Smart Energy最新文献

The future of Danish offshore wind: Integration and export strategies for energy hubs in the North Sea 丹麦海上风电的未来：北海能源中心的整合和出口战略

IF 5 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-12-26 DOI: 10.1016/j.segy.2025.100224

Hamza Abid , Brian Vad Mathiesen , Iva Ridjan Skov , Poul Alberg Østergaard

Denmark's abundant wind resources and expertise in offshore wind position it to support Europe's decarbonisation and energy security goals, especially as Europe seeks to diversify energy sources and invest in hydrogen and hydrogen-derived fuels. To achieve these objectives, Denmark and other Northern European countries aim to establish large-scale offshore energy hubs. This study examines two key aspects: (1) optimal infrastructure for connecting energy hubs to the mainland, and (2) the most advantageous export strategy, focusing on hydrogen or hydrogen-derived Sustainable Aviation Fuel (e-SAF) for the German market. The techno-economic analysis evaluates High Voltage Direct Current (HVDC) cables and hydrogen pipelines, assessing the Levelized Cost of Hydrogen (LCOH) for offshore and onshore electrolysis. Sensitivity analyses explore the economic benefits of utilizing excess heat in district heating. Using EnergyPLAN, a system-level assessment compares a decarbonized Danish energy system in 2045 with scenarios involving hydrogen and e-SAF exports. Results show that onshore electrolysis with HVDC is preferable for distances under 350 km, leveraging excess heat utilization for district heating and lower infrastructure costs. Hydrogen pipelines are advantageous only for greater distances. Utilizing excess heat from onshore electrolysis can reduce the LCOH by 10–30 %, depending on the selling price and utilization of heat. Direct hydrogen exports become profitable when hydrogen prices exceed 2.7 €/kg (80 €/MWh), while e-SAF export is favourable above 170 €/MWh (1.65 €/litre), aligning with fossil jet fuel competitiveness under carbon taxation. These findings underscore Denmark's potential to lead in renewable energy exports while bolstering European energy security and decarbonisation.

丹麦丰富的风能资源和海上风电专业知识使其能够支持欧洲的脱碳和能源安全目标，特别是在欧洲寻求能源多样化并投资氢和氢衍生燃料的情况下。为了实现这些目标，丹麦和其他北欧国家打算建立大规模的海上能源中心。本研究考察了两个关键方面：(1)连接能源枢纽与大陆的最佳基础设施；(2)最有利的出口战略，重点是面向德国市场的氢或氢衍生可持续航空燃料（e-SAF）。技术经济分析评估了高压直流（HVDC）电缆和氢气管道，评估了海上和陆上电解的氢气平准化成本。敏感性分析探讨了集中供热利用余热的经济效益。使用EnergyPLAN，系统级评估比较了2045年丹麦脱碳能源系统与涉及氢和e-SAF出口的情景。结果表明，在350公里以下的距离内，陆上电解与HVDC更可取，可以利用多余的热量进行区域供热，并降低基础设施成本。氢气管道只有在更远的距离上才有优势。根据销售价格和热量利用率的不同，利用陆上电解产生的余热可以将LCOH降低10 - 30%。当氢价格超过2.7欧元/公斤（80欧元/兆瓦时）时，直接氢出口就有利可图，而e-SAF出口高于170欧元/兆瓦时（1.65欧元/升）则有利，与碳税下的化石航空燃料竞争力保持一致。这些发现强调了丹麦在促进欧洲能源安全和脱碳的同时，在可再生能源出口方面处于领先地位的潜力。

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引用次数: 0

A mixed-integer linear programming model for BESS sizing optimization considering aging effects and emission costs 考虑老化和排放成本的BESS尺寸优化混合整数线性规划模型

IF 5 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-12-26 DOI: 10.1016/j.segy.2025.100225

