scholarly journals Assessment of three solar-assisted heat pump typologies in Canada: parallel, series, and ice storage

2021 ◽  
Vol 246 ◽  
pp. 06006
Author(s):  
Benjamin Beauchamp ◽  
Sébastien Brideau ◽  
Cynthia Cruickshank
Keyword(s):  
Heat Pump ◽  
Energy Savings ◽  
Operating Costs ◽  
Future Research ◽  
Ice Storage ◽  
Energy Modelling ◽  
Detached House ◽  
High Level ◽  
Series Systems ◽  
Level Analysis

This paper discusses the energy savings, operating costs, and net present values of three typologies of solar assisted heat pump in Canada: parallel systems, series systems, and ice storage systems. Typologies are evaluated for three detached house archetypes of varying energy performances, and across a variety of Canadian climates. Hourly energy modelling is accomplished with a custom spreadsheet tool. The models developed are approximate and meant for high level analysis. This work is meant as a first step in a process of verifying the potential for each of the typologies. In most cases, the parallel system performs best in terms of annual energy savings. The paper goes over the models, assumptions, and some results. Recommendations are discussed for future research focusing on system payback times. The next step will consist of using a detailed sub-hourly simulation tool for the typology that has been found to be the most promising.

Power of Modified Brown-Forsythe and Mixed-Model Approaches in Split-Plot Designs

Methodology ◽  
2017 ◽  
Vol 13 (1) ◽  
pp. 9-22 ◽  
Author(s):  
Pablo Livacic-Rojas ◽  
Guillermo Vallejo ◽  
Paula Fernández ◽  
Ellián Tuero-Herrero
Keyword(s):  
Repeated Measures ◽  
Statistical Power ◽  
Mixed Model ◽  
Covariance Structure ◽  
Simulation Method ◽  
Future Research ◽  
Repeated Measures Design ◽  
Fixed And Random Effects ◽  
Split Plot ◽  
High Level

Abstract. Low precision of the inferences of data analyzed with univariate or multivariate models of the Analysis of Variance (ANOVA) in repeated-measures design is associated to the absence of normality distribution of data, nonspherical covariance structures and free variation of the variance and covariance, the lack of knowledge of the error structure underlying the data, and the wrong choice of covariance structure from different selectors. In this study, levels of statistical power presented the Modified Brown Forsythe (MBF) and two procedures with the Mixed-Model Approaches (the Akaike’s Criterion, the Correctly Identified Model [CIM]) are compared. The data were analyzed using Monte Carlo simulation method with the statistical package SAS 9.2, a split-plot design, and considering six manipulated variables. The results show that the procedures exhibit high statistical power levels for within and interactional effects, and moderate and low levels for the between-groups effects under the different conditions analyzed. For the latter, only the Modified Brown Forsythe shows high level of power mainly for groups with 30 cases and Unstructured (UN) and Autoregressive Heterogeneity (ARH) matrices. For this reason, we recommend using this procedure since it exhibits higher levels of power for all effects and does not require a matrix type that underlies the structure of the data. Future research needs to be done in order to compare the power with corrected selectors using single-level and multilevel designs for fixed and random effects.

Saving Primary Energy Consumption Through Exergy Analysis of Combine Distillation and Power Plant

2012 ◽  
Vol 9 (2) ◽  
pp. 65
Author(s):  
Alhassan Salami Tijani ◽  
Nazri Mohammed ◽  
Werner Witt
Keyword(s):  
Energy Consumption ◽  
Power Plant ◽  
Heat Pump ◽  
Heat Recovery ◽  
Energy Savings ◽  
Primary Energy ◽  
Heat Pumps ◽  
Saturated Steam ◽  
Distillation Unit ◽  
Primary Energy Consumption

Industrial heat pumps are heat-recovery systems that allow the temperature ofwaste-heat stream to be increased to a higher, more efficient temperature. Consequently, heat pumps can improve energy efficiency in industrial processes as well as energy savings when conventional passive-heat recovery is not possible. In this paper, possible ways of saving energy in the chemical industry are considered, the objective is to reduce the primary energy (such as coal) consumption of power plant. Particularly the thermodynamic analyses ofintegrating backpressure turbine ofa power plant with distillation units have been considered. Some practical examples such as conventional distillation unit and heat pump are used as a means of reducing primary energy consumption with tangible indications of energy savings. The heat pump distillation is operated via electrical power from the power plant. The exergy efficiency ofthe primary fuel is calculated for different operating range ofthe heat pump distillation. This is then compared with a conventional distillation unit that depends on saturated steam from a power plant as the source of energy. The results obtained show that heat pump distillation is an economic way to save energy if the temperaturedifference between the overhead and the bottom is small. Based on the result, the energy saved by the application of a heat pump distillation is improved compared to conventional distillation unit.

