59.5–119.8 Kt in 2030, respectively.

Using energy profiles to identify university energy reduction opportunities

2016 ◽  
Vol 17 (2) ◽  
pp. 188-207 ◽  
Author(s):  
Nandarani Maistry ◽  
Harold Annegarn
Keyword(s):  
South Africa ◽  
Energy Efficiency ◽  
Energy Consumption ◽  
Quantitative Research ◽  
Electricity Consumption ◽  
Working Hours ◽  
Content Type ◽  
Academic Calendar ◽  
The University

Purpose – The purpose of this paper is to outline efforts at the University of Johannesburg, a large metropolitan university in Gauteng province, to examine energy efficiency within the context of the green campus movement, through the analysis of electricity consumption patterns. The study is particularly relevant in light of the cumulative 230 per cent increase in electricity costs between 2008 and 2014 in South Africa that has forced institutions of higher education to seek ways to reduce energy consumption. Design/Methodology/Approach – A quantitative research design was adopted for the analysis of municipal electricity consumption records using a case study approach to identify trends and patterns in consumption. The largest campus of the University of Johannesburg, which is currently one of the largest residential universities in South Africa, was selected as a case study. Average diurnal consumption profiles were plotted according to phases of the academic calendar, distinguished by specific periods of active teaching and research (in-session); study breaks, examinations and administration (out-of-session); and recesses. Average profiles per phase of the academic calendar were constructed from the hourly electricity consumption and power records using ExcelTM pivot tables and charts. Findings – It was found that the academic calendar has profound effects on energy consumption by controlling the level of activity. Diurnal maximum consumption corresponds to core working hours, peaking at an average of 2,500 kWh during “in-session” periods, 2,250 kWh during “out-of-session” periods and 2,100 kWh during recess. A high base load was evident throughout the year (between 1,300 and 1,650 kWh), mainly attributed to heating and cooling. By switching off the 350 kW chiller plant on weekdays, a 9 per cent electricity reduction could be achieved during out-of-session and recess periods. Similarly, during in-session periods, a 6 per cent reduction could be achieved. Practical implications – Key strategies and recommendations are presented to stimulate energy efficiency implementation within the institution. Originality Value – Coding of consumption profiles against the academic calendar has not been previously done in relation to an academic institution. The profiles were used to establish the influence of the academic calendar on electricity consumption, which along with our own observation were used to identify specific consumption reduction opportunities worth pursuing.

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.

Energy Consumption and Energy Saving Research Status of Air Compressor System

2014 ◽  
Vol 628 ◽  
pp. 225-228
Author(s):  
Xiao Lin Tian ◽  
Shou Gen Hu ◽  
Hong Bo Qin ◽  
Jun Zhao ◽  
Ling Yuan Ran
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Saving ◽  
Compressed Air ◽  
Efficiency Evaluation ◽  
Air Compressor ◽  
Research Status ◽  
Air System ◽  
Energy Efficiency Evaluation ◽  
At Home

As the most widely used fourth energy, compressed air system has high operating costs. The research about energy consumption and energy optimization measures of compressed air system has become the new field to achieve energy saving among countries all over the world. In recent years, air compressor system researches in energy consumption, influence factors, energy saving technologies and energy efficiency evaluation have been carried out at home and abroad, and some achievements have been achieved. This paper summarizes energy consumption research status of air compressor system at home and abroad, and energy-saving technologies of compressed air in generation link, treatment link and gas link, and energy efficiency evaluation methods for of air compressor systems. Potentials and drawbacks of current researches are analyzed simultaneously. In the end energy-saving development directions of air compressor system are predicted.

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