Nguyen Quoc Minh, Tran Van Dai, Pham Minh Hoang, Pham Hong Hai, Le Thi Minh Chau

With the rapid expansion of renewable energy sources (RES), battery energy storage systems (BESS) have become essential for ensuring grid stability, reliability, and operational efficiency. However, optimizing BESS sizing is a complex challenge that requires balancing economic, technical, and environmental factors while considering the long-term impact of battery degradation and replacement costs. This study presents a comprehensive optimization model for determining the optimal capacity of BESS within a microgrid, explicitly incorporating battery aging effects and associated lifecycle costs. The proposed model employs a mixed-integer linear programming (MILP) approach to minimize the total system cost, which includes investment, operation, and replacement expenses, while ensuring that load demand is met, RES integration is maximized, and system reliability is maintained. By considering the degradation of BESS performance over time, the model provides a more accurate estimation of long-term economic and technical feasibility. Simulation results validate the effectiveness of the model in optimizing BESS sizing and installation costs. Additionally, the study evaluates different BESS technologies and examines the impact of various factors, such as RES penetration and emission costs on overall system performance. The findings offer valuable insights into developing cost-effective BESS operation schedules and management strategies, contributing to improved energy efficiency and sustainability in microgrid applications.

随着可再生能源（RES）的快速发展，电池储能系统（BESS）已成为确保电网稳定性、可靠性和运行效率的关键。然而，优化BESS尺寸是一项复杂的挑战，需要平衡经济、技术和环境因素，同时考虑电池退化和更换成本的长期影响。本研究提出了一个综合优化模型，用于确定微电网中BESS的最佳容量，明确地考虑了电池老化效应和相关的生命周期成本。该模型采用混合整数线性规划（MILP）方法，在保证满足负荷需求、RES集成最大化和保持系统可靠性的前提下，使包括投资、运行和更换费用在内的系统总成本最小化。通过考虑BESS性能随时间的退化，该模型提供了对长期经济和技术可行性的更准确的估计。仿真结果验证了该模型在优化BESS尺寸和安装成本方面的有效性。此外，该研究还评估了不同的BESS技术，并检查了各种因素的影响，例如RES渗透和排放成本对整体系统性能的影响。研究结果为制定具有成本效益的BESS运行计划和管理策略提供了宝贵的见解，有助于提高微电网应用的能源效率和可持续性。

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引用次数: 0

Bridging theory and practice: Building a coordinated offshore grid in the North Sea and United States Eastern Seaboard 衔接理论与实践：构建北海与美国东海岸协同海上电网

IF 5 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-12-15 DOI: 10.1016/j.segy.2025.100223

Tyler A. Hansen , Ben Hinchliffe, Elizabeth J. Wilson

Offshore wind development in Europe's North Sea and the United States East Coast is central to decarbonization, but achieving ambitious deployment targets requires fundamentally changing how projects connect to the grid. While point-to-point (“radial”) connections enabled early growth, sector expansion to hundreds of gigawatts is increasingly costly, socially and environmentally disruptive, and dependent on extensive onshore reinforcements. Coordinated offshore transmission systems—where multiple projects share offshore and onshore transmission assets—show enormous promise to address these challenges and enable smarter energy systems, yet real-world implementation has proved slow and fragmented. Only a single project, integrating under 1 GW of offshore wind, has been completed. To examine this gap, this paper focuses on the institutional contexts that shape implementation, conducting a comparative case study of six jurisdictions—Denmark, Belgium, and the United Kingdom in the North Sea; and New Jersey, New York, and Massachusetts in the United States. Drawing on a literature review of conceptual and modeling studies and document analysis of policy, regulatory, and planning materials, this research compares the theoretical promise of coordinated transmission with real-world implementation efforts. The analysis shows that while implementation efforts are underway in all six jurisdictions, accelerating and scaling them requires addressing three intersecting institutional challenges: (1) developing coordinated offshore transmission systems amid fragmented authority and without an established regional plan, (2) legitimizing and incentivizing large upfront investments for benefits that are delayed and dispersed, and (3) building resilience amidst political and macroeconomic shocks. The paper concludes with a research agenda to explore potential solutions.

欧洲北海和美国东海岸的海上风电开发是脱碳的核心，但要实现雄心勃勃的部署目标，需要从根本上改变项目与电网的连接方式。虽然点对点（“放射状”）连接实现了早期的增长，但行业扩张到数百吉瓦的成本越来越高，对社会和环境造成破坏，并且依赖于广泛的陆上加固。协调的海上输电系统（多个项目共享海上和陆上输电资产）显示出解决这些挑战和实现更智能能源系统的巨大希望，但实际实施速度缓慢且分散。只有一个项目完成，整合了不到1吉瓦的海上风电。为了研究这一差距，本文将重点放在影响实施的制度背景上，对六个司法管辖区（丹麦、比利时和北海的英国）进行了比较案例研究；以及美国的新泽西、纽约和马萨诸塞州。通过对概念和模型研究的文献回顾，以及对政策、监管和规划材料的文件分析，本研究将协调传输的理论前景与现实世界的实施努力进行了比较。分析表明，虽然所有六个司法管辖区的实施工作都在进行中，但加速和扩大实施需要解决三个相互交叉的制度挑战：(1)在权力分散且没有既定区域计划的情况下发展协调的海上输电系统；(2)合法化和激励大规模的前期投资，以获得延迟和分散的收益；(3)在政治和宏观经济冲击中建立弹性。本文最后提出了一个研究议程，以探索潜在的解决方案。

