scholarly journals A comparison of bottom-up methods for estimating institutional building energy use to inform resource and emission reduction strategies

2021 ◽  
Author(s):  
Christopher Xavier Mendieta
Keyword(s):  
Energy Efficiency ◽  
Emission Reduction ◽  
Energy Demand ◽  
Large Scale ◽  
Energy Use ◽  
Reference Method ◽  
Bottom Up ◽  
Energy Error ◽  
Reduction Strategies ◽  
Emission Reduction Strategies

Bottom-up engineering models are an emerging approach for evaluating energy efficiency solutions at district or regional scales. More flexible than statistical models, bottom-up models allow planners to quantitatively evaluate energy efficiency and supply options, leading to more effective policies and energy demand solutions that better reflect our changing climate. This thesis compares two bottom-up methods for exploring resource and emission reduction strategies in the institutional sector: the Wireframe method and the Reference method. These methods are compared by predicting the annual consumption of post-secondary student residences in Southern Ontario and measuring the error of each, compared with the 2013 mandatory energy report data from the Ministry of Energy of Ontario. Both methods produced aggregate energy error ranges of 5% to 12% in a detailed analysis, suggesting that they are both effective for large-scale energy reduction studies.

scholarly journals A comparison of bottom-up methods for estimating institutional building energy use to inform resource and emission reduction strategies

2021 ◽  
Author(s):  
Christopher Xavier Mendieta
Keyword(s):  
Energy Efficiency ◽  
Emission Reduction ◽  
Energy Demand ◽  
Large Scale ◽  
Energy Use ◽  
Reference Method ◽  
Bottom Up ◽  
Energy Error ◽  
Reduction Strategies ◽  
Emission Reduction Strategies

Bottom-up engineering models are an emerging approach for evaluating energy efficiency solutions at district or regional scales. More flexible than statistical models, bottom-up models allow planners to quantitatively evaluate energy efficiency and supply options, leading to more effective policies and energy demand solutions that better reflect our changing climate. This thesis compares two bottom-up methods for exploring resource and emission reduction strategies in the institutional sector: the Wireframe method and the Reference method. These methods are compared by predicting the annual consumption of post-secondary student residences in Southern Ontario and measuring the error of each, compared with the 2013 mandatory energy report data from the Ministry of Energy of Ontario. Both methods produced aggregate energy error ranges of 5% to 12% in a detailed analysis, suggesting that they are both effective for large-scale energy reduction studies.

scholarly journals Statistical and machine learning models for optimizing energy in parallel applications

2019 ◽  
Vol 33 (6) ◽  
pp. 1079-1097 ◽  
Author(s):  
Mark Endrei ◽  
Chao Jin ◽  
Minh Ngoc Dinh ◽  
David Abramson ◽  
Heidi Poxon ◽  
...  
Keyword(s):  
Machine Learning ◽  
Energy Efficiency ◽  
High Performance ◽  
Large Scale ◽  
Energy Use ◽  
Parallel Applications ◽  
Learning Models ◽  
Trade Off ◽  
Time Required ◽  
Machine Learning Models

Rising power costs and constraints are driving a growing focus on the energy efficiency of high performance computing systems. The unique characteristics of a particular system and workload and their effect on performance and energy efficiency are typically difficult for application users to assess and to control. Settings for optimum performance and energy efficiency can also diverge, so we need to identify trade-off options that guide a suitable balance between energy use and performance. We present statistical and machine learning models that only require a small number of runs to make accurate Pareto-optimal trade-off predictions using parameters that users can control. We study model training and validation using several parallel kernels and more complex workloads, including Algebraic Multigrid (AMG), Large-scale Atomic Molecular Massively Parallel Simulator, and Livermore Unstructured Lagrangian Explicit Shock Hydrodynamics. We demonstrate that we can train the models using as few as 12 runs, with prediction error of less than 10%. Our AMG results identify trade-off options that provide up to 45% improvement in energy efficiency for around 10% performance loss. We reduce the sample measurement time required for AMG by 90%, from 13 h to 74 min.