COVID-19 Outbreak Prediction with Machine Learning

2020 ◽  
Author(s):  
Sina Faizollahzadeh Ardabili ◽  
Amir Mosavi ◽  
Pedram Ghamisi ◽  
Filip Ferdinand ◽  
Annamaria R. Varkonyi-Koczy ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Fuzzy Inference ◽  
Control Measures ◽  
Future Research ◽  
Complex Nature ◽  
Inference System ◽  
Wide Range ◽  
Standard Models ◽  
High Level

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and they are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models needs to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak as an alternative to SIR and SEIR models. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP, and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research. Paper further suggests that real novelty in outbreak prediction can be realized through integrating machine learning and SEIR models.

scholarly journals Monitoring the technological processes in the wood industry in order to make them more efficient through technical overhauling

2019 ◽  
Vol 290 ◽  
pp. 02007
Author(s):  
Radu Dan Paltan ◽  
Cristina Biriş ◽  
Loredana Anne-Marie Rădulescu
Keyword(s):  
Automotive Industry ◽  
Operating Mode ◽  
Solid Wood ◽  
Production Costs ◽  
Operating Costs ◽  
Future Research ◽  
Wood Industry ◽  
Research Article ◽  
State Of Research ◽  
The Cost

Of many techniques that are used to optimize production and costs, the studies conducted within a profile company lead to our choice for testing the 6Sigma method (the most used method in the automotive industry) in view of the economic efficiency applied in the wood Industry company. This method measures how many flaws exist in a process and determines in a systematic way how to improve it by technical overhauling and eliminating or minimizing the process for efficiency. This research article aims to study the state of research on the optimization of the production process through technical overhauling for panels reconstituted from solid wood and ways to make production more efficient by cutting costs through technical overhauling. From preliminary research, we estimate that all the items founded and others that will result from further research will result in a significant decrease in production costs that are reflected in the cost of the finished product and consequently in increasing the yield of the company by maximizing its profit. At the same time it may be the basis of future research studies in the field. The easier it is to maximize profits, the lower the operating costs are and the higher recovery rate of investments are, that will result a change in the operating mode: “working smarter not harder”.

scholarly journals Opportunities and Challenges of Green-Lean: An Integrated System for Sustainable Construction

2020 ◽  
Vol 12 (11) ◽  
pp. 4460 ◽  
Author(s):  
Mohammadsoroush Tafazzoli ◽  
Ehsan Mousavi ◽  
Sharareh Kermanshachi
Keyword(s):  
Cost Savings ◽  
Integrated Approach ◽  
Integrated System ◽  
Waste Minimization ◽  
Sustainable Construction ◽  
Future Research ◽  
Safety Improvement ◽  
The Individual ◽  
High Level ◽  
Industry Professionals

Although the two concepts of lean and sustainable construction have been developed due to different incentives, and they do not pursue the same exact goals, there exists considerable commonality between them. This paper discusses the potentials for integrating the two approaches and their practices and how the resulting synergy from combining the two methods can potentially lead to higher levels of fulfilling the individual goals of each of them. Some limitations and challenges to implementing the integrated approach are also discussed. Based on a comprehensive review of existing papers related to sustainable and lean construction topics, the commonality between the two approaches is discussed and grouped in five categories of (1) cost savings, (2) waste minimization, (3) Jobsite safety improvement, (4) reduced energy consumption, and (5) customers’ satisfaction improvement. The challenges of this integration are similarly identified and discussed in the four main categories of (1) additional initial costs to the project, (2) difficulty of providing specialized expertise, (3) contractors’ unwillingness to adopt the additional requirements, and (4) challenges to establish a high level of teamwork. Industry professionals were then interviewed to rank the elements in each of the two categories of opportunities and challenges. The results of the study highlight how future research can pursue the development of a new Green-Lean approach by investing in the communalities and meeting the challenges of this integration.

scholarly journals Time Granularity Impact on Propagation of Disruptions in a System-of-Systems Simulation of Infrastructure and Business Networks

2021 ◽  
Vol 18 (8) ◽  
pp. 3922
Author(s):  
Mateusz Iwo Dubaniowski ◽  
Hans Rudolf Heinimann
Keyword(s):  
Recovery Time ◽  
System Of Systems ◽  
Future Research ◽  
Business Networks ◽  
Simulation Experiments ◽  
Huge Impact ◽  
High Level ◽  
Systems Simulation ◽  
Different Characteristics ◽  
The Impact

A system-of-systems (SoS) approach is often used for simulating disruptions to business and infrastructure system networks allowing for integration of several models into one simulation. However, the integration is frequently challenging as each system is designed individually with different characteristics, such as time granularity. Understanding the impact of time granularity on propagation of disruptions between businesses and infrastructure systems and finding the appropriate granularity for the SoS simulation remain as major challenges. To tackle these, we explore how time granularity, recovery time, and disruption size affect the propagation of disruptions between constituent systems of an SoS simulation. To address this issue, we developed a high level architecture (HLA) simulation of three networks and performed a series of simulation experiments. Our results revealed that time granularity and especially recovery time have huge impact on propagation of disruptions. Consequently, we developed a model for selecting an appropriate time granularity for an SoS simulation based on expected recovery time. Our simulation experiments show that time granularity should be less than 1.13 of expected recovery time. We identified some areas for future research centered around extending the experimental factors space.

scholarly journals A Review on Thermal Energy Modelling for Optimal Microgrids Management

