A CONCEPTUAL FRAMEWORK FOR DELIVERING SUSTAINABLE BUILDING ENERGY EFFICENCY RETROFIT USING THE ENERGY PERFORMANCE CONTRACTING(EPC)IN CHINA

Sustainable building has become a future development trend in the building sector.Building Energy Efficiency Retrofit(BEER)provides excellent opportunities to reduce energy consumption in existing buildings,and to promote environmental protection,the rational use of resources,occupants’health,all of which helps to improve the sustainability of existing buildings.Energy Performance Contracting(EPC)provided by Energy Service Companies(ESCOs)is a market mechanism to provide financial and technological support for energy efficiency projects.This paper aims to develop a sustainability promotion framework for BEER projects under the EPC mechanism to link the sustainable performance of BEER with the success factors of this EPC mechanism.Different types of building have different energy consumption characteristics.This research focuses on hotel buildings in China.The paper develops a framework for sustainable BEER through an EPC mechanism in hotel buildings based on the EFQM Excellence Model for business quality management.Interviews were conducted with experts from the hotel industry,from energy service companies and with academics.Based on the developed framework,the study has identified 11 performance indicators for sustainable BEER and 28 success factors of an EPC mechanism.This provides significant groundwork for future study in developing an assessment model to evaluate the sustainability of BEER projects.

On construction waste disposal in Chongqing

With rapid development of the construction industry in China, lots of construction materials are being widely reused. Meanwhile, more and more materials for building remover or demolition enter into the environment as a result. However, China is facing big building garbage pollution, with simple disposal methods and low efficiency, which urgently needs to be improved. The paper takes Chongqing as an example to illustrate existing problems in this field and then puts forward corresponding countermeasures from the aspects of economy, technology, management and policy, aiming at enhancing the level of construction waste disposal in China.

Financing constraints and corporate investment:an empirical analysis of china’s manufacturing firms

With the measurement of dividend payout ratio, logistic regression index value and the firm size financing constraints, this paper investigated the investment behavior of China’s manufacturing firms over the period from 1998 to 2003, and the relationship between financing constraints and corporate investment using the OLS regression method. The empirical evidence shows that there are certain extent financing constraints in China’s manufacturing firms, but the results are different with different variables to measure the financing constraints.

Using Data Mining Techniques to Support Value Management Workshops in Construction

Problem-solving processes in value management （VM） workshops in the construction industry are experience-based, and the quality of these workshops depends very much on the experience of the team members. The efficiency and effectiveness of VM workshops can be improved by better reusing the experi- ence of previous VM cases and field knowledge. This paper describes a new approach to facilitate VM workshops in the construction industry using data mining （DM） techniques. The feasibility of integrating DM techniques with VM workshops in the construction industry is demonstrated in case studies. Examples are presented to illustrate different methods of applying DM tools in VM workshops. The results show that DM techniques can help team members in VM workshops to understand their problems more clearly and to generate more ideas for current problems.

Real Estate in Chongqing as a Pillar Industry: A Quantitative Analysis

The definition of pillar industry is stated and its indicators, including the proportion of added value in the GDP, the degree of industry correlation, the income elasticity of demand, and the growth rate of employment will be discussed. And then index weighing is determined based on the degree of importance. The result of the quantitative analysis of real estate industry in Chongqing suggests that its first three evaluating indicators live up to the index requirement of a pillar industry while its degree of industry correlation is not satisfactory. An overall evaluation indicates that the real estate industry in Chongqing meets the requirements of pillar industry.

Efficacy of weight adjusted bone mineral content in osteoporosis diagnosis in Chinese female population