A method for energy efficiency assessment during urban energy planning

2014 ◽  
Vol 3 (2) ◽  
pp. 132-152 ◽  
Author(s):  
Karin Regina de Casas Castro Marins
Keyword(s):  
Energy Efficiency ◽  
Urban Areas ◽  
Energy Use ◽  
Energy Performance ◽  
Urban Morphology ◽  
Pollutant Emissions ◽  
Energy Planning ◽  
Bottom Up ◽  
Content Type ◽  
Urban Energy

Purpose – Energy use in urban areas has turned a subject of local and worldwide interest over the last few years, especially emphasized by the correlated greenhouse gases emissions. The purpose of this paper is to analyse the overall energy efficiency potential and emissions resulting from integrated solutions in urban energy planning, in the scale of districts and neighbourhoods in Brazil. Design/methodology/approach – The approach is based on the description and the application of a method to analyse energy performance of urban areas and support their planning. It is a quantitative bottom-up method and involves urban morphology, urban mobility, buildings and energy supply systems. Procedures are applied to the case study of Agua Branca urban development area, located in Sao Paulo, Brazil. Findings – In the case of Agua Branca area, energy efficiency measures in buildings have shown to be very important mostly for the buildings economies themselves. For the area as a whole, strategies in promoting public transport are more effective in terms of energy efficiency and also to decrease pollutant emissions. Originality/value – Literature review has shown there is a lack of approaches and procedures able to support urban energy planning at a community scale. The bottom-up method presented in this paper integrates a plenty of disaggregated and multisectoral parameters at the same stage in urban planning and shows that is possible to identify the most promising actions by building overall performance indexes.

scholarly journals Research on the Pollutant Emission Reduction Strategy and Simulation of Paper-Making Enterprises under the Reward and Punishment Mechanism

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Sen Zhang ◽  
Guangyuan Qin ◽  
Yifan Xie ◽  
Yuan Tian ◽  
Liyuan Shi ◽  
...  
Keyword(s):  
Social Welfare ◽  
High Intensity ◽  
Emission Reduction ◽  
Stable Equilibrium Point ◽  
Simulation Research ◽  
Paper Making ◽  
Reduction Strategies ◽  
Punishment Mechanism ◽  
Emission Reduction Strategies ◽  
Reward And Punishment

Environmental pollution has become an important obstacle on the path of ecological civilization construction, and it is urgent to control environmental pollution. By establishing an evolutionary game model, this thesis focuses on analyzing how paper-making enterprises choose their own emission reduction strategies under the reward and punishment mechanism. It further analyzes how social welfare changes under the reward and punishment mechanism, and finally through simulation research, this thesis analyzes the evolutionary paths of paper-making enterprises’ pollution emission strategies under the reward and punishment mechanism. The results of the reward and punishment mechanism are as follows: under the static reward and punishment mechanism, the game system will repeatedly oscillate around a point. There is no stable equilibrium point at this time. However, under the dynamic reward and punishment mechanism, the game system will tend to a stable equilibrium point. The results of social welfare analysis show that high-intensity rewards will reduce the amount of pollution discharged by paper-making enterprises, thereby maximizing social welfare. On the contrary, when paper-making enterprises discharge a large amount of pollution, they will be subject to high-intensity penalties. When facing high-intensity punishments, paper-making enterprises will tend to not to discharge. So social welfare is also maximized. The simulation research results show that reasonable punishment strategies are more effective than reward ones. Based on this, the author proposes countermeasures, such as establishing a reasonable reward and punishment mechanism, reasonably determining the reward and punishment intensity for polluting enterprises. The emission reduction strategies of paper-making enterprises will be affected by the government’s reward and punishment mechanism. A deep study of its internal mechanism is not only of great significance for pollution control but also of great significance for the development of a green economy.

scholarly journals Energy Use Efficiency Past-to-Future Evaluation: An International Comparison

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3804 ◽  
Author(s):  
Chia-Nan Wang ◽  
Thi-Duong Nguyen ◽  
Min-Chun Yu
Keyword(s):  
United States ◽  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Demand ◽  
Energy Use ◽  
The United States ◽  
Total Energy Consumption ◽  
The Future ◽  
The Status ◽  
Energy Efficiency Evaluation

Despite the many benefits that energy consumption brings to the economy, consuming energy also leads nations to expend more resources on environmental pollution. Therefore, energy efficiency has been proposed as a solution to improve national economic competitiveness and sustainability. However, the growth in energy demand is accelerating while policy efforts to boost energy efficiency are slowing. To solve this problem, the efficiency gains in countries where energy consumption efficiency is of the greatest concern such as China, India, the United States, and Europe, especially, emerging economies, is central. Additionally, governments must take greater policy actions. Therefore, this paper studied 25 countries from Asia, the Americas, and Europe to develop a method combining the grey method (GM) and data envelopment analysis (DEA) slack-based measure model (SMB) to measure and forecast the energy efficiency, so that detailed energy efficiency evaluation can be made from the past to the future; moreover, this method can be extended to more countries around the world. The results of this study reveal that European countries have a higher energy efficiency than countries in Americas (except the United States) and Asian countries. Our findings also show that an excess of total energy consumption is the main reason causing the energy inefficiency in most countries. This study contributes to policymaking and strategy makers by sharing the understanding of the status of energy efficiency and providing insights for the future.

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