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Probabilistic load forecasting for integrated energy systems using attentive quantile regression temporal convolutional network 利用殷勤的量子回归时空卷积网络为综合能源系统进行概率负荷预测
Q1 ENERGY & FUELS Pub Date : 2024-02-19 DOI: 10.1016/j.adapen.2024.100165
Han Guo, Bin Huang, Jianhui Wang

The burgeoning proliferation of integrated energy systems has fostered an unprecedented degree of coupling among various energy streams, thereby elevating the necessity for unified multi-energy forecasting (MEF). Prior approaches predominantly relied on independent predictions for heterogeneous load demands, overlooking the synergy embedded within the dataset. The two principal challenges in MEF are extracting the intricate coupling correlations among diverse loads and accurately capturing the inherent uncertainties associated with each type of load. This study proposes an attentive quantile regression temporal convolutional network (QTCN) as a probabilistic framework for MEF, featuring an end-to-end predictor for the probabilistic intervals of electrical, thermal, and cooling loads. This study leverages an attention layer to extract correlations between diverse loads. Subsequently, a QTCN is implemented to retain the temporal characteristics of load data and gauge the uncertainties and temporal correlations of each load type. The multi-task learning framework is deployed to facilitate simultaneous regression of various quantiles, thereby expediting the training progression of the forecasting model. The proposed model is validated using realistic load data and meteorological data from the Arizona State University metabolic system and National Oceanic and Atmospheric Administration respectively, and the results indicate superior performance and greater economic benefits compared to the baselines in existing literature.

综合能源系统的蓬勃发展促进了各种能源流之间前所未有的耦合程度,从而提升了统一多能源预测(MEF)的必要性。之前的方法主要依赖于对异质负荷需求的独立预测,忽略了数据集中蕴含的协同作用。MEF 面临的两大挑战是提取不同负荷之间错综复杂的耦合相关性,以及准确捕捉与各类负荷相关的固有不确定性。本研究提出了一种注意力量化回归时序卷积网络(QTCN),作为 MEF 的概率框架,其特点是为电力、热力和冷却负载的概率区间提供端到端预测器。本研究利用注意力层提取不同负载之间的相关性。随后,实施了一个 QTCN,以保留负载数据的时间特性,并衡量每种负载类型的不确定性和时间相关性。多任务学习框架的部署有助于同时对各种量化数据进行回归,从而加快预测模型的训练进度。利用亚利桑那州立大学新陈代谢系统和美国国家海洋和大气管理局分别提供的现实负荷数据和气象数据,对所提出的模型进行了验证,结果表明,与现有文献中的基准相比,该模型具有更优越的性能和更大的经济效益。
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引用次数: 0
Geographically constrained resource potential of integrating floating photovoltaics in global existing offshore wind farms 在全球现有海上风电场中整合浮动光伏的地理限制资源潜力
Q1 ENERGY & FUELS Pub Date : 2024-02-01 DOI: 10.1016/j.adapen.2024.100163
Yubin Jin , Zhenzhong Zeng , Yuntian Chen , Rongrong Xu , Alan D. Ziegler , Wenchuang Chen , Bin Ye , Dongxiao Zhang

Marine renewable energy is gaining prominence as a crucial component of the energy supply in coastal cities due to proximity and minimal land requirements. The synergistic potential of integrating floating photovoltaics with offshore wind turbines presents an encouraging avenue for boosting power production, amplifying spatial energy generation density, and mitigating seasonal output fluctuations. While the global promise of offshore wind-photovoltaic hybrid systems is evident, a definitive understanding of their potential remains elusive. Here, we evaluate the resource potential of the hybrid systems under geographical constraints, offering insights into sustainable and efficient offshore energy solutions. We compile a database with 11,198 offshore wind turbine locations from Sentinel-1 imagery and technical parameters from commercial project details. Our analysis reveals an underutilization of spatial resources within existing offshore wind farms, yielding a modest 26 kWh per square meter. Furthermore, employing realistic climate-driven system simulations, we find an impressive potential photovoltaic generation of 1372 ± 18 TWh annually, over seven times higher than the current offshore wind capacity. Notably, floating photovoltaics demonstrated remarkable efficiency, matching wind turbine output with a mere 17 % of the wind farm area and achieving an average 76 % increase in power generation at equivalent investment costs. Additionally, the hybrid wind and photovoltaic systems exhibit monthly-scale complementarity, reflected by a Pearson correlation coefficient of -0.78, providing a consistent and reliable power supply. These findings support the notion that hybrid offshore renewable energy could revolutionize the renewable energy industry, optimize energy structures, and contribute to a sustainable future for coastal cities.