Thermo ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 63-76
Author(s):  
Mengxuan Yan ◽  
Dongxiao Wang ◽  
Chun Sing Lai ◽  
Loi Lei Lai
Keyword(s):  
Energy Management ◽  
Thermal Energy ◽  
Critical Role ◽  
Distribution Networks ◽  
Energy Resources ◽  
Future Research ◽  
Renewable Energy Resources ◽  
Energy Modelling ◽  
Microgrid Energy Management ◽  
Combined Cooling

Microgrids have become increasingly popular in recent years due to technological improvements, growing recognition of their benefits, and diminishing costs. By clustering distributed energy resources, microgrids can effectively integrate renewable energy resources in distribution networks and satisfy end-user demands, thus playing a critical role in transforming the existing power grid to a future smart grid. There are many existing research and review works on microgrids. However, the thermal energy modelling in optimal microgrid management is seldom discussed in the current literature. To address this research gap, this paper presents a detailed review on the thermal energy modelling application on the optimal energy management for microgrids. This review firstly presents microgrid characteristics. Afterwards, the existing thermal energy modeling utilized in microgrids will be discussed, including the application of a combined cooling, heating and power (CCHP) and thermal comfort model to form virtual energy storage systems. Current trial programs of thermal energy modelling for microgrid energy management are analyzed and some challenges and future research directions are discussed at the end. This paper serves as a comprehensive review to the most up-to-date thermal energy modelling applications on microgrid energy management.

More than carrots and sticks: Economic statecraft and coercion in China–Taiwan relations from 2000 to 2019

Politics ◽  
2021 ◽  
pp. 026339572096265
Author(s):  
Christina Lai
Keyword(s):  
Public Awareness ◽  
Theoretical Development ◽  
Future Research ◽  
Asian Countries ◽  
Power Asymmetry ◽  
Economic Statecraft ◽  
Trading Partners ◽  
Economic Coercion ◽  
Chinese Group ◽  
Level Analysis

China has become one of the most important trading partners for many Asian countries, and Taiwan is at the forefront of China’s economic coercion. It also leads to the following empirical puzzle: When can Beijing’s economic sanctions and incentives achieve their desired outcomes? Why and how do they often fail? Given the power asymmetry between China and Taiwan, how Taiwan resists China’s coercive measures contributes significantly to theoretical development in international relations. Taiwan has responded to Chinese economic pressure by diversifying its trade with and investment in Southeast Asian and South Asian countries to lessen dependence on China. It also securitizes China–Taiwan relations by raising public awareness about over-reliance on China’s market. Taiwan is not only a target of China’s coercion, but an active actor in its own right as well. This article re-evaluates the literature on East Asian politics and economic statecraft. First, it highlights the salience of power asymmetry to the field of economic statecraft. Second, it offers a three-level analysis of when and how China exercised economic coercion and incentives towards Taiwan. Third, it examines how Taiwan addressed Beijing’s sanctions on Chinese group tourists starting in 2016. The final section discusses some conclusions that can be drawn and suggests some avenues for future research.

scholarly journals The use of nocturnal flights for barrier crossing in a diurnally migrating songbird

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Christie D. Lavallée ◽  
Saeedeh Bani Assadi ◽  
Alicia M. Korpach ◽  
James D. Ray ◽  
Jason D. Fischer ◽  
...  
Keyword(s):  
Energy Savings ◽  
Open Water ◽  
Gps Tracking ◽  
Future Research ◽  
Barrier Crossing ◽  
Migration Patterns ◽  
Migration Strategies ◽  
Diurnal Migrant ◽  
Time And Energy ◽  
High Degree

Abstract Background The migration patterns of land birds can generally be divided into those species that migrate principally during the day and those that migrate during the night. Some species may show individual plasticity in the use of day or night flight, particularly when crossing large, open-water or desert barriers. However, individual plasticity in circadian patterns of migratory flights in diurnally migrating songbirds has never been investigated. Methods We used high precision GPS tracking of a diurnal, migratory swallow, the purple martin (Progne subis), to determine whether individuals were flexible in their spring migration strategies to include some night flight, particularly at barrier crossing. Results Most (91%) of individuals made large (sometimes > 1000 km), open-water crossings of the Caribbean Sea and the Gulf of Mexico that included the use of night flight. 32% of all water crossings were initiated at night, demonstrating that night flight is not only used to complete large crossings but may confer other advantages for diurnal birds. Birds were not more likely to initiate crossings with supportive winds, however crossings were more likely when they reduced travel distances. Our results are consistent with diurnal birds using night flight to help achieve time- and energy-savings through ‘short cuts’ at barrier crossings, at times and locations when foraging opportunities are not available. Conclusions Overall, our results demonstrate the use of nocturnal flight and a high degree of individual plasticity in migration strategies on a circadian scale in a species generally considered to be a diurnal migrant. Nocturnal flights at barrier crossing may provide time and energy savings where foraging opportunities are low in an otherwise diurnal strategy. Future research should target how diel foraging and refueling strategies support nocturnal flights and barrier crossing in this and other diurnal species.

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