Smart Energy最新文献_第4页

A systematic approach to analyse methodologies for renewables-based district heating potential assessments – A categorisation and literature review 基于可再生能源的区域供热潜力评估的系统分析方法-分类和文献综述

IF 5 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-08-01 DOI: 10.1016/j.segy.2025.100201

Mohammad Saeid Atabaki , Giulia Spirito , Luis Sánchez-García , Urban Persson

District heating systems (DHS) serve as promising infrastructures to harness renewable energy for space heating and domestic hot water purposes. However, the manner in which the potential of renewable energy sources (RES) is assessed varies across sources. This study aims to synthesise knowledge on methodologies for evaluating the integration of various RES into DHS. Key aspects scrutinised in the methodologies include the dimensions addressed, the spatial approaches used, the tools and methods applied, and the overall process followed. A structured literature review process was conducted, reaching 260 documents for full-text review, encompassing scientific publications, national comprehensive assessments, and project reports. The focus has been put on six RES: heat sources for heat pumps (HPs), solar thermal, geothermal heat, biomass, power-2-heat (P2H), and surplus heat. The review highlights surplus heat as the most frequently studied source (35%). Moreover, it shows that from a technological point of view, HPs constitute an indispensable element in integrating most RES (except biomass), particularly in next-generation DHS where reduced supply temperatures enhance HP efficiency. From a methodological perspective, it is observed that spatial mapping is increasingly utilised to deal with the dispersed nature of heat sources and demands. The findings also accentuate the necessity of sector coupling to provide a holistic analysis, given either the inherent interlinkages between the DH sector and others (e.g., in P2H), the derivation of heat from other sectors (e.g., surplus heat), or the multifunctionality of certain heat sources (e.g., geothermal and biomass).

区域供热系统（DHS）是利用可再生能源用于空间供暖和家庭热水的有前途的基础设施。然而，评估可再生能源（RES）潜力的方式因来源而异。本研究旨在综合评估各种RES整合到DHS的方法方面的知识。方法中审查的关键方面包括处理的维度，使用的空间方法，应用的工具和方法，以及遵循的整体过程。进行了结构化的文献综述过程，共计260份文献进行全文综述，包括科学出版物、国家综合评估和项目报告。重点是六种可再生能源：热泵（HPs）的热源，太阳能热，地热，生物质，动力-2-热（P2H）和余热。该综述强调，余热是最常被研究的来源（35%）。此外，从技术角度来看，HP是整合大多数可再生能源（除了生物质）不可或缺的元素，特别是在下一代DHS中，降低供应温度可以提高HP效率。从方法论的角度来看，空间测绘越来越多地用于处理热源和需求的分散性。研究结果还强调了部门耦合提供整体分析的必要性，考虑到卫生部门和其他部门之间的内在联系（例如，在P2H中），来自其他部门的热量的衍生（例如，余热），或某些热源的多功能性（例如，地热和生物质）。

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引用次数: 0

The principles of energy conservation by managing facility voltage levels and reactive power flow 通过管理设备电压水平和无功功率流来节约能源的原则

IF 5.4 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-07-25 DOI: 10.1016/j.segy.2025.100197

P.K. Ngongo , A.M.A. Almaktoof , M.T.E. Kahn

Reactive power optimization and voltage control are essential for the efficient operation of power systems. Effective management of these factors reduces energy losses and improves both economic performance and system security. In South Africa, the nominal phase voltage level is set at 220V, with an allowable range between 209V and 231V (±5 %). To ensure that the supply voltage stays within this acceptable range, the grid often provides a voltage higher than the nominal 220V at which most electrical equipment is designed to operate. Consequently, the equipment consumes more power without any improvement in performance. Additionally, while the grid supplies both real and reactive power, only the real power consumed is billed. To address the cost of unbillable reactive power, a power factor penalty is implemented. The practice of controlling supply voltage levels and enhancing the power factor is known as volt-var optimization. This approach involves regulating voltage levels and reactive power to maximize energy efficiency. This paper employs a model-based Volt-var optimization technique to illustrate how facilities can reduce energy waste. The findings indicate that, for facility system losses estimated at 5 %, reducing the useable voltage from 400V nominal to 380V can achieve a percentage loss reduction of 0.487 %. This saving is directly proportional to the difference between the useable and nominal voltages. Furthermore, optimizing the power factor from 0.85 lagging to unity results in a percentage loss reduction of 1.388 %. This saving is indirectly proportional to how closely the inherent power factor approaches unity.