海洋可再生能源由于距离近、对土地要求低,正逐渐成为沿海城市能源供应的重要组成部分。将漂浮光伏发电与海上风力涡轮机集成的协同潜力为提高发电量、扩大空间能源发电密度和缓解季节性输出波动提供了令人鼓舞的途径。虽然近海风能-光伏发电混合系统的全球前景显而易见,但对其潜力的确切了解仍然遥遥无期。在此,我们评估了混合系统在地理限制条件下的资源潜力,为可持续和高效的近海能源解决方案提供了见解。我们建立了一个数据库,其中包含来自哨兵-1 图像的 11,198 个海上风力涡轮机位置,以及来自商业项目详细信息的技术参数。我们的分析表明,现有海上风电场的空间资源利用率不足,每平方米仅能产生 26 千瓦时的电量。此外,通过采用现实的气候驱动系统模拟,我们发现光伏发电的潜在年发电量高达 1372 ± 18 太瓦时,是目前海上风力发电能力的七倍多。值得注意的是,浮动光伏发电表现出卓越的效率,仅用 17% 的风电场面积就能达到风力涡轮机的发电量,并且在投资成本相当的情况下,发电量平均增加了 76%。此外,风电和光伏发电混合系统呈现出月度互补性,皮尔逊相关系数为-0.78,可提供稳定可靠的电力供应。这些研究结果支持这样一种观点,即混合型海上可再生能源可以彻底改变可再生能源产业,优化能源结构,并为沿海城市的可持续未来做出贡献。
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引用次数: 0
Robust design of hybrid solar power systems: Sustainable integration of concentrated solar power and photovoltaic technologies 混合太阳能发电系统的稳健设计:聚光太阳能和光伏技术的可持续整合
Q1 ENERGY & FUELS Pub Date : 2024-02-01 DOI: 10.1016/j.adapen.2024.100164
Gabriele Furlan , Fengqi You

The global energy sector is now transitioning its structure towards carbon neutrality aided by renewable resource use. Despite its immense potential, solar energy contributes minimally to the global energy mix due to its intermittent nature and challenges with power demand fluctuations. Increased use of distributed solar sources alters market dynamics, necessitating conventional power plants to ramp up output during lower renewable energy production times and manage oversupply risks. Concentrated solar power (CSP) can contribute to grid decarbonization, but its high levelized cost of electricity (LCOE) impedes widespread adoption. This study proposes hybridizing CSP and photovoltaic (PV) technologies, aiming to leverage their synergy to maximize economic benefits. We develop a comprehensive process design framework that utilizes a robust multi-objective optimization (MOO) approach, which factors in techno-economic and environmental objectives while accounting for model uncertainty from resource prices and life cycle assessment indicators. Optimization results reveal that in Ivanpah, California, hybrid CSP + PV can reduce 41 % of LCOE and limit environmental impacts compared to standalone CSP plants. This robust framework also identifies design trends, such as a constant dependence on the PV field, and a trade-off between the installed area of the solar concentrators and the backup boiler operation. The optimal unit sizes, less susceptible to future market fluctuations and potential changes in the global warming potential (GWP) of technologies, contribute significantly to robust and sustainable energy planning decisions.

