Advances in Applied Energy最新文献

{"title":"Exploring the trilemma of cost-efficiency, landscape impact and regional equality in onshore wind expansion planning","authors":"Jann Michael Weinand ,&nbsp;Russell McKenna ,&nbsp;Heidi Heinrichs ,&nbsp;Michael Roth ,&nbsp;Detlef Stolten ,&nbsp;Wolf Fichtner","doi":"10.1016/j.adapen.2022.100102","DOIUrl":"10.1016/j.adapen.2022.100102","url":null,"abstract":"<div><p>Onshore wind development has historically focused on cost-efficiency, which may lead to uneven turbine distributions and public resistance due to landscape impacts. Using a multi-criteria planning approach, we show how onshore wind capacity targets can be achieved by 2050 in a cost-efficient, visually unobtrusive and evenly distributed way. For the case study of Germany, we build on the existing turbine stock and use open data on technically feasible turbine locations and data on scenicness of landscapes to plan the optimal expansion. The analysis shows that while the trade-off between optimizing either cost-efficiency or landscape impact of the turbines is rather weak with about 15% higher costs or scenicness, an even distribution has a large impact on these criteria. However, a more evenly distributed expansion is necessary for the achievement of the targeted <em>south quota</em>, a policy target that calls for more wind turbine additions in southern Germany. Our analysis assists stakeholders in resolving the onshore wind expansion trilemma.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"7 ","pages":"Article 100102"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792422000208/pdfft?md5=ceab46c1251b3c00b9f599f9b5cb58bf&pid=1-s2.0-S2666792422000208-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47605001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cities are not isolates: To reduce their impacts a change in urban-rural interdependencies and the direction of modernity are required","authors":"Stephanie Pincetl","doi":"10.1016/j.adapen.2022.100104","DOIUrl":"10.1016/j.adapen.2022.100104","url":null,"abstract":"<div><p>It has become assumed that most humans will live in cities going forward and that they can be made to mitigate their environmental impacts. These assumptions come out of a period that has enjoyed ample energy from fossil fuels, and invisible to most, enormous resource flows from non-urban areas. For cities to reduce their GHGs, that means they must be reduced in resourcing areas, challenging our current deep dependence on fossil energy. This perspective suggests there is a need for new research that investigates how to reduce GHGs in resourcing areas through intensive agroecology, how to build climate appropriate, low embedded GHG emissions buildings, low energy technologies, to move to a future where we begin to live within the limits of the planet.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"7 ","pages":"Article 100104"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792422000221/pdfft?md5=e3278d306af6c125e1a09f8c8a367241&pid=1-s2.0-S2666792422000221-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45722325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing resilience of integrated electricity-gas systems: A skeleton-network based strategy","authors":"Maosheng Sang ,&nbsp;Yi Ding ,&nbsp;Minglei Bao ,&nbsp;Yonghua Song ,&nbsp;Peng Wang","doi":"10.1016/j.adapen.2022.100101","DOIUrl":"10.1016/j.adapen.2022.100101","url":null,"abstract":"<div><p>The increasing frequency of major energy outages in recent years has significantly affected millions of people around the world, raising extensive concerns about enhancing infrastructure resilience to withstand and quickly recover from disasters. However, the post-disaster recovery of infrastructure functionality has been hindered by the lack of interdependency modeling of energy networks and priority identification of components, resulting in long-duration energy supply scarcity, wide-ranging service disruption, and huge social losses. Here, a skeleton-network based strategy for enhancing the resilience of integrated electricity-gas systems (IEGSs) is proposed, which can provide a clear representation of which network components should be protected and how to determine the component recovery priority considering interdependencies of power and gas systems. Using the modified energy systems in New England and Northwest China, the skeleton-network is uncovered to quickly recover more than 90% of system functionality using less than 44.3% of total resources, and consumer-affected time by energy outages decreases by more than 53%. The analysis also indicates that compared to conventional methods, the skeleton-network based strategy performs best in improving infrastructure resilience. These results elucidate the implications of skeleton-networks on quick recovery of infrastructure functionality and demonstrate resilience enhancement methods that are applicable to a wider class of coupled infrastructure networks in hazard-prone areas.