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引用次数: 0

Forecasting day-ahead hydropower bids in the colombian electricity market: A two-stage machine learning framework 预测哥伦比亚电力市场的水电报价：一个两阶段的机器学习框架

IF 5 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-12-13 DOI: 10.1016/j.segy.2025.100221

Laura Herrera-Mejía, Carlos D. Hoyos, David La Rotta, Yissel Mejía, John Castillo

Forecasting day-ahead energy prices in Colombia is challenging, as bids are shaped not only by hydrology and demand but also by strategic bidding under evolving regulatory and economic conditions. We develop a Machine Learning (ML) framework to forecast day-ahead bids of individual hydroelectric plants in the National Interconnected System (SIN), using plant-specific models that capture operational and strategic heterogeneity. To our knowledge, this is the first study to develop plant-specific ML models for Colombian hydro bidding.

The framework employs a two-stage architecture: (i) a classifier predicts whether a plant will bid at the regulatory minimum, and (ii) a regression model estimates the actual bid otherwise. Using daily data from XM (2016–2025), we benchmark multiple algorithms—including XGBoost, Random Forest, Gradient Boosting, MLP, and stacked ensembles.

Across plants, the framework achieves average F1-scores above 0.90 for classification, and regression errors in the range MAE = 1.5–3.0 COP/kWh (normalized by regulatory floor). Tercile classification accuracy exceeds 70% for key strategic plants such as Guavio and San Carlos, indicating strong ordinal predictive skill even under volatile conditions. The models perform particularly well for plants with stable bidding patterns, while highly intermittent plants (e.g. Porce II & III) remain harder to anticipate.

These results demonstrate that ML methods can capture mid-term gradients and relative positioning of competitor bids, providing actionable insights for market operators and traders. Future extensions should integrate contextual data—portfolio composition, regulatory signals, or sentiment indicators—to improve forecast robustness in behaviorally complex markets.

预测哥伦比亚未来一天的能源价格具有挑战性，因为出价不仅受水文和需求的影响，还受不断变化的监管和经济条件下的战略出价的影响。我们开发了一个机器学习（ML）框架来预测国家互联系统（SIN）中单个水力发电厂的提前报价，使用特定于工厂的模型来捕捉运营和战略异质性。据我们所知，这是第一个为哥伦比亚水电招标开发特定电厂ML模型的研究。该框架采用两阶段架构：(i)分类器预测电厂是否会以监管最低出价，（ii）回归模型估计实际出价否则。利用XM（2016-2025）的日常数据，我们对多种算法进行了基准测试，包括XGBoost、随机森林、梯度增强、MLP和堆叠集成。在所有工厂中，该框架的分类平均f1得分高于0.90，回归误差范围为MAE = 1.5-3.0 COP/kWh（按监管下限归一化）。Guavio和San Carlos等关键战略工厂的Tercile分类准确率超过70%，表明即使在波动条件下也具有较强的顺序预测能力。该模型对具有稳定投标模式的电厂表现得特别好，而高度间歇性电厂（如Porce II和III）仍然难以预测。这些结果表明，机器学习方法可以捕捉竞争对手出价的中期梯度和相对定位，为市场运营商和交易者提供可操作的见解。未来的扩展应整合上下文数据-投资组合，监管信号或情绪指标-以提高行为复杂市场的预测稳健性。

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引用次数: 0

A methodological framework for identifying District Heating Networks in Germany by utilizing the census data 利用人口普查数据确定德国区域供热网络的方法框架

IF 5 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-12-06 DOI: 10.1016/j.segy.2025.100218

Kai Droste, Luca Döring, Jonas Klingebiel, Rahul Karuvingal, Dirk Müller

In this study, we present a methodological framework to identify the spatial position and heat demand of District Heating Networks (DHNs) for residential buildings in Germany by utilizing the census dataset for 2022. A clustering approach is used to locate DHNs and further datasets are included to derive and evaluate additional characteristics. A top-down calibration is applied to match the heat demand of the identified networks with validation data for 2022 from the Federal Statistical Office of Germany.