在可再生资源利用的帮助下,全球能源部门目前正在向碳中和结构转型。尽管太阳能潜力巨大,但由于其间歇性和电力需求波动的挑战,太阳能对全球能源结构的贡献微乎其微。分布式太阳能资源使用的增加改变了市场动态,使传统发电厂必须在可再生能源产量较低时提高产量,并管理供过于求的风险。聚光太阳能发电(CSP)可促进电网去碳化,但其较高的平准化电力成本(LCOE)阻碍了其广泛应用。本研究建议将 CSP 和光伏(PV)技术混合使用,旨在利用它们的协同作用实现经济效益最大化。我们开发了一个综合流程设计框架,该框架采用了稳健的多目标优化(MOO)方法,在考虑资源价格和生命周期评估指标带来的模型不确定性的同时,还考虑了技术经济和环境目标。优化结果表明,与独立的 CSP 电站相比,在加利福尼亚州的 Ivanpah,CSP + PV 混合电站可降低 41% 的 LCOE,并限制对环境的影响。这一稳健的框架还确定了设计趋势,例如对光伏发电场的持续依赖,以及太阳能聚光器安装面积与备用锅炉运行之间的权衡。最佳装置尺寸不易受未来市场波动和技术全球升温潜能值(GWP)潜在变化的影响,可大大促进稳健和可持续的能源规划决策。
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引用次数: 0
A generation and transmission expansion planning model for the electricity market with decarbonization policies 采用去碳化政策的电力市场发电和输电扩展规划模型
Q1 ENERGY & FUELS Pub Date : 2024-01-02 DOI: 10.1016/j.adapen.2023.100162
Yunfei Du , Xinwei Shen , Daniel M. Kammen , Chaopeng Hong , Jinfeng Nie , Bo Zheng , Shangheng Yao

Globally, the power sector must undergo a profound transition to achieve the decarbonization development targets. Various roadmaps are implemented, but only from a macro perspective, lacking the consideration of the electricity market rules. In this paper, we develop and present a market-driven generation and transmission expansion planning (MGTEP) model considering the effectiveness of the electricity market. Specifically, generation and transmission companies incorporate hourly market trading and annual capacity investment into strategic decisions to maximize their profits, with the supply function equilibrium model to analyze bidding behaviors. An equivalent quadratic programming formulation is deployed to solve the trilevel MGTEP model. Meanwhile, the MGTEP model is coupled with decarbonization policies to support the state and federal government in assessing energy transition strategies. We implement the MGTEP model with carbon emission allowance and carbon tax policies for the southern China electricity market to achieve carbon peaking by 2030. Carbon emission allowance adopts an intensity-based cap based on generation companies' historical output. The case study results show that 50 % carbon emission allowance or 400 CNY/t carbon tax is required but with several drawbacks, including unsatisfactory decarbonization effect, excessive economic sacrifice, etc. Finally, the case study is extended to dual-track policies with different combinations of policies. An optimal combination is 70 % carbon emission allowance and 160 CNY/t carbon tax. In this case, the power sector's carbon dioxide emissions and electricity prices in the southern China electricity market would increase to 554.6 Mt and 864.34 CNY/MWh in 2030, respectively, along with a carbon price of 850 CNY/t.

在全球范围内,电力部门必须经历深刻的转型,以实现去碳化发展目标。各种路线图都已实施,但只是从宏观角度出发,缺乏对电力市场规则的考虑。在本文中,我们开发并提出了一个考虑到电力市场有效性的市场驱动型发电和输电扩建规划(MGTEP)模型。具体来说,发电公司和输电公司将每小时的市场交易和年度容量投资纳入战略决策,以实现利润最大化。该模型采用等效二次编程公式求解三级 MGTEP 模型。同时,MGTEP 模型与去碳化政策相结合,为州和联邦政府评估能源转型战略提供支持。我们将 MGTEP 模型与碳排放配额和碳税政策相结合,用于中国南方电力市场,以实现 2030 年的碳调峰。碳排放限额采用基于发电企业历史发电量的强度上限。案例研究结果表明,需要 50% 的碳排放配额或 400 元人民币/吨的碳税,但存在一些缺点,包括去碳化效果不理想、经济牺牲过大等。最后,案例研究扩展到不同政策组合的双轨制政策。最佳组合为 70% 的碳排放配额和 160 元人民币/吨的碳税。在此情况下,2030 年中国南方电力市场的电力行业二氧化碳排放量和电价将分别增至 5.546 亿吨和 864.34 元人民币/兆瓦时,碳价格为 850 元人民币/吨。
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引用次数: 0
Assessing the implications of hydrogen blending on the European energy system towards 2050 评估氢气掺混对 2050 年前欧洲能源系统的影响
Q1 ENERGY & FUELS Pub Date : 2023-12-30 DOI: 10.1016/j.adapen.2023.100161
Jonathan Hanto , Philipp Herpich , Konstantin Löffler , Karlo Hainsch , Nikita Moskalenko , Sarah Schmidt