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"7 ","pages":"Article 100101"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792422000191/pdfft?md5=d8d5e808a577f29bec9b9fe563dd6457&pid=1-s2.0-S2666792422000191-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45032880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"False data injection attacks on data markets for electric vehicle charging stations","authors":"Samrat Acharya,&nbsp;Robert Mieth,&nbsp;Ramesh Karri,&nbsp;Yury Dvorkin","doi":"10.1016/j.adapen.2022.100098","DOIUrl":"10.1016/j.adapen.2022.100098","url":null,"abstract":"<div><p>Modern societies use machine learning techniques to support complex decision-making processes (e.g., renewable energy and power demand forecasting in energy systems). Data fuels these techniques, so the quality of the data fed into them determines the accuracy of the results. While the amount of data is increasing with the adoption of internet-of-things, most of it is still private. Availability of data limits the application of machine learning. Scientists and industry pioneers are proposing a model that relies on the economics of data markets, where private data can be traded for a price. Cybersecurity analyses of such markets are lacking. In this context, our study makes two contributions. First, it designs a data market for electric vehicle charging stations, which aims to improve the accuracy of electric vehicle charging demand forecasts. Accurate demand forecasts are essential for sustainable operations of the electric vehicle - charging station - power grid ecosystem, which, in turn, facilitates the electrification and decarbonization of the transportation sector. On the other hand, erroneous demand forecasts caused by malicious cyberattacks impose operational challenges to the ecosystem. Thus, the second contribution of our study is to examine the feasibility of false data injection attacks on the data market for electric vehicle charging stations and to propose a defense mechanism against such attacks. We illustrate our results using data from electric vehicle charging stations in Manhattan, New York. We demonstrate that the data market improves forecasting accuracy of charging stations and reduces the effectiveness of false data injection attacks. The purpose of this work is not only to inform electric vehicle charging stations about the economic benefits of data markets, but to promote cyber awareness among data market pioneers and stakeholders.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"7 ","pages":"Article 100098"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792422000166/pdfft?md5=8334939cc12261b864ed7d64ec18484b&pid=1-s2.0-S2666792422000166-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43405904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High technical and temporal resolution integrated energy system modelling of industrial decarbonisation","authors":"Sánchez Diéguez Manuel ,&nbsp;Taminau Floris ,&nbsp;West Kira ,&nbsp;Sijm Jos ,&nbsp;Faaij André","doi":"10.1016/j.adapen.2022.100105","DOIUrl":"10.1016/j.adapen.2022.100105","url":null,"abstract":"<div><p>Owing to the complexity of the sector, industrial activities are often represented with limited technological resolution in integrated energy system models. In this study, we enriched the technological description of industrial activities in the integrated energy system analysis optimisation (IESA-Opt) model, a peer-reviewed energy system optimisation model that can simultaneously provide optimal capacity planning for the hourly operation of all integrated sectors. We used this enriched model to analyse the industrial decarbonisation of the Netherlands for four key activities: high-value chemicals, hydrocarbons, ammonia, and steel production. The analyses performed comprised 1) exploring optimality in a reference scenario; 2) exploring the feasibility and implications of four extreme industrial cases with different technological archetypes, namely a bio-based industry, a hydrogen-based industry, a fully electrified industry, and retrofitting of current assets into carbon capture utilisation and storage; and 3) performing sensitivity analyses on key topics such as imported biomass, hydrogen, and natural gas prices, carbon storage potentials, technological learning, and the demand for olefins. The results of this study show that it is feasible for the energy system to have a fully bio-based, hydrogen-based, fully electrified, and retrofitted industry to achieve full decarbonisation while allowing for an optimal technological mix to yield at least a 10% cheaper transition. We also show that owing to the high predominance of the fuel component in the levelled cost of industrial products, substantial reductions in overnight investment costs of green technologies have a limited effect on their adoption. Finally, we reveal that based on the current (2022) energy prices, the energy transition is cost-effective, and fossil fuels can be fully displaced from industry and the national mix by 2050.