The impact of two-stage discharging on the exergoeconomic performance of a storage-type domestic water-heater

Energy ◽  
2015 ◽  
Vol 83 ◽  
pp. 379-386 ◽  
Author(s):  
U. Atikol ◽  
L.B.Y. Aldabbagh
Keyword(s):  
Water Heater ◽  
Domestic Water ◽  
Two Stage ◽  
The Impact ◽  
Storage Type

scholarly journals Robust Inferences from a Before-and-After Study with Multiple Unaffected Control Groups

2013 ◽  
Vol 1 (2) ◽  
pp. 209-234 ◽  
Author(s):  
Pengyuan Wang ◽  
Mikhail Traskin ◽  
Dylan S. Small
Keyword(s):  
Sensitivity Analysis ◽  
Control Groups ◽  
Two Stage ◽  
Time Effects ◽  
Unaffected Control ◽  
Group Time ◽  
Before And After ◽  
Group Variation ◽  
The Impact ◽  
Before And After Study

AbstractThe before-and-after study with multiple unaffected control groups is widely applied to study treatment effects. The current methods usually assume that the control groups’ differences between the before and after periods, i.e. the group time effects, follow a normal distribution. However, there is usually no strong a priori evidence for the normality assumption, and there are not enough control groups to check the assumption. We propose to use a flexible skew-t distribution family to model group time effects, and consider a range of plausible skew-t distributions. Based on the skew-t distribution assumption, we propose a robust-t method to guarantee nominal significance level under a wide range of skew-t distributions, and hence make the inference robust to misspecification of the distribution of group time effects. We also propose a two-stage approach, which has lower power compared to the robust-t method, but provides an opportunity to conduct sensitivity analysis. Hence, the overall method of analysis is to use the robust-t method to test for the overall hypothesized range of shapes of group variation; if the test fails to reject, use the two-stage method to conduct a sensitivity analysis to see if there is a subset of group variation parameters for which we can be confident that there is a treatment effect. We apply the proposed methods to two datasets. One dataset is from the Current Population Survey (CPS) to study the impact of the Mariel Boatlift on Miami unemployment rates between 1979 and 1982.The other dataset contains the student enrollment and grade repeating data in West Germany in the 1960s with which we study the impact of the short school year in 1966–1967 on grade repeating rates.

scholarly journals Optimization of Two-Stage IPD-(1+I) Controllers for Frequency Regulation of Sustainable Energy Based Hybrid Microgrid Network

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 919
Author(s):  
Abdul Latif ◽  
S. M. Suhail Hussain ◽  
Dulal Chandra Das ◽  
Taha Selim Ustun
Keyword(s):  
Sustainable Energy ◽  
Research Field ◽  
Optimization Techniques ◽  
Frequency Regulation ◽  
Water Heater ◽  
Two Stage ◽  
Domain Specific ◽  
Hybrid Microgrid ◽  
Main Challenge ◽  
Algorithmic Technique

Sustainable energy based hybrid microgrids are advantageous in meeting constantly increasing energy demands. Conversely, the intermittent nature of renewable sources represents the main challenge to achieving a reliable supply. Hence, load frequency regulation by adjusting the amount of power shared between subsystems is considered as a promising research field. Therefore, this paper presents a new stratagem for frequency regulation by developing a novel two stage integral-proportional-derivative with one plus integral (IPD-(1+I)) controller for multi sources islanded microgrid system (MS-IμGS). The proposed stratagem has been tested in an MS-IμGS comprising of a wind turbine, parabolic trough, biodiesel generators, solid-oxide fuel cell, and electric water heater. The proposed model under different scenarios is simulated in MATLAB environment considering the real-time recorded wind data. A recently developed sine-cosine algorithmic technique (SCA) has been leveraged for optimal regulation of frequency in the considered microgrid. To identify the supremacy of the proposed technique, comparative studies with other classical controllers with different optimization techniques have been performed. From the comparison, it is clearly evident that, SCA-(IPD-(1+I)) controller gives better performance over other considered stratagems in terms of various time domain specific parameters, such as peak deviations (overshoot, undershoot) and settling time. Finally, the robustness of the proposed stratagem is evaluated by conducting sensitivity analysis under ±30% parametric variations and +30% load demand. The lab tests results validate the operation of the proposed system and show that it can be used to regulate the frequency in stand-alone microgrids with a high penetration of renewable energy.

