IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2024-11-03 DOI: 10.1016/j.energy.2024.133667

Zhongyan Liu, Hongwei Guan, Xu Jin, Wei Su, Jiawei Shao, Jing Fan, Hao Zhang, Heng Li, Dahan Sun

In this paper, a CO₂ energy storage system that integrates an organic Rankine cycle (ORC) with solar energy is proposed to support grid peaking, enhance the efficient use of renewable energy sources, and optimize system performance. A thermodynamic analysis of the system has been performed and the performance under different operating models is evaluated. In model A, the energy storage efficiency of the system is 77.28 %, the solar energy conversion efficiency is 30.7 %, and the exergy efficiency is 66.1 %. In models B and C, the energy storage efficiency is 76.72 % and 80 %, the solar conversion efficiency is 32.2 % and 31.5 %, and the exergy efficiency is 66.8 % and 65.2 %, respectively. To evaluate the thermodynamic and economic performance of the system, the effect of the decision variables on the system performance is analyzed. Then, the NSGA-II optimization algorithm was applied to optimize the system, and the TOPSIS method was used to evaluate the optimization results. The results show that the energy storage efficiencies under optimal operating conditions are 78.8 %, 77.5 %, and 81.1 % for operating models A, B, and C, respectively. In addition, the levelized cost of storage (LCOS) for operating models A, B, and C are 0.307$/(kW∙h), 0.316$/(kW∙h), and 0.318$/(kW∙h), respectively.

本文提出了一种将有机郎肯循环（ORC）与太阳能集成在一起的二氧化碳储能系统，以支持电网调峰，提高可再生能源的使用效率，并优化系统性能。对该系统进行了热力学分析，并评估了其在不同运行模式下的性能。在模式 A 中，系统的储能效率为 77.28%，太阳能转换效率为 30.7%，放能效率为 66.1%。在模型 B 和 C 中，储能效率分别为 76.72 % 和 80 %，太阳能转换效率分别为 32.2 % 和 31.5 %，放能效率分别为 66.8 % 和 65.2 %。为了评估系统的热力学和经济性能，分析了决策变量对系统性能的影响。然后，应用 NSGA-II 优化算法对系统进行优化，并采用 TOPSIS 方法对优化结果进行评估。结果表明，在最佳运行条件下，运行模式 A、B 和 C 的储能效率分别为 78.8%、77.5% 和 81.1%。此外，运行模式 A、B 和 C 的平准化储能成本（LCOS）分别为 0.307 美元/（kW∙h）、0.316 美元/（kW∙h）和 0.318 美元/（kW∙h）。

{"title":"Thermodynamic and economic analysis of a trans-critical CO2 energy storage system integrated with ORC and solar energy","authors":"Zhongyan Liu, Hongwei Guan, Xu Jin, Wei Su, Jiawei Shao, Jing Fan, Hao Zhang, Heng Li, Dahan Sun","doi":"10.1016/j.energy.2024.133667","DOIUrl":"10.1016/j.energy.2024.133667","url":null,"abstract":"<div><div>In this paper, a CO<sub>2</sub> energy storage system that integrates an organic Rankine cycle (ORC) with solar energy is proposed to support grid peaking, enhance the efficient use of renewable energy sources, and optimize system performance. A thermodynamic analysis of the system has been performed and the performance under different operating models is evaluated. In model A, the energy storage efficiency of the system is 77.28 %, the solar energy conversion efficiency is 30.7 %, and the exergy efficiency is 66.1 %. In models B and C, the energy storage efficiency is 76.72 % and 80 %, the solar conversion efficiency is 32.2 % and 31.5 %, and the exergy efficiency is 66.8 % and 65.2 %, respectively. To evaluate the thermodynamic and economic performance of the system, the effect of the decision variables on the system performance is analyzed. Then, the NSGA-II optimization algorithm was applied to optimize the system, and the TOPSIS method was used to evaluate the optimization results. The results show that the energy storage efficiencies under optimal operating conditions are 78.8 %, 77.5 %, and 81.1 % for operating models A, B, and C, respectively. In addition, the levelized cost of storage (LCOS) for operating models A, B, and C are 0.307$/(kW∙h), 0.316$/(kW∙h), and 0.318$/(kW∙h), respectively.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133667"},"PeriodicalIF":9.0,"publicationDate":"2024-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cooperative energy and reserve trading strategies for multiple integrated energy systems based on asymmetric nash bargaining theory 基于非对称纳什讨价还价理论的多综合能源系统能源和储备合作交易策略