无功优化和电压控制是电力系统高效运行的关键。对这些因素的有效管理可以减少能源损失，提高经济性能和系统安全性。在南非，标称相电压水平设定为220V，允许范围为209V至231V（±5%）。为了确保供电电压保持在这个可接受的范围内，电网通常提供高于大多数电气设备设计运行的标称220V的电压。因此，设备消耗更多的电力，而性能却没有任何改善。此外，当电网同时提供实功率和无功功率时，只收取实际消耗的功率。为了解决不可计费的无功功率的成本，实施了功率因数惩罚。控制电源电压水平和提高功率因数的做法被称为电压无功优化。这种方法包括调节电压水平和无功功率，以最大限度地提高能源效率。本文采用基于模型的电压无功优化技术来说明设施如何减少能源浪费。研究结果表明，对于估计为5%的设施系统损耗，将可用电压从标称400V降低到380V可以实现0.487 %的损耗降低百分比。这种节省与可用电压和标称电压之间的差成正比。此外，优化功率因数从0.85滞后到统一的结果在1.388%的百分比损失减少。这种节省与固有功率因数接近统一的程度间接成正比。

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引用次数: 0

Digital twin-based smart heating system with a condensing boiler 带冷凝锅炉的数字双体智能供暖系统

IF 5.4 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-07-23 DOI: 10.1016/j.segy.2025.100198

Volodymyr Voloshchuk, Inna Bilous, Pavlo Novikov, Oleksandr Stepanets, Anastasiya Zakharchenko

Improving energy efficiency in residential space heating has a key role to play for achieving the goal of carbon-neutrality. Condensing boilers for providing heating can achieve significantly higher efficiency than conventional ones due to possibility to recover latent heat of vaporization from the flue gas. But it can be achieved when return temperature of heating system is sufficiently low (below the dew temperature of the flue gas), which directly depends on real thermal modes of the heating system. So, development of methods and tools that can use data under real operating conditions and have possibilities to find the most efficient modes is crucial for improving performance of such system. Implementation of these methods should be based on mathematical modeling or simulation. The model should be automatically fitted to current measurements. The paper presents development of a digital twin-based smart heating system, which includes a condensing boiler. The proposed framework of a digital twin (DT) takes advantage of the latest technologies in information technology, which could be applied for real-time information interchange between the physical system and its virtual copy to achieve energy efficient operation modes. A methodology and a user-friendly interface, which are easy to use and navigate, have been developed for estimation of energy efficient solutions in the studied system. It has been demonstrated that the biggest increase in boiler efficiency (by 6.6 %) can be achieved by switching to low-temperature heating systems. Applying intermittent heating is in second place in terms of the possibility of increasing boiler efficiency (up to 1.5 %).

提高住宅空间供暖的能源效率对于实现碳中和的目标具有关键作用。由于可以从烟气中回收汽化潜热，用于供热的冷凝锅炉可以获得比传统锅炉更高的效率。但在供热系统回温足够低（低于烟气露温）的情况下可以实现，这直接取决于供热系统的实际热模式。因此，开发能够在实际操作条件下使用数据并有可能找到最有效模式的方法和工具对于提高此类系统的性能至关重要。这些方法的实现应基于数学建模或仿真。该模型应自动适应当前的测量值。本文介绍了一种基于数字孪生的智能供暖系统的开发，该系统包括一个冷凝锅炉。提出的数字孪生（DT）框架利用了信息技术的最新技术，可用于物理系统与其虚拟副本之间的实时信息交换，以实现节能的操作模式。开发了一种方法和用户友好界面，易于使用和导航，用于估计所研究系统中的节能解决方案。已经证明，锅炉效率的最大增加（6.6%）可以通过切换到低温加热系统来实现。在提高锅炉效率的可能性方面，应用间歇加热排在第二位（高达1.5%）。