scholarly journals A Two-Stage Joint Model for Nonlinear Longitudinal Response and a Time-to-Event with Application in Transplantation Studies

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Magdalena Murawska ◽  
Dimitris Rizopoulos ◽  
Emmanuel Lesaffre
Keyword(s):  
Empirical Bayes ◽  
Cox Model ◽  
Data Sets ◽  
Two Stage ◽  
Nonlinear Mixed Effects Model ◽  
Resistance Evolution ◽  
Longitudinal Response ◽  
Longitudinal Measurements ◽  
Subject Specific ◽  
The Impact

In transplantation studies, often longitudinal measurements are collected for important markers prior to the actual transplantation. Using only the last available measurement as a baseline covariate in a survival model for the time to graft failure discards the whole longitudinal evolution. We propose a two-stage approach to handle this type of data sets using all available information. At the first stage, we summarize the longitudinal information with nonlinear mixed-effects model, and at the second stage, we include the Empirical Bayes estimates of the subject-specific parameters as predictors in the Cox model for the time to allograft failure. To take into account that the estimated subject-specific parameters are included in the model, we use a Monte Carlo approach and sample from the posterior distribution of the random effects given the observed data. Our proposal is exemplified on a study of the impact of renal resistance evolution on the graft survival.

Effect of female executives on Chinese cultural media enterprise efficiency

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ying Li ◽  
Yung-Ho Chiu ◽  
Tai-Yu Lin ◽  
Hongyi Cen
Keyword(s):  
Boards Of Directors ◽  
Company Performance ◽  
Tobit Regression ◽  
Female Executives ◽  
Two Stage ◽  
Content Type ◽  
Female Directors ◽  
The Impact ◽  
Cultural Media ◽  
Better Than

Purpose As more women are now being appointed to senior and top management positions and invited to sit on boards of directors, they are now directly participating in strategic company decision-making. As female directors have been found to provide new ideas, increase company competitiveness, efficiency and performance and bring a greater number of external resources to a company than male directors, this paper aims to put female directors as a variable into the data envelopment analysis (DEA) and statistical models to explore the effect of female directors on operating performances. The DEA first quantified and measured the company efficiencies, after which the statistical model analyzed the correlations between the variables to specifically identify the impact of female decision makers on the operating efficiencies in state-owned and private enterprises. Design/methodology/approach A novel two-stage, meta-hybrid dynamic DEA was developed to explore Chinese cultural media company efficiencies under optimal input and output resource allocations, after which Tobit Regression was applied to determine the effect of female executives on these efficiencies. Findings From 2012 to 2016, the overall efficiencies in Chinese state-owned cultural media enterprises were better than in the private cultural media enterprises. The overall technology gaps (TGs) in the state-owned cultural media enterprises were better than in the private cultural media enterprises. Originality/value Previous research has tended to focus on the causal relationships between female senior executives and business performances; however, there have been few studies on the relationships between female executives and company performance from an efficiency perspective (optimal resource allocation). This paper, therefore, is the first to develop a novel two-stage, meta-hybrid dynamic DEA to examine Chinese cultural media enterprise efficiencies, and the first to apply Tobit Regression to assess the effect of female executives on those efficiencies.

A Novel Two-Stage Structural Damage Identification Method Based on Superposition of Modal Flexibility Curvature and Whale Optimization Algorithm

2021 ◽  
pp. 2150169
Author(s):  
Minshui Huang ◽  
Xihao Cheng ◽  
Zhigang Zhu ◽  
Jin Luo ◽  
Jianfeng Gu
Keyword(s):  
Optimization Algorithm ◽  
Damage Identification ◽  
Whale Optimization Algorithm ◽  
Two Stage ◽  
Simply Supported ◽  
Damage Location ◽  
Flexibility Matrix ◽  
Modal Flexibility ◽  
Whale Optimization ◽  
The Impact