With the aim of reducing carbon emissions and seeking independence from Russian gas in the wake of the conflict in Ukraine, the use of hydrogen in the European Union is expected to rise in the future. In this regard, hydrogen transport via pipeline will become increasingly crucial, either through the utilization of existing natural gas infrastructure or the construction of new dedicated hydrogen pipelines. This study investigates the effects of hydrogen blending in existing pipelines on the European energy system by the year 2050, by introducing hydrogen blending sensitivities to the Global Energy System Model (GENeSYS-MOD). Results indicate that hydrogen demand in Europe is inelastic and limited by its high costs and specific use cases, with hydrogen production increasing by 0.17% for 100%-blending allowed compared to no blending allowed. The availability of hydrogen blending has been found to impact regional hydrogen production and trade, with countries that can utilize existing natural gas pipelines, such as Norway, experiencing an increase in hydrogen and synthetic gas exports from 44.0 TWh up to 105.9 TWh in 2050, as the proportion of blending increases. Although the influence of blending on the overall production and consumption of hydrogen in Europe is minimal, the impacts on the location of production and dependence on imports must be thoroughly evaluated in future planning efforts.

为了减少碳排放,并在乌克兰冲突后寻求从俄罗斯天然气中独立出来,预计未来欧盟的氢气使用量将会增加。在这方面,通过管道运输氢气将变得越来越重要,既可以利用现有的天然气基础设施,也可以建设新的氢气专用管道。本研究通过在全球能源系统模型(GENeSYS-MOD)中引入氢气掺混敏感性,研究了到 2050 年现有管道中氢气掺混对欧洲能源系统的影响。结果表明,欧洲的氢气需求缺乏弹性,并受到其高昂成本和特定用途的限制,与不允许混合氢气相比,允许 100% 混合氢气的情况下氢气产量增加 0.17%。研究发现,氢气掺混的可用性会影响区域氢气生产和贸易,随着掺混比例的增加,挪威等可以利用现有天然气管道的国家的氢气和合成气出口量将从 44.0 太瓦时增加到 2050 年的 105.9 太瓦时。尽管掺混对欧洲氢气总体生产和消费的影响微乎其微,但在未来的规划工作中,必须全面评估掺混对生产地点和进口依赖性的影响。
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引用次数: 0
Balancing stakeholder benefits: A many-objective optimal dispatch framework for home energy systems inspired by Maslow's Hierarchy of needs 平衡利益相关者的利益:受马斯洛需求层次理论启发的家庭能源系统多目标优化调度框架
Q1 ENERGY & FUELS Pub Date : 2023-12-21 DOI: 10.1016/j.adapen.2023.100160
Jinqing Peng , Zhengyi Luo , Yutong Tan , Haihao Jiang , Rongxin Yin , Jinyue Yan

The optimal scheduling of home energy systems is influenced by the benefits of different stakeholders, with the hierarchical nature of user's needs being particularly significant. However, previous studies have largely neglected these factors. To bridge the research gaps, a many-objective optimal dispatch framework for home energy systems, which was inspired by Maslow's hierarchy of needs, was proposed. In the framework, user's needs for the optimal dispatch of home energy systems were categorized into various hierarchies referring to the Maslow's theory, which were fulfilled in a specific sequence during the scheduling optimization. In addition to the user's needs, the benefits of grid operators and policymakers were considered in the developed many-objective nonlinear optimal model, which includes six objective functions that capture the interests of end-users, grid operators, and policymakers. Simulation results obtained across the home energy systems with various configurations verified the effectiveness of the proposed framework. Results indicate that user's needs can be fully satisfied and a tradeoff among the benefits of end-users, grid operators, and policymakers was achieved. For various home energy systems, the optimal scheduling demonstrated reductions of 22.33 %-81.05 % in daily operation costs, 14.39 %-25.68 % in CO2 emissions, and 15.58 %-17.49 % in peak-valley differences, associated with increment of 5.37 %-15.51 % in self-consumption rate and 8.91 %-27.29 % in self-sufficiency rate, compared with the benchmark. The proposed framework provides valuable guidance for the optimal scheduling of various home energy systems in practical applications.