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引用次数: 0

Solar prosumage under different pricing regimes: Interactions with the transmission grid 不同定价制度下的太阳能产量：与输电网的相互作用

IF 5.4 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-07-15 DOI: 10.1016/j.segy.2025.100193

Dana Kirchem , Mario Kendziorski , Enno Wiebrow , Wolf-Peter Schill , Claudia Kemfert , Christian von Hirschhausen

Residential electricity consumers equipped with photovoltaic (PV) systems and battery storage, also referred to as solar prosumers, are transforming electricity markets. While previous research has dealt with various aspects of solar prosumage, dedicated analyses of their interactions with the transmission grid under varying tariff designs are sparse. We explore the influence of different pricing regimes on prosumer investment and dispatch decisions and their subsequent impact on the transmission grid. Using an integrated modeling approach that combines two open-source dispatch, investment and grid models, we simulate prosumage behavior in Germany’s electricity market under real-time or time-invariant pricing, as well as under zonal or nodal pricing. Our findings show that zonal pricing favors prosumer investments, while time-invariant pricing rather hinders it. In comparison, regional solar availability emerges as a larger driver for rooftop PV investments. The impact of prosumer strategies on grid congestion remains limited within the scope of our model-setup, in which home batteries cannot be used for energy arbitrage.

配备光伏（PV）系统和电池存储的住宅电力消费者，也被称为太阳能产消者，正在改变电力市场。虽然以前的研究已经处理了太阳能发电的各个方面，但对它们在不同电价设计下与输电网相互作用的专门分析却很少。我们探讨了不同定价制度对产消投资和调度决策的影响，以及它们对输电网的后续影响。采用集成的建模方法，结合了两个开源调度、投资和电网模型，我们模拟了实时或定常定价以及分区或节点定价下德国电力市场的消费行为。我们的研究结果表明，区域定价有利于生产消费者投资，而时不变定价反而阻碍了生产消费者的投资。相比之下，区域太阳能可用性成为屋顶光伏投资的更大推动力。在我们的模型设置范围内，产消策略对电网拥堵的影响仍然有限，在这种情况下，家用电池不能用于能源套利。

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引用次数: 0

Decarbonizing semiconductor manufacturing: cost-competitiveness of PV-based green hydrogen production 脱碳半导体制造：基于pv的绿色制氢的成本竞争力

IF 5.4 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-06-29 DOI: 10.1016/j.segy.2025.100192

Davide Trapani, Paolo Marocco, Marta Gandiglio, Massimo Santarelli

Hard-to-abate industries heavily depend on fossil fuels and low-cost fossil-based feedstocks, significantly contributing to energy-related CO₂ emissions. Therefore, a cost-effective transition towards low-carbon solutions becomes imperative. This study investigates the cost-competitiveness of decarbonizing semiconductor manufacturing by switching from conventional grey hydrogen supply to on-site green hydrogen production in a power-to-hydrogen (P-t-H) system. A silicon wafer production facility with an annual hydrogen demand of approximately 110 tonnes is considered as a case study. An optimization framework based on a metaheuristic approach is developed for the cost-optimal design of the P-t-H system, while the ε-constraint technique is applied to investigate multiple decarbonization targets. The findings indicate that fully relying on grey hydrogen remains the most cost-effective strategy, resulting in a levelized cost of hydrogen (LCOH) of 4 €/kg but emitting 1045 tonnes of CO₂ annually. As grey hydrogen consumption is limited to reduce CO₂ emissions, the LCOH increases exhibiting distinct trends. For decarbonization targets up to 70 %, the LCOH steadily rises to 6.10 €/kg, while stricter CO₂ emissions constraints cause a steeper increase in the hydrogen production cost, reaching 10.51 €/kg in the fully decarbonized scenario. Achieving complete decarbonization requires scaling up the P-t-H components, particularly the pressurized storage tank, which becomes essential for a reliable hydrogen supply. Grid electricity import can prevent the system oversizing, thus boosting the cost-competitiveness of green hydrogen production. Conventional hydrogen supply remains cost-efficient for grey hydrogen purchase prices up to 6 €/kg, while above this threshold integrating on-site green hydrogen production becomes beneficial.