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2024-11-03 DOI: 10.1016/j.energy.2024.133703

Biao Wu, Shaohua Zhang, Chenxin Yuan, Xian Wang, Fei Wang, Shengqi Zhang

To tackle the issues of cooperative energy and reserve trading as well as fair cooperative benefit allocation among multiple integrated energy systems (IESs), this paper proposes a two-stage cooperative energy and reserve trading model for multiple integrated energy systems (MIESs). Specifically, at day-ahead stage, MIESs aim to maximize their overall profit through cooperative electricity and heat trading. At real-time stage, MIESs trade demand response (DR) reserve to minimize the overall wind power deviation compensation cost. To reduce the complexity in model solution, we transform the model into two sub-problems. In sub-problem 1, we determine the energy and DR reserve trading volumes. Here, distributionally robust optimization (DRO) is utilized to manage the severe uncertainties in wind power distribution. In sub-problem 2, based on the outcomes from sub-problem 1, we settle the energy and DR reserve trading prices. To ensure the fairness of benefit allocation, asymmetric Nash bargaining theory is applied to assess each IES's contributions in trading volumes and profit growth. Interval adaptive alternating direction method of multipliers (IA-ADMM) is used to preserve each IES's privacy. Finally, simulation results demonstrate that, compared with independent operation, cooperative trading among MIESs increases profits for all IESs, thereby motivating their participation in cooperative trading.

为了解决多个综合能源系统（IES）之间的能源和储备合作交易以及公平的合作利益分配问题，本文提出了一个多综合能源系统（MIES）两阶段能源和储备合作交易模型。具体来说，在日前阶段，MIES 通过电力和热力的合作交易实现整体利益最大化。在实时阶段，MIES 交易需求响应储备，以最小化整体风电偏差补偿成本。为降低模型求解的复杂性，我们将模型转化为两个子问题。在子问题 1 中，我们确定能源和 DR 储备交易量。在此，利用分布式鲁棒优化（DRO）来管理风电分布中的严重不确定性。在子问题 2 中，根据子问题 1 的结果，我们确定能源和 DR 储备交易价格。为确保利益分配的公平性，我们采用非对称纳什讨价还价理论来评估每个 IES 在交易量和利润增长方面的贡献。采用区间自适应交替乘法（IA-ADMM）来保护每个 IES 的隐私。最后，模拟结果表明，与独立运营相比，MIES 之间的合作交易会增加所有 IES 的利润，从而激励它们参与合作交易。

{"title":"Cooperative energy and reserve trading strategies for multiple integrated energy systems based on asymmetric nash bargaining theory","authors":"Biao Wu, Shaohua Zhang, Chenxin Yuan, Xian Wang, Fei Wang, Shengqi Zhang","doi":"10.1016/j.energy.2024.133703","DOIUrl":"10.1016/j.energy.2024.133703","url":null,"abstract":"<div><div>To tackle the issues of cooperative energy and reserve trading as well as fair cooperative benefit allocation among multiple integrated energy systems (IESs), this paper proposes a two-stage cooperative energy and reserve trading model for multiple integrated energy systems (MIESs). Specifically, at day-ahead stage, MIESs aim to maximize their overall profit through cooperative electricity and heat trading. At real-time stage, MIESs trade demand response (DR) reserve to minimize the overall wind power deviation compensation cost. To reduce the complexity in model solution, we transform the model into two sub-problems. In sub-problem 1, we determine the energy and DR reserve trading volumes. Here, distributionally robust optimization (DRO) is utilized to manage the severe uncertainties in wind power distribution. In sub-problem 2, based on the outcomes from sub-problem 1, we settle the energy and DR reserve trading prices. To ensure the fairness of benefit allocation, asymmetric Nash bargaining theory is applied to assess each IES's contributions in trading volumes and profit growth. Interval adaptive alternating direction method of multipliers (IA-ADMM) is used to preserve each IES's privacy. Finally, simulation results demonstrate that, compared with independent operation, cooperative trading among MIESs increases profits for all IESs, thereby motivating their participation in cooperative trading.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133703"},"PeriodicalIF":9.0,"publicationDate":"2024-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How does green fiscal policy promote the synergy of pollution mitigation and carbon reduction? Evidence from China 绿色财政政策如何促进污染缓解与碳减排的协同作用？来自中国的证据

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2024-11-02 DOI: 10.1016/j.energy.2024.133700