In total, 8,684 areas of presumed DHNs could be identified in Germany. 90 % of the demand is covered by about 10.87 % of the DHNs. The resulting dataset is published under the name District Heating Networks Dataset from Clustered Census Data (AixDHN)¹ on GitHub.

To demonstrate the application of the AixDHN dataset, a use case is presented in which the potential of Shallow Geothermal Collectors (SGCs) for supplying the identified district heating grids is evaluated. The use case reveals a technical potential of approximately 15.31 TWh/a for SGCs in Germany, supplying the heat for domestic buildings connected to the DHNs.

The AixDHN dataset provides a spatially detailed, transparent basis and enables the evaluation of the potential of further renewable heat sources for integration into DHNs. The methodology’s strengths lie in its robust, generalized, and systematic approach, which makes it applicable throughout Germany without any further research on a regional level. It may act as a tool to support the planning and transformation of the heating sector towards renewable sources as well as municipal heat planning on a broad scope.

When cooling applications are addressed alongside heating, the economic viability of cold DHNs can be significantly improved, particularly enabling new applications in mixed-use areas that remain attractive even with lower heat densities.

在这项研究中，我们提出了一个方法框架，利用2022年的人口普查数据集，确定德国住宅建筑区域供热网络（dhn）的空间位置和热需求。使用聚类方法来定位dhn，并包括进一步的数据集来派生和评估其他特征。采用自上而下的校准方法，将已确定的管网的热需求与德国联邦统计局2022年的验证数据进行匹配。在德国，总共可以确定8,684个假定的dhn区域。约10.87%的dhn覆盖了90%的需求。结果数据集在GitHub上以“集中普查数据（AixDHN）1区域供热网络数据集”的名称发布。为了演示AixDHN数据集的应用，提出了一个用例，其中评估了浅层地热集热器（SGCs）为确定的区域供热网提供服务的潜力。该用例显示，德国SGCs的技术潜力约为15.31太瓦时/年，为连接到dhn的住宅建筑提供热量。AixDHN数据集提供了一个空间详细、透明的基础，并能够评估进一步可再生热源整合到dhn的潜力。该方法的优势在于其稳健、普遍和系统的方法，这使得它适用于全德国，而无需在区域层面进行进一步研究。它可以作为一种工具，支持供热部门向可再生能源的规划和转变，以及广泛的市政供热规划。当冷却应用与加热一起解决时，冷dhn的经济可行性可以显着提高，特别是在混合用途区域的新应用，即使在较低的热密度下仍然具有吸引力。

{"title":"A methodological framework for identifying District Heating Networks in Germany by utilizing the census data","authors":"Kai Droste, Luca Döring, Jonas Klingebiel, Rahul Karuvingal, Dirk Müller","doi":"10.1016/j.segy.2025.100218","DOIUrl":"10.1016/j.segy.2025.100218","url":null,"abstract":"<div><div>In this study, we present a methodological framework to identify the spatial position and heat demand of District Heating Networks (DHNs) for residential buildings in Germany by utilizing the census dataset for 2022. A clustering approach is used to locate DHNs and further datasets are included to derive and evaluate additional characteristics. A top-down calibration is applied to match the heat demand of the identified networks with validation data for 2022 from the Federal Statistical Office of Germany.</div><div>In total, 8,684areas of presumed DHNs could be identified in Germany. 90% of the demand is covered by about 10.87% of the DHNs. The resulting dataset is published under the name District Heating Networks Dataset from Clustered Census Data (AixDHN)<span><span><sup>1</sup></span></span> on GitHub.</div><div>To demonstrate the application of the AixDHN dataset, a use case is presented in which the potential of Shallow Geothermal Collectors (SGCs) for supplying the identified district heating grids is evaluated. The use case reveals a technical potential of approximately 15.31TWh/a for SGCs in Germany, supplying the heat for domestic buildings connected to the DHNs.</div><div>The AixDHN dataset provides a spatially detailed, transparent basis and enables the evaluation of the potential of further renewable heat sources for integration into DHNs. The methodology’s strengths lie in its robust, generalized, and systematic approach, which makes it applicable throughout Germany without any further research on a regional level. It may act as a tool to support the planning and transformation of the heating sector towards renewable sources as well as municipal heat planning on a broad scope.</div><div>When cooling applications are addressed alongside heating, the economic viability of cold DHNs can be significantly improved, particularly enabling new applications in mixed-use areas that remain attractive even with lower heat densities.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"21 ","pages":"Article 100218"},"PeriodicalIF":5.0,"publicationDate":"2025-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145738405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A decision support tool for waste heat to heat recovery technologies in industrial sectors 工业部门废热到热回收技术的决策支持工具