难以减排的行业严重依赖化石燃料和低成本的化石原料，大大增加了与能源相关的二氧化碳排放。因此，向低碳解决方案的低成本转型势在必行。本研究探讨了在电力制氢（P-t-H）系统中，从传统的灰色氢供应转向现场绿色氢生产的脱碳半导体制造的成本竞争力。一个硅晶圆生产设施，其年氢需求约为110吨，被视为一个案例研究。提出了一种基于元启发式方法的优化框架，用于P-t-H系统的成本优化设计，并应用ε约束技术对多个脱碳目标进行了研究。研究结果表明，完全依赖灰氢仍然是最具成本效益的策略，导致氢的平均成本（LCOH）为4欧元/公斤，但每年排放1045吨二氧化碳。由于减少二氧化碳排放限制了灰氢的消耗，LCOH呈现出明显的增长趋势。对于高达70%的脱碳目标，LCOH稳步上升至6.10欧元/千克，而更严格的二氧化碳排放限制导致制氢成本急剧上升，在完全脱碳的情况下达到10.51欧元/千克。实现完全脱碳需要扩大P-t-H组件，特别是加压储罐，这对于可靠的氢供应至关重要。电网电力导入可以防止系统过大，从而提高绿色制氢的成本竞争力。当灰色氢气购买价格高达6欧元/公斤时，传统的氢气供应仍然具有成本效益，而超过这一门槛，整合现场绿色氢气生产将是有益的。

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引用次数: 0

IoT-Driven smart energy management with a closed PEMFC-PEMEC loop: A sustainable approach to decarbonizing flexible buildings in London 物联网驱动的智能能源管理与封闭的PEMFC-PEMEC循环：伦敦柔性建筑脱碳的可持续方法

IF 5.4 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-06-28 DOI: 10.1016/j.segy.2025.100191

Araz Emami, Ata Chitsaz, Amirali Nouri

Buildings with energy-flexible technologies such as electric heating, smart DSM, and advanced PEMFC systems, offer innovative ways to reduce grid dependency during peak demand and enhance energy resilience. By aligning variable spot price tariffs with intelligent control strategies based on environmental conditions, occupancy, and energy pricing, these systems help lower peak loads and promote sustainable energy use. This study proposes an integrated, digitized energy flexible system combining demand-side management (DSM), smart controls, and a proton exchange membrane fuel cell (PEMFC) to enhance building energy performance under variable electricity pricing. Using TRNSYS simulations of a four-story UK building, the model incorporates machine learning and IoT data (occupancy, weather, and energy tariffs) to forecast energy demands and guide system operation. Sensitivity analyses and surface plots identified optimal operating points for electrolyzer temperature (around 70–75 °C) and ambient conditions (above 20 °C), which maximized hydrogen production and improved PEMEC efficiency (up to 84 %). The system maintained indoor temperatures between 17 and 21 °C and hot water and underfloor heating within 45 °C–55 °C, while reducing electricity usage during peak periods. These results highlight the potential of intelligent, flexible control strategies to achieve cost savings, thermal comfort, and improved energy resilience in smart buildings.