家庭能源系统的优化调度受到不同利益相关者利益的影响,其中用户需求的层次性尤为重要。然而,以往的研究在很大程度上忽视了这些因素。为了弥补研究空白,受马斯洛需求层次理论的启发,提出了一个多目标家庭能源系统优化调度框架。在该框架中,参照马斯洛理论,用户对家庭能源系统优化调度的需求被分为不同层次,并在调度优化过程中按特定顺序得到满足。除用户需求外,开发的多目标非线性优化模型还考虑了电网运营商和政策制定者的利益,该模型包括六个目标函数,分别反映了最终用户、电网运营商和政策制定者的利益。在不同配置的家庭能源系统中获得的模拟结果验证了所提框架的有效性。结果表明,用户的需求可以得到充分满足,并实现了终端用户、电网运营商和政策制定者之间的利益权衡。对于不同的家庭能源系统,与基准相比,优化调度可减少 22.33 %-81.05 % 的日常运营成本、14.39 %-25.68 % 的二氧化碳排放量和 15.58 %-17.49 % 的峰谷差,同时可提高 5.37 %-15.51 % 的自用率和 8.91 %-27.29 % 的自给率。所提出的框架为实际应用中各种家庭能源系统的优化调度提供了宝贵的指导。
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引用次数: 0
Energy and cost savings of cool coatings for multifamily buildings in U.S. climate zones 美国气候区多户住宅建筑冷却涂层的节能与成本节约
Q1 ENERGY & FUELS Pub Date : 2023-12-20 DOI: 10.1016/j.adapen.2023.100159
Xiao Nie , Robert Flores , Jack Brouwer , Jaeho Lee

While cool coatings have recently received much attention for building applications, their impact on building energy consumption strongly depends upon climatic conditions. Herein we evaluate the energy, cost, carbon, and interior comfort impact of cool coatings applied to a residential multifamily building across 32 climate zones in the United States by applying advanced cool coating properties to established building energy models. The model not only considers promising cool coating properties based upon recent experiments but also an ideal cool coating. Our calculations show that the ideal cool coating can achieve annual cooling energy savings of up to 6.64 kWh/m2 (Phoenix, AZ), annual net utility cost savings up to $1.16/m2 (Brawley, CA), and net annual carbon emission savings up to 7.7 % (Phoenix, AZ). We also estimate the change in interior temperature for buildings without space cooling systems and show that cool coatings make buildings in the warmest climate zones in the U.S. without space cooling more comfortable by 30 % to 50 % on a cooling degree days basis. Using analysis of variance, we examine the statistical relationships between building performance metrics and climatic parameters. The presented methodology enables evaluation of cool coating application to buildings in various climate zones across the world.

虽然清凉涂料在建筑中的应用近来备受关注,但其对建筑能耗的影响在很大程度上取决于气候条件。在此,我们通过将先进的降温涂料特性应用到已建立的建筑节能模型中,对应用于美国 32 个气候带多户住宅建筑的降温涂料在能源、成本、碳排放和室内舒适度方面的影响进行了评估。该模型不仅考虑了基于最新实验的有前景的降温涂层特性,还考虑了理想的降温涂层。我们的计算结果表明,理想的冷却涂层每年可节省高达 6.64 kWh/m2 的制冷能耗(亚利桑那州凤凰城),每年可节省高达 1.16 美元/m2 的净水电成本(加利福尼亚州布劳利),每年可节省高达 7.7 % 的净碳排放(亚利桑那州凤凰城)。我们还估算了没有空间冷却系统的建筑物的室内温度变化,结果表明,在美国气候最温暖、没有空间冷却系统的地区,按降温度日计算,降温涂料可使建筑物的舒适度提高 30% 至 50%。通过方差分析,我们研究了建筑性能指标与气候参数之间的统计关系。所介绍的方法可以对全球不同气候区的建筑应用降温涂层进行评估。
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引用次数: 0
Reviewing accuracy & reproducibility of large-scale wind resource assessments 审查大规模风能资源评估的准确性和可重复性
Q1 ENERGY & FUELS Pub Date : 2023-12-07 DOI: 10.1016/j.adapen.2023.100158
Tristan Pelser , Jann Michael Weinand , Patrick Kuckertz , Russell McKenna , Jochen Linssen , Detlef Stolten