IF 5 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-12-02 DOI: 10.1016/j.segy.2025.100219

Mohamed Mostafa , Arman Ashabi , Andriy Hryshchenko , Ken Bruton , Dominic T.J. O'Sullivan

Industrial waste heat-to-heat recovery directly repurposes thermal energy for on-site duties, avoiding conversion losses and fuel consumption. This paper presents a decision-support tool that screens and ranks thirteen heat-to-heat technologies: indirect heat exchangers, recuperators/regenerators, heat pipes, thermal storage, air preheaters, heat pumps, absorption heat pumps, and mechanical vapour recompression, using uniform criteria weights, performance, economic, and environmental indicators. The framework filters options based on temperature class and industrial application, normalises datasets, and uses a weighted-sum multi-criteria analysis with visual heatmaps to clarify trade-offs. For a rubber facility with medium-temperature exhaust and low-temperature demand, the tool shows that heat pumps and conventional exchangers are preferable due to their readiness, low integration risk, and minimal CAPEX/OPEX in cost-focused scenarios. Technical emphasis elevates heat-upgrading options, as heat pumps improve recoverable temperature lift and site coverage, but require higher investment. Environmental emphasis prioritises heat pumps and long-lived equipment, achieving the largest CO₂-intensity reductions per delivered kilowatt-hour of useful heat. Results highlight that optimal selections depend strongly on stakeholder priorities and boundary conditions. Conventional exchangers deliver fast, low-risk savings; upgrading technologies unlock deeper decarbonisation where a temperature gap exists. The framework enables auditable, site-specific short-listing, clarifies the rationale behind rankings, and supports early engagement between process owners and integrators. The results show a 20.8 % annual reduction in useful energy demand. Savings narrow during demand peaks and decline during extended periods of low load.

工业废热回收直接将热能重新用于现场工作，避免了转换损失和燃料消耗。本文提出了一个决策支持工具，该工具使用统一的标准权重、性能、经济和环境指标，对13种热到热技术进行筛选和排名：间接热交换器、回热器/蓄热器、热管、蓄热器、空气预热器、热泵、吸收式热泵和机械蒸汽再压缩。该框架根据温度类别和工业应用筛选选项，规范化数据集，并使用带有可视化热图的加权和多标准分析来澄清权衡。对于具有中温排气和低温需求的橡胶设施，该工具显示，热泵和传统换热器由于其准备就绪，集成风险低，并且在以成本为重点的情况下，CAPEX/OPEX最小，因此更受欢迎。技术重点提升了热升级的选择，因为热泵提高了可回收的温度提升和现场覆盖，但需要更高的投资。环境重点优先考虑热泵和长寿命设备，实现每输送千瓦时有用热量的最大二氧化碳强度降低。结果表明，最优选择在很大程度上取决于利益相关者的优先级和边界条件。传统的交易所提供快速、低风险的储蓄；在存在温度差距的地方，技术升级可以开启更深层次的脱碳。该框架支持可审计的、特定于站点的短列表，阐明了排名背后的基本原理，并支持流程所有者和集成商之间的早期参与。结果表明，有效能源需求每年减少20.8%。储蓄在需求高峰时缩小，在长时间的低负荷期间下降。

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引用次数: 0

PreFlex — A new marketplace for distributed flexibility providers hedging wind producers: A case study of the Norwegian electricity market PreFlex -分布式灵活性供应商对冲风力生产商的新市场：挪威电力市场的案例研究

IF 5 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-12-02 DOI: 10.1016/j.segy.2025.100220

