Evaluation of a high temperature solar thermal seasonal borehole storage

A solar thermal system with seasonal borehole storage for heating of a residential area in Anneberg, Sweden, approximately 10 km north of Stockholm, has been in operation since late 2002. Originally, the project was part of the EU THERMIE project “Large-scale Solar Heating Systems for Housing Developments” (REB/0061/97) and was the first solar heating plant in Europe with borehole storage in rock not utilizing a heat pump. Earlier evaluations of the system show lower performance than the preliminary simulation study, with residents complaining of a high use of electricity for domestic hot water (DHW) preparation and auxiliary heating. One explanation mentioned in the earlier evaluations is that the borehole storage had not yet reached “steady state” temperatures at the time of evaluation. Many years have passed since then and this paper presents results from a new evaluation. The main aim of this work is to evaluate the current performance of the system based on several key figures, as well as on system function based on available measurement data. The analysis show that though the borehole storage now has reached a quasi-steady state and operates as intended, the auxiliary electricity consumption is much higher than the original design values largely due to high losses in the distribution network, higher heat loads as well as lower solar gains.

Testing Seasonal Unit Roots in Data at Any Frequency, an HEGY approach

This paper generalizes the HEGY-type test to detect seasonal unit roots in data at any frequency, based on the seasonal unit root tests in univariate time series by Hylleberg, Engle, Granger and Yoo (1990). We introduce the seasonal unit roots at first, and then derive the mechanism of the HEGY-type test for data with any frequency. Thereafter we provide the asymptotic distributions of our test statistics when different test regressions are employed. We find that the F-statistics for testing conjugation unit roots have the same asymptotic distributions. Then we compute the finite-sample and asymptotic critical values for daily and hourly data by a Monte Carlo method. The power and size properties of our test for hourly data is investigated, and we find that including lag augmentations in auxiliary regression without lag elimination have the smallest size distortion and tests with seasonal dummies included in auxiliary regression have more power than the tests without seasonal dummies. At last we apply the our test to hourly wind power production data in Sweden and shows there are no seasonal unit roots in the series.

Testing for Seasonal Unit Roots when Residuals Contain Serial Correlations under HEGY Test Framework

This paper introduces a corrected test statistic for testing seasonal unit roots when residuals contain serial correlations, based on the HEGY test proposed by Hylleberg,Engle, Granger and Yoo (1990). The serial correlations in the residuals of test regressionare accommodated by making corrections to the commonly used HEGY t statistics. Theasymptotic distributions of the corrected t statistics are free from nuisance parameters.The size and power properties of the corrected statistics for quarterly and montly data are investigated. Based on our simulations, the corrected statistics for monthly data havemore power compared with the commonly used HEGY test statistics, but they also have size distortions when there are strong negative seasonal correlations in the residuals.

Estimation of Parameters in Random Effect Models with Incidence Matrix Uncertainty

Random effect models have been widely applied in many fields of research. However, models with uncertain design matrices for random effects have been little investigated before. In some applications with such problems, an expectation method has been used for simplicity. This method does not include the extra information of uncertainty in the design matrix is not included. The closed solution for this problem is generally difficult to attain. We therefore propose an two-step algorithm for estimating the parameters, especially the variance components in the model. The implementation is based on Monte Carlo approximation and a Newton-Raphson-based EM algorithm. As an example, a simulated genetics dataset was analyzed. The results showed that the proportion of the total variance explained by the random effects was accurately estimated, which was highly underestimated by the expectation method. By introducing heuristic search and optimization methods, the algorithm can possibly be developed to infer the 'model-based' best design matrix and the corresponding best estimates.

Association between levels of pentraxin 3 and incidence of chronic kidney disease in the elderly

OBJECTIVE: Higher levels of the novel inflammatory marker pentraxin 3 (PTX3) predict cardiovascular mortality in patients with chronic kidney disease (CKD). Yet, whether PTX3 predicts worsening of kidney function has been less well studied. We therefore investigated the associations between PTX3 levels, kidney disease measures and CKD incidence. METHODS: Cross-sectional associations between serum PTX3 levels, urinary albumin/creatinine ratio (ACR) and cystatin C-estimated glomerular filtration rate (GFR) were assessed in two independent community-based cohorts of elderly subjects: the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS, n = 768, 51% women, mean age 75 years) and the Uppsala Longitudinal Study of Adult Men (ULSAM, n = 651, mean age 77 years). The longitudinal association between PTX3 level at baseline and incident CKD (GFR <60 mL( ) min(-1)  1.73 m(-) ²) was also analysed (number of events/number at risk: PIVUS 229/746, ULSAM 206/315). RESULTS: PTX3 levels were inversely associated with GFR [PIVUS: B-coefficient per 1 SD increase -0.16, 95% confidence interval (CI) -0.23 to -0.10, P < 0.001; ULSAM: B-coefficient per 1 SD increase -0.09, 95% CI -0.16 to -0.01, P < 0.05], but not ACR, after adjusting for age, gender, C-reactive protein and prevalent cardiovascular disease in cross-sectional analyses. In longitudinal analyses, PTX3 levels predicted incident CKD after 5 years in both cohorts [PIVUS: multivariable odds ratio (OR) 1.21, 95% CI 1.01-1.45, P < 0.05; ULSAM: multivariable OR 1.37, 95% CI 1.07-1.77, P < 0.05]. CONCLUSIONS: Higher PTX3 levels are associated with lower GFR and independently predict incident CKD in elderly men and women. Our data confirm and extend previous evidence suggesting that inflammatory processes are activated in the early stages of CKD and drive impairment of kidney function. Circulating PTX3 appears to be a promising biomarker of kidney disease.