采用电供暖、智能DSM和先进PEMFC系统等能源柔性技术的建筑，提供了创新的方法，可以在高峰需求期间减少对电网的依赖，并增强能源弹性。通过将可变的现货电价与基于环境条件、占用率和能源定价的智能控制策略相结合，这些系统有助于降低峰值负荷，促进可持续能源使用。本研究提出了一个集成的、数字化的能源柔性系统，结合了需求侧管理（DSM）、智能控制和质子交换膜燃料电池（PEMFC），以提高可变电价下的建筑能源性能。该模型利用TRNSYS对英国一栋四层建筑的模拟，结合了机器学习和物联网数据（入住率、天气和能源关税）来预测能源需求并指导系统运行。灵敏度分析和表面图确定了电解槽温度（约70-75°C）和环境条件（高于20°C）的最佳工作点，从而最大限度地提高了氢气产量并提高了PEMEC效率（高达84%）。该系统将室内温度保持在17至21°C之间，热水和地板采暖保持在45°C至55°C之间，同时减少高峰时段的用电量。这些结果突出了智能、灵活的控制策略在智能建筑中实现成本节约、热舒适和提高能源弹性方面的潜力。

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引用次数: 0

Electric vehicle charging emissions under different control strategies and temporal resolutions: Case study for Australia 不同控制策略和时间分辨率下的电动汽车充电排放：澳大利亚案例研究

IF 5.4 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-06-25 DOI: 10.1016/j.segy.2025.100190

Kriengsak Fungyai , Rob Passey , Baran Yildiz

The increasing adoption of electric vehicles (EVs) presents both challenges and opportunities for reducing greenhouse gas (GHG) emissions. While EVs are essential for decarbonising the transport sector, the emissions from charging vary greatly depending on the generation mix at the time. This study investigates the impact of various EV charging strategies on GHG emissions in different regions in the Australian National Electricity Market (NEM). The study focuses on four key charging strategies–Control Tariff, Timer, Solar Soak, and Convenience Charging. Using real-world data, the analysis evaluates both average and marginal emissions across regions with varying levels of renewable energy integration. Sensitivity analysis showed that coarser temporal resolution in emissions calculations can lead to variances of up to 6.3 %, emphasising the importance of using higher resolution data when available. It was found that the Solar Soak strategy is the most effective in minimising EV charging emissions and can also help with challenges associated with increasing solar exports in the distribution network. The choice between average and marginal emissions intensity factors is also critical in determining outcomes. In Tasmania and South Australia, where renewable energy sources dominate, the use of marginal emission factors resulted in higher EV charging emissions than average emissions due to their reliance on coal and gas as the marginal generators. The sensitivity analysis carried out with emissions data between 2019 and 2023 revealed a negative relationship between renewable energy fraction and emissions intensity and highlighted the importance of aligning EV charging with high renewable generation periods to achieve maximum GHG reductions.

电动汽车（ev）的日益普及为减少温室气体（GHG）排放带来了挑战和机遇。虽然电动汽车对交通运输部门的脱碳至关重要，但充电产生的排放因当时的发电组合而有很大差异。本研究调查了澳大利亚国家电力市场（NEM）不同地区的各种电动汽车充电策略对温室气体排放的影响。该研究重点研究了四种关键的充电策略——控制电价、定时充电、太阳能充电和便利充电。利用真实世界的数据，该分析评估了不同可再生能源整合水平地区的平均和边际排放量。敏感性分析表明，排放计算中较粗的时间分辨率可能导致高达6.3%的差异，这强调了在可用时使用更高分辨率数据的重要性。研究发现，太阳能浸泡策略在最大限度地减少电动汽车充电排放方面是最有效的，并且还可以帮助应对与配电网络中增加太阳能出口相关的挑战。在平均和边际排放强度因子之间的选择对于决定结果也至关重要。在可再生能源占主导地位的塔斯马尼亚州和南澳大利亚州，由于依赖煤炭和天然气作为边际发电机，使用边际排放因子导致电动汽车充电排放高于平均排放量。利用2019年至2023年的排放数据进行的敏感性分析显示，可再生能源比例与排放强度之间存在负相关关系，并强调了将电动汽车充电与高可再生能源发电周期相结合以实现最大温室气体减排的重要性。

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引用次数: 0

Exploring the impact of green finance, technological innovation, mineral resources, and carbon tax on the green energy transition 探讨绿色金融、技术创新、矿产资源、碳税对绿色能源转型的影响