A novel two-stage method is proposed to properly identify the location and severity of damage in plate structures. In the first stage, a superposition of modal flexibility curvature (SMFC) is adopted to locate the damage accurately, and the identification index of modal flexibility matrix is improved. The low-order modal parameters are used and a new column matrix is formed based on the modal flexibility matrix before and after the structure is damaged. The difference of modal flexibility matrix is obtained, which is used as a damage identification index. Meanwhile, based on SMFC, a method of weakening the “vicinity effect” is proposed to eliminate the impact of the surrounding elements to the damaged elements when damage identification is carried out for the plate-type structure. In the second stage, the objective function based on the flexibility matrix is constructed, and according to the damage location identified in the first stage, the actual damage severity is determined by the enhanced whale optimization algorithm (EWOA). In addition, the effects of 3% and 10% noise on damage location and severity estimation are also studied. By taking a simply supported beam and a four-side simply supported plate as examples, the results show that the method can accurately estimate the damage location and quantify the damage severity without noise. When considering noise, the increase of noise level will not affect the assessment of damage location, but the error of quantifying damage severity will increase. In addition, damage identification of a steel-concrete composite bridge (I-40 Bridge) under four damage cases is carried out, and the results show that the modified method can evaluate the damage location and quantify 5%–92% of the damage severity.

Benchmarking the efficiencies of Indonesia’s municipal water utilities using Stackelberg data envelopment analysis

2015 ◽  
Vol 22 (4) ◽  
pp. 588-609 ◽  
Author(s):  
Andreas Wibowo ◽  
Hans Wilhelm Alfen
Keyword(s):  
Data Envelopment Analysis ◽  
The Body ◽  
Water Utilities ◽  
Data Envelopment ◽  
Two Stage ◽  
Restrictive Assumption ◽  
Content Type ◽  
Second Stage ◽  
Municipal Water ◽  
The Impact

Purpose – The purpose of this paper is to present a yardstick efficiency comparison of 269 Indonesian municipal water utilities (MWUs) and measures the impact of exogenous environmental variables on efficiency scores. Design/methodology/approach – Two-stage Stackelberg leader-follower data envelopment analysis (DEA) and artificial neural networks (ANN) were employed. Findings – Given that serviceability was treated as the leader and profitability as the follower, the first and second stage DEA scores were 55 and 32 percent (0 percent = totally inefficient, 100 percent = perfectly efficient), respectively. This indicates sizeable opportunities for improvement, with 39 percent of the total sample facing serious problems in both first- and second-stage efficiencies. When profitability instead leads serviceability, this results in more decreased efficiency. The size of the population served was the most important exogenous environmental variable affecting DEA efficiency scores in both the first and second stages. Research limitations/implications – The present study was limited by the overly restrictive assumption that all MWUs operate at a constant-return-to-scale. Practical implications – These research findings will enable better management of the MWUs in question, allowing their current level of performance to be objectively compared with that of their peers, both in terms of scale and area of operation. These findings will also help the government prioritize assistance measures for MWUs that are suffering from acute performance gaps, and to devise a strategic national plan to revitalize Indonesia’s water sector. Originality/value – This paper enriches the body of knowledge by filling in knowledge gaps relating to benchmarking in Indonesia’s water industry, as well as in the application of ensemble two-stage DEA and ANN, which are still rare in the literature.

scholarly journals A Two-Stage Method to Determine Optimal Product Sampling considering Dynamic Potential Market

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Zhineng Hu ◽  
Wei Lu ◽  
Bing Han
Keyword(s):  
Impact Analysis ◽  
Negative Influence ◽  
Key Factors ◽  
Two Stage ◽  
Logistic Analysis ◽  
Potential Market ◽  
Dynamic Potential ◽  
Diffusion Effects ◽  
The Impact ◽  
Changing Rate

This paper develops an optimization model for the diffusion effects of free samples under dynamic changes in potential market based on the characteristics of independent product and presents a two-stage method to figure out the sampling level. The impact analysis of the key factors on the sampling level shows that the increase of the external coefficient or internal coefficient has a negative influence on the sampling level. And the changing rate of the potential market has no significant influence on the sampling level whereas the repeat purchase has a positive one. Using logistic analysis and regression analysis, the global sensitivity analysis gives a whole analysis of the interaction of all parameters, which provides a two-stage method to estimate the impact of the relevant parameters in the case of inaccuracy of the parameters and to be able to construct a 95% confidence interval for the predicted sampling level. Finally, the paper provides the operational steps to improve the accuracy of the parameter estimation and an innovational way to estimate the sampling level.

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