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您的检索式：作者名="Mengran Cui"
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| 1 | Transient Simulation and Optimization of Regional Integrated Energy System显示文摘A modeling method of regional integrated energy system based on bus method and transient simulation is proposed,and the system optimization is based on the dynamic balance of supply and demand in the whole year energy supply cycle.A CCHP systemof gas turbine coupled with ground source heat pump and electric refrigeration unit is constructed.The energy relationship of the systemis described by bus structure,and the transient calculationmodel is built on TRNSYS platform.The weighted sum of annual total cost saving rate,primary energy saving rate and environmental pollutant shadow cost saving rate is taken as the optimized objective function,and on the basis of annual dynamic balance,the Hooke-Jeeves algorithm is used for optimization of the system configuration.A complex commercial area in Beijing is taken as an example,and different weighting coefficients are set for optimization of the system configuration.The results show that,from the perspective of economy,environmental benefit and primary energy consumption,performance of the system increases and then decreases with rise of gas turbine power;under the simulated cooling/heating load,the maximum number of optimum configuration is seen in the combination of 35 kW gas turbine+723 kW GSHP and 1178 kW electric chiller;in comparison with traditional distributed system,the annual cost saving rate,primary energy saving rate and environmental pollutant shadow cost saving rate of the system are 29.4%,49.6%and 58.2%,respectively. | Xueqin Tian Mengran Cui Tong Xu Jinfei Sun Xinlei Wang Jiangxiang Guo De-Gejirifu Na Wang | 2022 | Energy Engineering2022，119，3： | 0 |
| 2 | Dynamic Simulation and Performance Analysis on Multi-Energy Coupled CCHP System显示文摘Although the Combined Cooing,Heating and Power System(hereinafter referred to as“CCHP”)improves the capacity utilization rate and energy utilization efficiency,single use of CCHP system cannot realize dynamic matching between supply and demand loads due to the unbalance features of the user’s cooling and heating loads.On the basis of user convenience and wide applicability of clean air energy,this paper tries to put forward a coupled CCHP system with combustion gas turbine and ASHP ordered power by heat,analyze trends of such parameters as gas consumption and power consumption of heat pump in line with adjustment of heating load proportion of combustion gas turbine,and optimize the system ratio in the method of annual costs and energy environmental benefit assessment.Based on the analysis of the hourly simulation and matching characteristics of the cold and hot load of the 100 thousand square meter building,it is found that the annual cost of the air source heat pump is low,but the energy and environmental benefits are poor.It will lead to 6.35%shortage of cooling load in summer.Combined with the evaluation method of primary energy consumption and zero carbon dioxide emission,the coupling system of CHHP and air source heat pump with 41%gas turbine load ratio is the best configuration.This system structure and optimization method can provide some reference for the development of CCHP coupling system. | Xueqin Tian Jinfei Sun Tong Xu Mengran Cui Xinlei Wang Jianxiang Guo De-gejirifu Na Wang | 2022 | Energy Engineering2022，119，2： | 0 |
| 3 | Annotating TSSs in Multiple Cell Types Based on DNA Sequence and RNA-seq Data via DeeReCT-TSS显示文摘The accurate annotation of transcription start sites(TSSs)and their usage are critical for the mechanistic understanding of gene regulation in different biological contexts.To fulfill this,specific high-throughput experimental technologies have been developed to capture TSSs in a genome-wide manner,and various computational tools have also been developed for in silico prediction of TSSs solely based on genomic sequences.Most of these computational tools cast the problem as a binary classification task on a balanced dataset,thus resulting in drastic false positive predictions when applied on the genome scale.Here,we present Dee Re CT-TSS,a deep learningbased method that is capable of identifying TSSs across the whole genome based on both DNA sequence and conventional RNA sequencing data.We show that by effectively incorporating these two sources of information,Dee Re CT-TSS significantly outperforms other solely sequence-based methods on the precise annotation of TSSs used in different cell types.Furthermore,we develop a meta-learning-based extension for simultaneous TSS annotations on 10 cell types,which enables the identification of cell type-specific TSSs.Finally,we demonstrate the high precision of DeeReCT-TSS on two independent datasets by correlating our predicted TSSs with experimentally defined TSS chromatin states.The source code for Dee Re CT-TSS is available at http://gffzzec4b27d8b73d463as5noppwkn05c0666o.ffgz.tsg.suse.edu.cn/Joshua Chou2018/Dee Re CT-TSS_release and http://gffzz77e3413bc06540eds5noppwkn05c0666o.ffgz.tsg.suse.edu.cn/biocode/tools/BT007316. | Juexiao Zhou Bin Zhang Haoyang Li Longxi Zhou Zhongxiao Li Yongkang Long Wenkai Han Mengran Wang Huanhuan Cui Jingjing Li Wei Chen Xin Gao | 2022 | Genomics, Proteomics & Bioinformatics2022，20，5： | 0 |
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