Henrik Rognes, Felipe Van de Sande Araujo, Pedro Crespo del Granado, Ehsan Nokandi

Renewable power producers’ commitments in the day-ahead (DA) market may face uncertainties and deviations, necessitating swift adjustments in the intraday timeframe. This paper introduces a novel daily capacity-based market, the “Pre-contracting Flexibility Market” (or simply “PreFlex”). PreFlex enables intermittent generation units, specifically Wind Power Producers (WPPs), to contract Distributed Energy Resources (DERs) for flexibility. This enhances the WPP’s ability to counter potential deviations, primarily addressed during the intraday stage. The PreFlex market operates in two steps: first, before the closure of the DA market, the WPPs contract flexibility capacity from DERs through aggregators; second, in parallel with the intraday market, the WPPs activate the acquired capacity to offset predictive generation errors. Using two-stage stochastic optimization models, a comprehensive analysis has been conducted within the Norwegian power market context. The results demonstrate significant benefits for the WPPs by reducing the exposure to imbalance penalties and intraday market illiquidity risks. In addition, from the independent system operator’s perspective, the analysis indicates that introducing the PreFlex market reduces median system imbalances. However, the total costs of procuring and maintaining balancing reserves would not be considerably reduced, as sufficient reserves are needed to cover peak imbalances, which will not be affected by the PreFlex market.

可再生能源生产商在日前（DA）市场的承诺可能面临不确定性和偏差，需要在日内时间框架内迅速调整。本文介绍了一种新的基于日容量的市场，即“预承包弹性市场”（或简称“PreFlex”）。PreFlex使间歇发电机组，特别是风力发电机组（wpp），能够灵活地与分布式能源（DERs）签订合同。这增强了WPP应对潜在偏差的能力，主要是在日内阶段解决。PreFlex市场分两步运作：首先，在DA市场关闭之前，wpp通过聚合商从der手中签订灵活性合同；其次，与日内市场并行，wpp激活已获得的容量以抵消预测生成误差。使用两阶段随机优化模型，在挪威电力市场背景下进行了全面分析。结果表明，通过减少对不平衡处罚和日内市场非流动性风险的暴露，wpp显著受益。此外，从独立系统运营商的角度来看，分析表明，引入PreFlex市场减少了中位数系统失衡。然而，采购和维持平衡储备的总成本不会大大降低，因为需要足够的储备来弥补高峰不平衡，这不会受到PreFlex市场的影响。

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引用次数: 0

Coordinated energy systems in decentralized districts: Evaluating the cellular approach for improved grid stability and renewable integration 分散地区的协调能源系统：评估改善电网稳定性和可再生能源整合的蜂窝方法

IF 5 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-11-01 DOI: 10.1016/j.segy.2025.100215

Lukas Richter , Volker Lenz , Martin Dotzauer , Joachim Seifert

引用次数: 0

Feasibility study of a renewable energy community using stochastic methods: a case-study in Genoa city 基于随机方法的可再生能源社区可行性研究——以热那亚市为例

IF 5 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-11-01 DOI: 10.1016/j.segy.2025.100212

Johan Augusto Bocanegra , Vincenzo Bianco , Mattia De Rosa , Federico Scarpa , Corrado Schenone , Luca Antonio Tagliafico

Renewable energy communities (RECs) provide a novel approach to organizing the production-consumption of renewable energy, involving multiple stakeholders who generate and utilize electricity from renewable sources (commonly wind turbines or solar panels). The REC's economic feasibility depends on sociotechnical factors that are location-dependent and determine costs and benefits. A significant advantage is the shared energy, which balances the energy production and consumption. Approximate estimations of shared energy can be derived from monthly-based models; a more comprehensive analysis requires an hourly-based model. This study develops a stochastic methodology to assess the feasibility of RECs under uncertainty. The approach combines Monte Carlo simulations with hourly energy balance and economic evaluation. The methodology is applied to a condominium-scale case in Genoa, Italy, as a representative example, but can be generalized to other urban contexts. The proposed case study involves a cluster of private buildings with a PV infrastructure and some apartments (consumers) that participate in the REC. This analysis aims to assess the feasibility of the REC under various scenarios, considering factors such as installed power capacity and the number of apartments comprising the community. The results of this study provide valuable insights into the viability of forming a REC in private buildings, offering a methodology for stakeholders involved in sustainable energy planning. The proposed approach can be extrapolated to other locations by selecting the proper parameters.