Background:Areal bone mineral density(aBMD)applied for osteoporosis diagnosis unavoidably results in the missingdiagnosis in patients with large bones and misdiagnosis in those with small bones.Therefore,we try to find a new adjusted index of bone mineral content(BMC)to make up shortcomings of aBMD in osteoporosis diagnosis.Methods:In this multi-center epidemiological study,BMC and aBMD of lumbar spines(n=5510)and proximal femurs(n=4710)were measured with dual energy X-ray absorptiometry(DXA).We analyzed the correlation between the bone mass and body weight in all subjects including four age groups(<19 years,20-39 years,40-49 years,>50 years).And then the body weight was used for standardizing BMC(named wBMC)and applied for the epidemiological analysis of osteoporosis?Results:The correlation of body weight and BMC is 0.839 to 0.931 of lumbar vertebra 1-4(Li_4),and 0.71 to 0.95 of femoral neck in different age groups.When aBMD was applied for diagnosing osteoporosis,the prevalence was 7.55%,16.39%,and 25.83%in patients with a high,intermediate,and low body weight respectively.However,the prevalence was 21.8%,18.03%,and 11.64%by wBMC applied for diagnosing osteoporosis.Moreover,the prevalence of osteoporosis increased by 3.76%by wBMC with the body weight increased by 5 kg.The prevalence decreased by 1.94%when the body weight decreased by 5 kg.Conclusions:wBMC can reduce the missed diagnosis in patients with large body weight and reduce misdiagnosis in those with small body weight.Including children,wBMC may be feasible for osteoporosis diagnosis individuals at any age.

Improving the Performance of DC Microgrids by Utilizing Adaptive Takagi-Sugeno Model Predictive Control

In naval direct current(DC)microgrids,pulsed power loads(PPLs)are becoming more prominent.A solar sys-tem,an energy storage system,and a pulse load coupled directly to the DC bus compose a DC microgrid in this study.For DC mi-crogrids equipped with sonar,radar,and other sensors,pulse load research is crucial.Due to high pulse loads,there is a possibility of severe power pulsation and voltage loss.The original contribution of this paper is that we are able to address the nonlinear problem by applying the Takagi-Sugeno(TS)model formulation for naval DC microgrids.Additionally,we provide a nonlinear power observer for estimating major disturbances affecting DC microgrids.To demonstrate the TS-potential,we examine three approaches for mitigating their negative effects:instantaneous power control(IPC)control,model predictive control(MPC)formulation,and TS-MPC approach with compensated PPLs.The results reveal that the TS-MPC approach with adjusted PPLs effectively shares power and regulates bus voltage under a variety of load conditions,while greatly decreasing detrimental impacts of the pulse load.Additionally,the comparison confirmed the efficiency of this technique.Index Terms-DC microgrids(MG),model predictive control(MPC),pulsed power loads(PPLs),nonlinear power observer,Takagi-Sugeno(TS)fuzzy model.

Correlation Functions of an Autonomous Stochastic System with Nonlinear Time Delays

The auto-correlation function and the cross-correlation of an autonomous stochastic system with nonlinear time-delayed feedback are investigated by using the stochastic simulation method. There are prominent differences be- tween the roles of quadratic time-delayed feedback and cubic time-delayed feedback on the correlations of an autonomous stochastic system. Under quadratic time-delayed feedback, the nonlinear time delay fails to improve the noisy state of the autonomous stochastic system, the auto-correlation decreases monotonously to zero, and the cross-correlation increases monotonously to zero with the decay time. Under cubic time-delayed feedback, the nonlinear time delay can improve the noisy state of the autonomous stochastic system; the auto-correlation and the cross-correlation show periodical oscillation and attenuation, finally tending to zero with the decay time. Comparing the correlations of the system between with nonfinear time-delayed feedback and linear time-delayed feedback, we find that nonlinear time-delayed feedback lowers the correlation strength of the autonomous stochastic system.

Hybrid SDS and WPT-IBBO-DNM Based Model for Ultra-short Term Photovoltaic Prediction

Accurate photovoltaic(PV)power prediction has been a subject of ongoing study in order to address grid stability concerns caused by PV output unpredictability and intermittency.This paper proposes an ultra-short-term hybrid photovoltaic power forecasting method based on a dendritic neural model(DNM)in this paper.This model is trained using improved biogeography-based optimization(IBBO),a technique that incorporates a domestication operation to increase the performance of classical biogeography-based optimization(BBO).To be more precise,a similar day selection(SDS)technique is presented for selecting the training set,and wavelet packet transform(WPT)is used to divide the input data into many components.IBBO is then used to train DNM weights and thresholds for each component prediction.Finally,each component’s prediction results are stacked and reassembled.The suggested hybrid model is used to forecast PV power under various weather conditions using data from the Desert Knowledge Australia Solar Centre(DKASC)in Alice Springs.Simulation results indicate the proposed hybrid SDS and WPT-IBBO-DNM model has the lowest error of any of the benchmark models and hence has the potential to considerably enhance the accuracy of solar power forecasting(PVPF).