The accurate quantification and assessment of available renewable energy resources has emerged as a research topic with high relevance to policymakers and industry. Motivated by the need for a contemporary review on the methodologies and practices prevalent in wind resource assessments, we employ a systematic analysis of 195 articles that describe large-scale wind assessments. Our review reveals significant heterogeneity in global and continental-scale potentials and geographical bias of research towards the Northern Hemisphere, despite electrification needs in regions like Africa and Latin America. A fraction of the literature attempts to explicitly include social and political barriers to wind power development, thereby defining ‘feasible’ potentials. We delve into advancements in this domain, focusing on innovative methodologies that encapsulate the viewpoints of subject experts and stakeholders in the assessment process. Our analysis underscores pressing challenges relating to data sharing and scientific reproducibility, with our findings revealing a mere 10 % of studies that offer openly available data for download. This highlights a pervasive insufficiency in the reproducibility of wind assessments. Additionally, we tackle notable hurdles concerning wind data and meteorological characterization, including an over-reliance on single-source wind data and a deficit in adequately characterizing temporal wind variability. Relatedly, we uncover a highly heterogenous approach to turbine siting and characterizing wake-related losses. These methods are frequently simplistic, potentially leading to an overestimation of wind potentials by assuming an overly optimistic capacity density. In each of these domains, we discuss the state of the art for modern wind resource assessments, propose best practices, and pinpoint crucial areas warranting future research.

可再生能源资源的准确量化和评估已成为政策制定者和行业高度相关的研究课题。由于需要对风能资源评估中普遍存在的方法和实践进行当代回顾,我们对195篇描述大规模风能评估的文章进行了系统分析。我们的回顾显示,尽管非洲和拉丁美洲等地区有电气化需求,但全球和大陆范围内的潜力存在显著的异质性,研究的地理偏差也倾向于北半球。一小部分文献试图明确地包括风力发电发展的社会和政治障碍,从而定义“可行”的潜力。我们深入研究了这一领域的进展,专注于在评估过程中封装主题专家和利益相关者观点的创新方法。我们的分析强调了与数据共享和科学可重复性相关的紧迫挑战,我们的研究结果显示,只有10%的研究提供公开的数据供下载。这突出了风评估的可重复性普遍不足。此外,我们解决了有关风数据和气象特征的显著障碍,包括过度依赖单一来源的风数据和在充分表征时间风变率方面的缺陷。与此相关,我们发现了一种高度异质的方法来定位涡轮机并表征尾迹相关的损失。这些方法往往过于简单,通过假设过于乐观的容量密度,可能导致对风力潜力的高估。在这些领域中,我们讨论了现代风能资源评估的最新技术,提出了最佳实践,并指出了需要未来研究的关键领域。
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引用次数: 0
Integrated optimization in operations control and systems design for carbon emission reduction in building electrification with distributed energy resources 分布式能源建筑电气化运行控制与碳减排系统设计集成优化
Q1 ENERGY & FUELS Pub Date : 2023-12-01 DOI: 10.1016/j.adapen.2023.100144
Shiyu Yang , H. Oliver Gao , Fengqi You

Building electrification with distributed energy resources (DERs) is a promising strategy to decarbonize the building sector. Considering the inter-dependencies between operations control and systems design, integrating technology operations control optimization with DERs investment optimization can cost-effectively enhance such building decarbonization opportunities. This study proposes a multi-timescale integrated optimization framework to simultaneously optimize the design and control of DERs and electrification technologies for buildings. A novel building operational performance prediction model based on deep learning is developed to approximate and replace the computationally expensive control optimization. This helps resolve the challenging, computationally intractable multi-timescale integrated design and control optimization problem. Applying the proposed framework to a residential building, our results demonstrate its effectiveness in cost-efficient carbon emissions reduction. With integrated design and control optimization for DERs and electric building energy systems, the proposed framework reduces operational carbon emissions by 80% and total costs by 2.7% compared to a base case, which uses typical conventional building energy systems without DERs and control/design optimization. Separate optimization of operations control and system design cannot achieve such performance. Further scenario analyses indicate that as power grids become cleaner, the reliance on DERs can be alleviated but remain important in building carbon emission reduction under 2050 power grid scenario. Overall, as our results demonstrate, it is possible to reduce building operational carbon emissions simultaneously with net electrical load: compared to the base case, the proposed framework helps reduce the carbon emission by 80% while driving down the net electrical load from 44.1 to 19.3 kWh/m2/year.