可再生能源社区（RECs）提供了一种组织可再生能源生产和消费的新方法，涉及从可再生能源（通常是风力涡轮机或太阳能电池板）产生和利用电力的多个利益相关者。REC的经济可行性取决于地理位置相关的社会技术因素，这些因素决定了成本和收益。一个显著的优势是共享能源，它平衡了能源的生产和消费。共享能量的近似估计可以从基于月的模型中得到；更全面的分析需要一个基于小时的模型。本研究发展了一种随机方法来评估不确定条件下RECs的可行性。该方法将蒙特卡罗模拟与小时能量平衡和经济评估相结合。该方法应用于意大利热那亚的一个公寓规模的案例，作为一个代表性的例子，但可以推广到其他城市环境。建议的案例研究涉及一组拥有光伏基础设施的私人建筑物和一些参与可再生能源中心的公寓（消费者）。该分析旨在评估可再生能源中心在各种情况下的可行性，考虑到装机容量和组成社区的公寓数量等因素。本研究的结果为在私人建筑中建立可再生能源中心的可行性提供了宝贵的见解，为参与可持续能源规划的利益相关者提供了一种方法。通过选择适当的参数，可以将所提出的方法外推到其他位置。

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引用次数: 0

Risk-aware sellers and comfort-driven buyers: A game-theoretic P2P energy trading framework 有风险意识的卖家和舒适驱动的买家：一个博弈论的P2P能源交易框架

IF 5 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-11-01 DOI: 10.1016/j.segy.2025.100211

Waqas Amin , Qi Huang , Abdullah Aman Khan , Jian Li , Muhammad Afzal

A transitional shift from the centralized energy system to the distributed energy system has promised to address several concerns of today’s energy system such as rising pollution, variation in energy price, energy availability, and sustainability. However, the increased penetration of renewable energy sources and their stochastic nature also create challenges for the grid, such as economic threats, and meeting energy demand for consumers with limited generation capacity to cope with the buyers’ comfort level. This paper presents a novel method based on a game-theoretic framework for energy trading in the peer-to-peer energy market to meet these challenges. For this purpose, firstly, a model is proposed which invites energy buyers and sellers to form a trading place. Then, a model has been proposed to determine how the energy demand of the buyers and their comfortable index varies. In the case of uncertainty in supply from the grid and when the sellers have no prior information about it determining a fair energy trading price becomes a challenging task. For this purpose, a game-theoretic framework is proposed among energy sellers and the grid to determine the optimal energy price. Thirdly, a game-theoretic framework is used for energy allocation policy, ensuring the buyers’ comfortable index. Fourth, Vogel’s approximation-based optimization problem is proposed to minimize energy losses. The proposed model is evaluated on an IEEE-14 interconnected bus system having 22 players i.e., (11 buyers and 11 sellers) for the dataset of one year. Simulation results show that the proposed model helps to satisfy the energy demand of buyers with an increase in profitability to the sellers and grid. The proposed framework also helps to reduce stress on the grid

从集中式能源系统到分布式能源系统的过渡转变有望解决当今能源系统的几个问题，如日益严重的污染、能源价格的变化、能源的可用性和可持续性。然而，可再生能源的日益普及及其随机性也给电网带来了挑战，如经济威胁，以及在有限的发电能力下满足消费者的能源需求，以满足买家的舒适水平。本文提出了一种基于博弈论框架的点对点能源交易方法来解决这些问题。为此，首先提出了一个邀请能源买卖双方组成交易场所的模型。然后，提出了一个模型来确定买家的能源需求和他们的舒适指数是如何变化的。在电网供应不确定的情况下，当卖方没有事先信息时，确定一个公平的能源交易价格成为一项具有挑战性的任务。为此，提出了一个能源卖家与电网之间的博弈框架来确定最优能源价格。第三，运用博弈论框架制定能源分配政策，保证购买者的舒适指数。第四，提出基于Vogel近似的优化问题，使能量损失最小化。所提出的模型在一个IEEE-14互连总线系统上进行评估，该系统有22个参与者，即（11个买家和11个卖家），用于一年的数据集。仿真结果表明，该模型在满足买方能源需求的同时，提高了卖方和电网的盈利能力。提出的框架还有助于减少电网的压力

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