Bangzhu Zhu , Gang Chen , Ping Wang

This study constructs a comprehensive analysis model, utilizing data from Chinese provinces from 2014 to 2021 as the sample to explore how green fiscal policy (GFP) influences the synergy of pollution mitigation and carbon reduction (SPMCR). We collect data on multiple pollutants and greenhouse gas emissions and utilize a composite system model to assess the SMPCR in various regions of China. The findings show that green fiscal policy has significantly contributed to fostering the SPMCR. Industrial upgrading, green innovation, and energy optimization are effective channels for green fiscal policy to achieve SPMCR. Green fiscal policy is more conducive to promoting SPMCR in China's eastern and central regions, demonstrating a gradient of “east > central > west”. Environmental regulation and green fiscal policy synergistically promote SPMCR, with the positive impact of green fiscal policy being more pronounced in regions with stringent environmental regulations. The green fiscal policy presents more positive nonlinear effects on SPMCR when the level of green finance and informatization is higher. After a series of rigorous robustness tests, the main findings are consistent and reliable. In addition, we provide policy recommendations for developing countries to promote pollution and carbon reduction, thus fostering sustainable development.

本研究构建了一个综合分析模型，以中国各省 2014 年至 2021 年的数据为样本，探讨绿色财政政策（GFP）如何影响污染减排与碳减排的协同作用（SPMCR）。我们收集了多种污染物和温室气体排放数据，并利用复合系统模型评估了中国各地区的污染减排与碳减排协同效应。研究结果表明，绿色财政政策极大地促进了 SPMCR 的发展。产业升级、绿色创新和能源优化是绿色财政政策实现 SPMCR 的有效渠道。东部和中部地区的绿色财政政策更有利于促进 SPMCR，呈现出 "东、中、西 "梯度。环境监管与绿色财政政策协同促进 SPMCR，绿色财政政策的积极影响在环境监管严格的地区更为明显。当绿色金融和信息化水平较高时，绿色财政政策对 SPMCR 的正向非线性影响更大。经过一系列严格的稳健性检验，主要结论是一致的、可靠的。此外，我们还为发展中国家提供了促进污染和碳减排的政策建议，从而推动可持续发展。

{"title":"How does green fiscal policy promote the synergy of pollution mitigation and carbon reduction? Evidence from China","authors":"Bangzhu Zhu , Gang Chen , Ping Wang","doi":"10.1016/j.energy.2024.133700","DOIUrl":"10.1016/j.energy.2024.133700","url":null,"abstract":"<div><div>This study constructs a comprehensive analysis model, utilizing data from Chinese provinces from 2014 to 2021 as the sample to explore how green fiscal policy (GFP) influences the synergy of pollution mitigation and carbon reduction (SPMCR). We collect data on multiple pollutants and greenhouse gas emissions and utilize a composite system model to assess the SMPCR in various regions of China. The findings show that green fiscal policy has significantly contributed to fostering the SPMCR. Industrial upgrading, green innovation, and energy optimization are effective channels for green fiscal policy to achieve SPMCR. Green fiscal policy is more conducive to promoting SPMCR in China's eastern and central regions, demonstrating a gradient of “east > central > west”. Environmental regulation and green fiscal policy synergistically promote SPMCR, with the positive impact of green fiscal policy being more pronounced in regions with stringent environmental regulations. The green fiscal policy presents more positive nonlinear effects on SPMCR when the level of green finance and informatization is higher. After a series of rigorous robustness tests, the main findings are consistent and reliable. In addition, we provide policy recommendations for developing countries to promote pollution and carbon reduction, thus fostering sustainable development.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133700"},"PeriodicalIF":9.0,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Techno-economic analysis of hybrid renewable energy systems for cost reduction and reliability improvement using dwarf mongoose optimization algorithm 利用矮獴优化算法对混合可再生能源系统进行技术经济分析，以降低成本并提高可靠性

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2024-11-02 DOI: 10.1016/j.energy.2024.133653

Saleh Al Dawsari , Fatih Anayi , Michael Packianather

The global energy crisis, particularly in isolated and remote regions, has increased interest in renewable energy sources (RESs) to meet growing energy demands. Integrating RESs with energy storage systems offers a promising solution to mitigate fluctuations and intermittency, but concerns about cost and reliability remain. This study explores the optimal design of various microgrid configurations, combining photovoltaic (PV), wind turbine (WT), battery energy storage system (BESS), and diesel generator (DG) systems for Najran city, Saudi Arabia, via real-world meteorological and load demand data. The Dwarf Mongoose Optimization Algorithm (DMOA), alongside the salp swarm algorithm (SSA) and whale optimization algorithm (WOA), was applied to minimize the levelized cost of energy (LCOE) while improving system reliability. The results demonstrate that the PV/BESS configuration, although cost-effective with an LCOE of 0.038 USD/kWh, fail to meet reliability constraints with a loss of power supply probability (LPSP) of 0.679. In contrast, the PV, WT, BESS, and DG configurations achieved an LPSP of 1.9 × 10^--8% with an LCOE of 0.199 USD/kWh, offering a robust and reliable solution for the region's energy needs. This paper presents a novel application of the DMOA for optimizing hybrid renewable energy systems, demonstrating its effectiveness in achieving a balance between cost and reliability. This strategy provides a viable approach for sustainable energy planning in similar regions facing energy challenges.