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"7 ","pages":"Article 100105"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792422000233/pdfft?md5=3e6ba392ed1f0588cbccbadc72f0c602&pid=1-s2.0-S2666792422000233-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48704206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Strategic retail pricing and demand bidding of retailers in electricity market: A data-driven chance-constrained programming","authors":"Dawei Qiu ,&nbsp;Zihang Dong ,&nbsp;Guangchun Ruan ,&nbsp;Haiwang Zhong ,&nbsp;Goran Strbac ,&nbsp;Chongqing Kang","doi":"10.1016/j.adapen.2022.100100","DOIUrl":"10.1016/j.adapen.2022.100100","url":null,"abstract":"<div><p>This paper proposes a novel bi-level optimization model to study the strategic retail pricing and demand bidding problems of an electricity retailer that considers the interactions between demand response and market clearing process. In order to accurately forecast the day-ahead demand bids submitted by the retailer, a novel deep learning framework based on convolutional neural networks and long short-term memory is proposed that can capture both local trends and long-term dependency of the forecasting data. In addition, uncertainties about the retailer’s served demand, rivals’ demand bids, and wind power generation are incorporated using the data-driven uncertainty set constructed from data. We further propose chance-constrained programming that introduces a set of chance constraints to represent the operational risk associated with the market uncertainties. To solve this problem, we first reformulate chance-constrained programming as a tractable second-order conic programming and then convert it into a single-level mathematical program with equilibrium constraints by using its Karush Kuhn Tucker conditions. The scope of the examined case studies is four-fold. First, they evaluate the benefits of the proposed forecasting framework in terms of higher accuracy and expected profit compared to the conventional forecasting methods. Second, they demonstrate how demand flexibility affects the retailer’s strategies and its business cases. Third, they highlight the added value of the proposed bi-level model capturing the market clearing process by comparing its outcomes against the state-of-the-art bi-level model with exogenous market prices. Finally, they analyze the retailer’s strategies and business cases at different confidence levels regarding the imposed chance constraints.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"7 ","pages":"Article 100100"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266679242200018X/pdfft?md5=9094ba34e1f6fcc630a959da13cd6aaa&pid=1-s2.0-S266679242200018X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45265271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analyzing the techno-economic role of nuclear power in the Dutch net-zero energy system transition","authors":"Amirhossein Fattahi ,&nbsp;Jos Sijm ,&nbsp;Machteld Van den Broek ,&nbsp;Rafael Martínez Gordón ,&nbsp;Manuel Sanchez Dieguez ,&nbsp;André Faaij","doi":"10.1016/j.adapen.2022.100103","DOIUrl":"10.1016/j.adapen.2022.100103","url":null,"abstract":"<div><p>To analyze the role of nuclear power in an integrated energy system, we used the IESA-Opt-N cost minimization model focusing on four key themes: system-wide impacts of nuclear power, uncertain technological costs, flexible generation, and cross-border electricity trade. We demonstrate that the LCOE (levelized cost of electricity) alone should not be used to demonstrate the economic feasibility of a power generation technology. For instance, under the default techno-economic assumptions, particularly the 5% discount rate and exogenous electricity trade potentials, it is cost-optimal for the Netherlands to invest in 9.6 GWe nuclear capacity by 2050. However, its LCOE is 34 €/MWh higher than offshore wind. Moreover, we found that nuclear power investments can reduce demand for variable renewable energy sources in the short term and higher energy independence (i.e., lower imports of natural gas, biomass, and electricity) in the long term. Furthermore, investing in nuclear power can reduce the mitigation costs of the Dutch energy system by 1.6% and 6.2% in 2040 and 2050, and 25% lower national CO₂ prices by 2050. However, this cost reduction is not significant given the odds of higher nuclear financing costs and longer construction times. In addition, with 3% interest rate value (e.g., EU taxonomy support), even high cost nuclear (10 B€/GW) can be cost-effective in the Netherlands. In conclusion, under the specific assumptions of this study, nuclear power can play a complementary role (in parallel to the wind and solar power) in supporting the Dutch energy transition from the sole techno-economic point of view.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"7 ","pages":"Article 100103"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266679242200021X/pdfft?md5=c42664685c80e83adba5029ca0a72b4a&pid=1-s2.0-S266679242200021X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44619165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How much demand flexibility could have spared texas from the 2021 outage?","authors":"Dongqi Wu ,&nbsp;Xiangtian Zheng ,&nbsp;Ali Menati ,&nbsp;Lane Smith ,&nbsp;Bainan Xia ,&nbsp;Yixing Xu ,&nbsp;Chanan Singh ,&nbsp;Le Xie","doi":"10.1016/j.adapen.2022.100106","DOIUrl":"https://doi.org/10.1016/j.adapen.2022.100106","url":null,"abstract":"<div><p>The February 2021 Texas winter power outage has led to hundreds of deaths and billions of dollars in economic losses, largely due to the generation failure and record-breaking electric demand. In this paper, we study the scaling-up of demand flexibility as a means to avoid load shedding during such an extreme weather event. The three mechanisms considered are interruptible load, residential load rationing, and incentive-based demand response. By simulating on a synthetic but realistic large-scale Texas grid model along with demand flexibility modeling and electricity outage data, we identify portfolios of mixing mechanisms that can completely avoid outages, where individual mechanisms may fail due to decaying marginal effects. We also reveal that interruptible load and residential load rationing are complementary, while incentive-based demand response exhibits counterintuitive nonlinear effects on the efficacy of other mechanisms. The quantitative results can provide instructive insights for developing demand response programs against extreme weather conditions.