Cost-Effective Heating Control Approaches by Demand Response and Peak Demand Limiting in an Educational Office Building with District Heating

This study examined three different approaches to reduce the heating cost while maintaining indoor thermal comfort at acceptable levels in an educational office building, including decentralized (DDRC) and centralized demand response control (CDRR) and limiting peak demand. The results showed that although all these approaches did not affect the indoor air temperature significantly, the DDRC method could adjust the heating set point to between 20–24.5 °C. The DDRC approach reached heating cost savings of up to 5% while controlling space heating temperature without sacrificing the thermal comfort. The CDRC of space heating had limited potential in heating cost savings (1.5%), while the indoor air temperature was in the acceptable range. Both the DDRC and CDRC alternatives can keep the thermal comfort at good levels during the occupied time. Depending on the district heating provider, applying peak demand limiting of 35% can not only achieve 13.6% maximum total annual district heating cost saving but also maintain the thermal comfort level, while applying that of 43% can further save 16.9% of the cost, but with sacrificing a little thermal comfort. This study shows that demand response on heating energy only benefited from the decentralized control alternative, and the district heating-based peak demand limiting has significant potential for saving heating costs

Revealing the crystalline packing structure of Y6 in the active layer of organic solar cells: the critical role of solvent additives

The bulk heterojunction (BHJ) morphology of photovoltaic materials is crucial to the fundamental optoelectronic properties of organic solar cells (OSCs). However, in the photoactive layer, the intrinsic crystalline packing structure of Y6, currently the hallmark molecule among Y-series non-fullerene acceptors (NFAs), has not been unambiguously determined. Here, employing grazing-incidence wide-angle X-ray scattering (GIWAXS), we managed to uncover the intrinsic crystalline packing structure of Y6 in the BHJ active layer of OSCs, which is found to be different from its single-crystal structure reported previously. Moreover, we find that solvent additive 1-chloronaphthalene (CN) can induce highly ordered packing of Y6 in BHJ thin films. With the help of atomistic molecular dynamics simulations, it is revealed that π-π interactions generally exist between naphthalene derivatives and IC terminals of Y6 analogues, which would essentially improve their long-range ordering. Our work reveals the intrinsic crystalline packing structure of Y6 in the BHJ active layer as well as its crystallization mechanism in thin films, thus providing direct correlations between this crystalline packing and the device characteristics and photophysical properties.Knut och Alice Wallenbergs StiftelseImmediate accessThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

GWAS Identifies Novel Susceptibility Loci on 6p21.32 and 21q21.3 for Hepatocellular Carcinoma in Chronic Hepatitis B Virus Carriers

Genome-wide association studies (GWAS) have recently identified KIF1B as susceptibility locus for hepatitis B virus (HBV)–related hepatocellular carcinoma (HCC). To further identify novel susceptibility loci associated with HBV–related HCC and replicate the previously reported association, we performed a large three-stage GWAS in the Han Chinese population. 523,663 autosomal SNPs in 1,538 HBV–positive HCC patients and 1,465 chronic HBV carriers were genotyped for the discovery stage. Top candidate SNPs were genotyped in the initial validation samples of 2,112 HBV–positive HCC cases and 2,208 HBV carriers and then in the second validation samples of 1,021 cases and 1,491 HBV carriers. We discovered two novel associations at rs9272105 (HLA-DQA1/DRB1) on 6p21.32 (OR = 1.30, P = 1.13×$10^{−19}$) and rs455804 (GRIK1) on 21q21.3 (OR = 0.84, P = 1.86×$10^{−8}$), which were further replicated in the fourth independent sample of 1,298 cases and 1,026 controls (rs9272105: OR = 1.25, P = 1.71×$10^{−4}$; rs455804: OR = 0.84, P = 6.92×$10^{−3}$). We also revealed the associations of HLA-DRB1*0405 and 0901*0602, which could partially account for the association at rs9272105. The association at rs455804 implicates GRIK1 as a novel susceptibility gene for HBV–related HCC, suggesting the involvement of glutamate signaling in the development of HBV–related HCC

High-coverage whole-genome analysis of 1220 cancers reveals hundreds of genes deregulated by rearrangement-mediated cis-regulatory alterations.