IF 5.4 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-06-25 DOI: 10.1016/j.segy.2025.100189

Mei Dong , Cai Li , Agyemang Kwasi Sampene

Achieving global carbon neutrality necessitates a decisive transition to clean energy sources. This study examines the dynamic relationships between green finance, mineral resources, technological innovation, carbon taxation, and the green energy transition (GET) within the Nordic energy market from 1995 to 2021. Motivated by the urgent need to understand the key drivers and barriers to sustainable energy adoption, this study employed a robust panel data technique, including Driscoll and Kraay standard errors, cross-sectional dependency tests, and heterogeneity tests, to ensure reliable and generalizable findings. Results from the study confirmed that mineral resources, technological innovation, and green finance play a significant role in promoting the shift to clean energy. In contrast, a carbon tax may negatively hinder this transition by increasing operational costs for energy firms. Furthermore, the causality analysis reveals a unidirectional influence of carbon tax, mineral resources, and technological innovation on GET, as well as a bidirectional relationship between green finance and GET. These findings underscore the importance of carefully designed carbon tax policies and increased support for innovation and green finance to drive the clean energy transition effectively. Additionally, enhanced support for technological innovation, sustainable mineral resource management, and green finance initiatives is essential for accelerating the clean energy transition. This study offers novel empirical insights with significant policy implications to inform Nordic and global efforts toward sustainable energy futures.

要实现全球碳中和，就必须果断地向清洁能源过渡。本研究考察了1995年至2021年北欧能源市场中绿色金融、矿产资源、技术创新、碳税和绿色能源转型之间的动态关系。由于迫切需要了解可持续能源采用的关键驱动因素和障碍，本研究采用了强大的面板数据技术，包括Driscoll和Kraay标准误差、横断面依赖检验和异质性检验，以确保可靠和可推广的结果。研究结果证实，矿产资源、技术创新和绿色金融在推动清洁能源转型中发挥着重要作用。相比之下，碳税可能会增加能源公司的运营成本，从而对这种转变产生负面影响。因果关系分析表明，碳税、矿产资源和技术创新对碳交易的影响是单向的，绿色金融对碳交易的影响是双向的。这些发现强调了精心设计碳税政策和加大对创新和绿色金融支持的重要性，以有效推动清洁能源转型。此外，加强对技术创新、可持续矿产资源管理和绿色金融倡议的支持对于加快清洁能源转型至关重要。本研究提供了新颖的实证见解，具有重要的政策意义，为北欧和全球朝着可持续能源未来的努力提供信息。

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引用次数: 0

Integrating bottom-up GIS and machine learning models for spatial-temporal analysis of electric mobility impact on power system 基于自底向上GIS和机器学习模型的电动交通对电力系统影响的时空分析

IF 5.4 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-06-20 DOI: 10.1016/j.segy.2025.100185

Corrado Maria Caminiti, Davide Fratelli, Matteo Spiller, Aleksandar Dimovski, Marco Merlo

The ongoing electrification in the light-duty transportation sector represents a pivotal shift that deeply influences electricity distribution networks’ operations, introducing a peculiar demand profile characterised by spatial and temporal variability. To address these challenges posed by the increasing adoption of Electric Vehicles (EVs), this work integrates a Machine Learning (ML) model for the vehicle selection procedure in a holistic Spatial-Temporal Model (STM) that accurately simulates the most typical stochastic behaviour within the transportation and electricity networks. The methodology assesses traffic behaviour, evaluates the grid impact of charging processes, and extends the analysis to flexibility services, particularly the provision of primary frequency regulation. The methodology is applied to the Lombardy region in Italy, adopting the 2030 e-mobility scenario defined by policymakers as a reference. This framework selects EVs diverting from linear probabilistic extraction models based on penetration rates by exploiting behavioural patterns and the socio-economic characterisation of EV drivers. Relying purely on open-source data, the work demonstrates the frequency regulation potential of EVs fostered by smart charging algorithms, which increase the power band available for grid services. The results of the procedure provide actionable insights for grid operators and urban planners, bridging the gap between transportation and electrical infrastructure.