全球能源危机，尤其是偏远地区的能源危机，增加了人们对可再生能源（RES）的兴趣，以满足日益增长的能源需求。将可再生能源与储能系统集成在一起，为缓解波动和间歇性提供了一种前景广阔的解决方案，但成本和可靠性问题仍然令人担忧。本研究通过真实世界的气象和负荷需求数据，探讨了各种微电网配置的优化设计，将光伏（PV）、风力涡轮机（WT）、电池储能系统（BESS）和柴油发电机（DG）系统结合在一起，用于沙特阿拉伯的纳季兰市。矮獴优化算法（DMOA）与沙蜂群算法（SSA）和鲸鱼优化算法（WOA）一起被用于最大限度地降低平准化能源成本（LCOE），同时提高系统可靠性。结果表明，光伏/BESS 配置虽然具有成本效益（LCOE 为 0.038 美元/千瓦时），但无法满足可靠性约束，供电损失概率 (LPSP) 为 0.679。相比之下，光伏、风电、BESS 和 DG 配置的 LPSP 为 1.9 × 10^--8%，LCOE 为 0.199 美元/千瓦时，为该地区的能源需求提供了稳健可靠的解决方案。本文介绍了 DMOA 在优化混合可再生能源系统方面的新应用，证明了它在实现成本与可靠性之间的平衡方面的有效性。这一策略为面临能源挑战的类似地区提供了一种可行的可持续能源规划方法。

{"title":"Techno-economic analysis of hybrid renewable energy systems for cost reduction and reliability improvement using dwarf mongoose optimization algorithm","authors":"Saleh Al Dawsari , Fatih Anayi , Michael Packianather","doi":"10.1016/j.energy.2024.133653","DOIUrl":"10.1016/j.energy.2024.133653","url":null,"abstract":"<div><div>The global energy crisis, particularly in isolated and remote regions, has increased interest in renewable energy sources (RESs) to meet growing energy demands. Integrating RESs with energy storage systems offers a promising solution to mitigate fluctuations and intermittency, but concerns about cost and reliability remain. This study explores the optimal design of various microgrid configurations, combining photovoltaic (PV), wind turbine (WT), battery energy storage system (BESS), and diesel generator (DG) systems for Najran city, Saudi Arabia, via real-world meteorological and load demand data. The Dwarf Mongoose Optimization Algorithm (DMOA), alongside the salp swarm algorithm (SSA) and whale optimization algorithm (WOA), was applied to minimize the levelized cost of energy (LCOE) while improving system reliability. The results demonstrate that the PV/BESS configuration, although cost-effective with an LCOE of 0.038 USD/kWh, fail to meet reliability constraints with a loss of power supply probability (LPSP) of 0.679. In contrast, the PV, WT, BESS, and DG configurations achieved an LPSP of 1.9 × 10^--8% with an LCOE of 0.199 USD/kWh, offering a robust and reliable solution for the region's energy needs. This paper presents a novel application of the DMOA for optimizing hybrid renewable energy systems, demonstrating its effectiveness in achieving a balance between cost and reliability. This strategy provides a viable approach for sustainable energy planning in similar regions facing energy challenges.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133653"},"PeriodicalIF":9.0,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unraveling the dynamic nexus: Green cryptocurrencies and their role in sustainable market evolution 解开动态关系：绿色加密货币及其在可持续市场演变中的作用

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2024-11-02 DOI: 10.1016/j.energy.2024.133660

Pin Peng , Feifei Liang , Yaping Fu , Yanan Chen , Lin-shu Qiu , Haozhi Qi

This study explores the intricate relationships between green cryptocurrencies, traditional energy, and renewable energy stock markets using an innovative approach that combines time-frequency spillover analysis with cross-quantile dependence methodologies. Our findings show a complicated network of market interactions that change over time and vary widely. In the short term, green cryptocurrencies and new energy equities emerge as pivotal drivers of market dynamics, showcasing their growing influence within traditional energy sectors. This interplay, however, is marked by significant temporal variations, with green cryptocurrencies demonstrating remarkable resilience to external shocks and increasingly becoming transmitters of volatility over time. The cross-quantile dependence analysis further highlights the conditional nature of these interactions, shedding light on the nuanced impact of green cryptocurrencies across different market conditions, particularly during periods of extreme market stress. These insights underscore the transformative role of green financial instruments in the context of the energy transition and sustainable development, offering important implications for investors, policymakers, and the strategic orientation of financial markets toward sustainability.