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"7 ","pages":"Article 100106"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792422000245/pdfft?md5=9dc51b1b571609a8c481a745ac3b2c2f&pid=1-s2.0-S2666792422000245-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91638725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Model predictive control for demand flexibility: Real-world operation of a commercial building with photovoltaic and battery systems","authors":"Kun Zhang ,&nbsp;Anand Prakash ,&nbsp;Lazlo Paul ,&nbsp;David Blum ,&nbsp;Peter Alstone ,&nbsp;James Zoellick ,&nbsp;Richard Brown ,&nbsp;Marco Pritoni","doi":"10.1016/j.adapen.2022.100099","DOIUrl":"10.1016/j.adapen.2022.100099","url":null,"abstract":"<div><p>Hundreds of studies have investigated Model Predictive Control (MPC) for the optimal operation of building energy systems in the past two decades. However, MPC field tests are still uncommon, especially for small- and medium-sized commercial buildings and for buildings integrated with onsite renewables. This paper describes the implementation and the long-term performance evaluation of an MPC controller in a small commercial building equipped with behind-the-meter photovoltaics and electrochemical batteries. MPC controls space conditioning, commercial refrigeration, and the battery system. We tested two types of demand flexibility applications in the field: electricity bill minimization under time-of-use tariffs and responses to grid flexibility events. Results show that the proposed controller achieves 12% of annual electricity cost savings and 34% peak demand reduction against the baseline, while respecting thermal comfort and food safety. The field tests also demonstrate the ability of the MPC controller to provide a multitude of grid services including real-time pricing, demand limiting, load shedding, load shifting, and load tracking, using the same optimization framework.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"7 ","pages":"Article 100099"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792422000178/pdfft?md5=543c118e317ff65541736f89f831de84&pid=1-s2.0-S2666792422000178-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43140234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Benefits of an integrated power and hydrogen offshore grid in a net‐zero North Sea energy system","authors":"Rafael Martínez-Gordón ,&nbsp;Laura Gusatu ,&nbsp;Germán Morales-España ,&nbsp;Jos Sijm ,&nbsp;André Faaij","doi":"10.1016/j.adapen.2022.100097","DOIUrl":"https://doi.org/10.1016/j.adapen.2022.100097","url":null,"abstract":"<div><p>The North Sea Offshore Grid concept has been envisioned as a promising alternative to: 1) ease the integration of offshore wind and onshore energy systems, and 2) increase the cross-border capacity between the North Sea region countries at low cost. In this paper we explore the techno-economic benefits of the North Sea Offshore Grid using two case studies: a power-based offshore grid, where only investments in power assets are allowed (i.e. offshore wind, HVDC/HVAC interconnectors); and a power-and-hydrogen offshore grid, where investments in offshore hydrogen assets are also permitted (i.e. offshore electrolysers, new hydrogen pipelines and retrofitted natural gas pipelines). In this paper we present a novel methodology, in which extensive offshore spatial data is analysed to define meaningful regions via data clustering. These regions are incorporated to the <strong>I</strong>ntegrated <strong>E</strong>nergy <strong>S</strong>ystem <strong>A</strong>nalysis for the <strong>N</strong>orth <strong>S</strong>ea region (IESA-NS) model. In this optimization model, the scenarios are run without any specific technology ban and under open optimization. The scenario results show that the deployment of an offshore grid provides relevant cost savings, ranging from 1% to 4.1% of relative cost decrease (2.3 bn € to 8.7 bn €) in the power-based, and ranging from 2.8% to 7% of relative cost decrease (6 bn € to 14.9 bn €) in the power-and-hydrogen based. In the most extreme scenario an offshore grid permits to integrate 283 GW of HVDC connected offshore wind and 196 GW of HVDC meshed interconnectors. Even in the most conservative scenario the offshore grid integrates 59 GW of HVDC connected offshore wind capacity and 92 GW of HVDC meshed interconnectors. When allowed, the deployment of offshore electrolysis is considerable, ranging from 61 GW to 96 GW, with capacity factors of around 30%.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"7 ","pages":"Article 100097"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792422000154/pdfft?md5=b47b559d263d07ea7ade207642de50f5&pid=1-s2.0-S2666792422000154-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91638726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}