轻型运输部门正在进行的电气化代表了一个关键的转变，它深刻地影响着配电网络的运营，引入了一个以空间和时间变化为特征的特殊需求剖面。为了解决电动汽车（ev）日益普及带来的这些挑战，本研究将用于车辆选择过程的机器学习（ML）模型集成到一个整体时空模型（STM）中，该模型精确模拟了交通和电力网络中最典型的随机行为。该方法评估交通行为，评估收费过程对电网的影响，并将分析扩展到灵活性服务，特别是提供主要频率调节。该方法应用于意大利伦巴第地区，采用政策制定者定义的2030年电动交通情景作为参考。该框架通过利用电动汽车驾驶员的行为模式和社会经济特征，从基于渗透率的线性概率提取模型中选择电动汽车。纯粹依靠开源数据，这项工作证明了智能充电算法促进电动汽车的频率调节潜力，这增加了电网服务的可用功率频带。该程序的结果为电网运营商和城市规划者提供了可行的见解，弥合了交通和电力基础设施之间的差距。

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引用次数: 0

Assessing the role of storage and thermoelectric plants in the energy transition: a short- and medium-term scenario analysis with Italy as a case study 评估储能和热电厂在能源转型中的作用：以意大利为例的短期和中期情景分析

IF 5.4 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-06-13 DOI: 10.1016/j.segy.2025.100186

Andrea Franzoso, Michel Noussan, Paolo Marocco, Marco Badami, Gabriele Fambri, Marta Gandiglio

Global warming is pushing many countries worldwide to adopt decarbonization strategies aimed at reducing the dependence on fossil fuels. The successful development of these strategies critically depends on the ability to model and evaluate alternative options, thereby enabling policymakers to identify and implement the most effective solutions. In this context, the present study introduces a detailed operational analysis of the Italian energy system under the 2030 and 2040 horizons, based on authoritative scenarios developed by national transmission system operators. The primary goal is to complement these scenarios by highlighting short- and medium-term operational challenges, particularly concerning the role of thermoelectric power plants and electricity storage systems. To this aim, a set of key performance indicators is introduced to systematically assess scenario impacts. The analysis captures the effects of rising electricity demand, driven by the diffusion of electric vehicles and heat pumps, on system operation, highlighting a projected 25% increase in peak demand along with an 8.3% increase in peak thermoelectric generation. Despite a marked decline in the capacity factor of thermoelectric power plants (from 0.54 to 0.18), these units remain essential to meet demand during extended periods of low renewable generation, with peak capacity requirements remaining close to 40 GW. The results also underscore the role of electricity storage in providing short-term flexibility. However, the benefits of additional storage become marginal beyond 230 GWh of capacity.

全球变暖正在推动世界上许多国家采取旨在减少对化石燃料依赖的脱碳战略。这些战略的成功制定在很大程度上取决于对备选方案进行建模和评估的能力，从而使决策者能够确定和实施最有效的解决方案。在此背景下，本研究基于国家输电系统运营商制定的权威方案，对2030年和2040年的意大利能源系统进行了详细的运行分析。主要目标是通过强调短期和中期运营挑战，特别是关于热电厂和电力储存系统的作用，来补充这些情景。为此目的，引入了一套关键绩效指标来系统地评估情景影响。该分析抓住了由电动汽车和热泵的普及所驱动的电力需求上升对系统运行的影响，强调了预计峰值需求将增长25%，峰值热电发电量将增长8.3%。尽管热电厂的容量系数明显下降（从0.54降至0.18），但这些机组仍然是满足低可再生能源发电长期需求的必要条件，峰值容量需求仍接近40吉瓦。研究结果还强调了电力储存在提供短期灵活性方面的作用。然而，超过230吉瓦时的容量，额外存储的好处就变得微不足道了。

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引用次数: 0