The impact of somatic structural variants (SVs) on gene expression in cancer is largely unknown. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole-genome sequencing data and RNA sequencing from a common set of 1220 cancer cases, we report hundreds of genes for which the presence within 100 kb of an SV breakpoint associates with altered expression. For the majority of these genes, expression increases rather than decreases with corresponding breakpoint events. Up-regulated cancer-associated genes impacted by this phenomenon include TERT, MDM2, CDK4, ERBB2, CD274, PDCD1LG2, and IGF2. TERT-associated breakpoints involve ~3% of cases, most frequently in liver biliary, melanoma, sarcoma, stomach, and kidney cancers. SVs associated with up-regulation of PD1 and PDL1 genes involve ~1% of non-amplified cases. For many genes, SVs are significantly associated with increased numbers or greater proximity of enhancer regulatory elements near the gene. DNA methylation near the promoter is often increased with nearby SV breakpoint, which may involve inactivation of repressor elements

Calculation method for the effect of heat rejection of split-type air conditioner on thermal environment and building energy demand for neighbourhood-level

The purpose of this research is to propose a simple and fast method to evaluate the effect of heat rejection of split-type air conditioner on the thermal environment surrounding the building and the building cooling demand to provide guidance for architectural design in the urban planning stage. In this paper, we first determined the factors that affect or are affected by heat rejection as heat dissipation, wind speed, and ambient air temperature, which as inputs to the CFD to build the regression model of the temperature rise. Then, the regression model is coupled with the energy consumption simulation software EnergyPlus to estimate the building cooling increase. The result of taking a typical residential building as a reference show that the maximum temperature rise and cooling demand increase with the values of 1.86°C and 17%

The role of place-based policies on carbon emission: A quasi-natural experiment from China’s old revolutionary development program

The effectiveness of place-based policies on carbon emission is controversial, and particularly the mechanism behind its effectiveness is unknown. We treat China’s Old Revolutionary Development Program (ORDP)— a large-scale and novel type of place-based policy targeted at undeveloped regions, as a natural experiment to estimate ORDP’s impact on carbon emission. Employing the panel data of 110 prefecture-level cities in China from 2010 to 2019, we perform a time-varying difference-in-differences (DID) study and discover that ORDP leads to an average of 26.7% increase in carbon emission and this effect takes a period to emerge and is not sustainable in the long term. Three mechanisms that may result in such impact are that ORDP improves economic development, changes industrial structure, and decreases technological progress. Further heterogeneity analysis indicates that ORDP results in a greater increased impact on carbon emission in old revolutionary cities that are located in western China compared to those located in central and eastern China

Development and Test of a New Fast Estimate Tool for Cooling and Heating Load Prediction of District Energy Systems at Planning Stage

During the design and planning stage of a district energy system, the prediction of the cooling and heating loads is an important step. The accurate estimate of the load pattern can provide a basis for the configuration and optimization of the system. To meet the demand in practical application, this paper proposes a fast load prediction method for district energy systems based on a presimulated forward modelling database and KNN (K-nearest neighbor) algorithm and develops it into a practical tool. Owing to the absence of some design parameters at the planning stage, scenario analysis is also used to determine some input conditions for load prediction. In this paper, the scenarios cover three types of building: office, shopping mall and hotel. To test the performance of this new method, we randomly selected 15 virtual buildings (5 buildings for each type) with different design parameters and took their detailed BPS (building performance simulation) model as a benchmark to assess the prediction results of the new method. The index “ratio of the hours with effective prediction” is defined as the ratio of the hours whose relative error of hourly load prediction is less than 15% to the hours whose load is not 0 in the whole year, and the test result shows that this index is not less than 0.9 (90%) for the predicted cooling load of all 45 test cases and the predicted heating load of 25 of the 45 cases. As a research achievement with practical value, this paper accomplishes the programming work of the tool and makes it into a software. The application of this software in the actual project of district energy system is also presented. The performance of the new load prediction tool was compared with the traditional approach commonly used in engineering—the load estimation based on reference building models—and the result shows that the fast load estimate tool can provide the same level of prediction accuracy as traditional simulation methods

Energy consumption baselining and benchmarking of green office buildings in Shanghai

In recent years, many green buildings were built across China, but the actual performance is not as good as expected. Therefore, it is necessary to improve their performance and establish an objective energy consumption baseline as well as the benchmarking approach for green office buildings in Shanghai. Firstly, we categorized the green office buildings in Shanghai into two type - small and large, according to their floor area. Then we defined the baseline of EUI (energy use intensity, kWh/sq.m.a) based on the survey and submetering data and developed the reference models for both small and large green office building. Secondly, we specified four EUI reference levels for each type after studying the energy saving potential of green office buildings in Shanghai. Thirdly, in order to make the benchmarking approach more objective, we proposed EUI correction method for office buildings considering three main influencing factors - schedule, occupant density and meteorological parameters. We established a typical building model library of office buildings in Shanghai. We adopted regression analysis to obtain the corrections for schedule and occupant density. As for meteorological parameters, by classifying the typical days and calculating their representative EUIs, we determined the correction method