利用分布式能源资源(DERs)实现楼宇电气化是楼宇领域去碳化的一项前景广阔的战略。考虑到运营控制与系统设计之间的相互依存关系,将技术运营控制优化与 DERs 投资优化相结合,可以经济有效地提高建筑行业的去碳化机会。本研究提出了一个多时间尺度的集成优化框架,可同时优化 DERs 和建筑电气化技术的设计和控制。研究开发了一种基于深度学习的新型建筑运行性能预测模型,以近似并取代计算成本高昂的控制优化。这有助于解决具有挑战性、难以计算的多时间尺度综合设计和控制优化问题。我们将所提出的框架应用于一栋住宅楼,结果证明了它在经济高效地减少碳排放方面的有效性。通过对 DERs 和电动建筑能源系统进行集成设计和控制优化,与使用典型传统建筑能源系统(无 DERs 和控制/设计优化)的基本情况相比,所提出的框架减少了 80% 的运行碳排放和 2.7% 的总成本。单独优化运行控制和系统设计无法实现这样的性能。进一步的情景分析表明,随着电网变得更加清洁,对 DER 的依赖可以减轻,但在 2050 年电网情景下,DER 在建筑碳减排中仍然非常重要。总之,我们的研究结果表明,在减少建筑运行碳排放的同时,还能减少净电力负荷:与基本情况相比,所提出的框架有助于减少 80% 的碳排放,同时将净电力负荷从 44.1 千瓦时/平方米/年降低到 19.3 千瓦时/平方米/年。
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引用次数: 2
Carbon abatement costs for renewable fuels in hard-to-abate transport sectors 在难以减排的运输部门使用可再生燃料的碳减排成本
Q1 ENERGY & FUELS Pub Date : 2023-10-28 DOI: 10.1016/j.adapen.2023.100156
Jonas Martin , Emil Dimanchev , Anne Neumann

Renewable fuels can help to reduce carbon emissions from transportation. To inform planning decisions, this paper estimates carbon abatement costs of replacing fossil fuels with renewable hydrogen, ammonia, or Fischer–Tropsch e-fuel in Norwegian freight transport across long-haul trucking, short-sea shipping, and medium-haul aviation. We do this by applying a holistic cost model of renewable fuel value chains. We compare abatement costs across transport sectors and analyze how policy interventions along the value chains – such as carbon pricing, subsidies, and de-risking policies – impact carbon abatement costs. We estimate abatement costs of 793–1,598 €/tCO2 in 2020 and -11–675 €/tCO2 in 2050, depending on the electricity source, transport sector, and type of fuel. A 1 €/kg reduction in the cost of hydrogen - e.g. through a subsidy - lowers present-day carbon abatement cost by 95 €/tCO2 for hydrogen-powered trucking, 133 €/tCO2 for e-fuel-powered shipping, and 143 €/tCO2 for e-fuel-powered aviation. We further show that reductions in the weighted average cost of capital materially decrease abatement cost, particularly for renewable hydrogen due to its relative capital intensity.

可再生燃料有助于减少交通运输中的碳排放。为了为规划决策提供信息,本文估算了挪威长途卡车运输、短途海运和中程航空货运中用可再生氢、氨或费托电子燃料替代化石燃料的碳减排成本。我们通过应用可再生燃料价值链的整体成本模型来做到这一点。我们比较了各个运输部门的减排成本,并分析了价值链上的政策干预(如碳定价、补贴和降低风险政策)如何影响碳减排成本。根据电力来源、运输部门和燃料类型的不同,我们估计2020年的减排成本为793 - 1598欧元/吨二氧化碳,2050年为-11-675欧元/吨二氧化碳。氢的成本每公斤降低1欧元(例如通过补贴),目前氢动力卡车的碳减排成本将降低95欧元/吨二氧化碳,电子燃料动力航运的碳减排成本将降低133欧元/吨二氧化碳,电子燃料动力航空的碳减排成本将降低143欧元/吨二氧化碳。我们进一步表明,加权平均资本成本的降低大大降低了减排成本,特别是可再生氢,因为它的相对资本强度。
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引用次数: 0
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Advances in Applied Energy
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