本研究采用创新方法，将时频溢出分析与交叉量依存度方法相结合，探讨了绿色加密货币、传统能源和可再生能源股票市场之间错综复杂的关系。我们的研究结果表明，市场互动网络错综复杂，随着时间的推移而变化，而且差异很大。在短期内，绿色加密货币和新能源股票成为市场动态的关键驱动因素，显示出它们在传统能源行业中日益增长的影响力。然而，这种相互作用具有显著的时间差异，绿色加密货币对外部冲击表现出卓越的复原力，并随着时间的推移日益成为波动的传播者。跨量纲依赖性分析进一步突出了这些相互作用的条件性质，揭示了绿色加密货币在不同市场条件下的细微影响，尤其是在极端市场压力时期。这些见解强调了绿色金融工具在能源转型和可持续发展背景下的变革作用，为投资者、政策制定者以及金融市场的可持续发展战略导向提供了重要启示。

{"title":"Unraveling the dynamic nexus: Green cryptocurrencies and their role in sustainable market evolution","authors":"Pin Peng , Feifei Liang , Yaping Fu , Yanan Chen , Lin-shu Qiu , Haozhi Qi","doi":"10.1016/j.energy.2024.133660","DOIUrl":"10.1016/j.energy.2024.133660","url":null,"abstract":"<div><div>This study explores the intricate relationships between green cryptocurrencies, traditional energy, and renewable energy stock markets using an innovative approach that combines time-frequency spillover analysis with cross-quantile dependence methodologies. Our findings show a complicated network of market interactions that change over time and vary widely. In the short term, green cryptocurrencies and new energy equities emerge as pivotal drivers of market dynamics, showcasing their growing influence within traditional energy sectors. This interplay, however, is marked by significant temporal variations, with green cryptocurrencies demonstrating remarkable resilience to external shocks and increasingly becoming transmitters of volatility over time. The cross-quantile dependence analysis further highlights the conditional nature of these interactions, shedding light on the nuanced impact of green cryptocurrencies across different market conditions, particularly during periods of extreme market stress. These insights underscore the transformative role of green financial instruments in the context of the energy transition and sustainable development, offering important implications for investors, policymakers, and the strategic orientation of financial markets toward sustainability.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133660"},"PeriodicalIF":9.0,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A drift-aware dynamic ensemble model with two-stage member selection for carbon price forecasting 采用两阶段成员选择的漂移感知动态集合模型进行碳价格预测

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2024-11-02 DOI: 10.1016/j.energy.2024.133699

Liling Zeng , Huanling Hu , Qingkui Song , Boting Zhang , Ruibin Lin , Dabin Zhang

Forecasting carbon prices is a pivotal topic in achieving the targets of carbon neutrality and carbon peaking. However, the complex and time-evolving characteristics inherent in carbon price series render precise forecasting a formidable undertaking. Numerous studies have demonstrated that distinct prediction models exhibit varying capabilities and performances, and ensemble learning offers an efficacious approach to enhance forecasting performance. To address variations in model performance and data distribution, a drift-aware ensemble learning framework is employed to adaptively select and combine models for carbon prices forecasting. First, thirty candidate models are generated by integrating data processing techniques with multiple forecast models to comprehensively capture sample information. Second, an initial selection process of candidate models is dynamically executed utilizing a performance drift detection mechanism. Following each drift detection, a second-stage selection is performed given the significance of diversity in ensemble models. Finally, final predictions are calculated by combining the outputs of selected models via a sliding-window weighted average. Carbon price data from four distinct trading markets in China are employed to validate the efficacy of the drift-aware dynamic ensemble (DDE) framework. The results substantiate that DDE can be a convincing tool for the operation and management of carbon trading markets.

预测碳价格是实现碳中和与碳峰值目标的关键课题。然而，碳价格序列固有的复杂性和随时间变化的特点使得精确预测成为一项艰巨的任务。大量研究表明，不同的预测模型表现出不同的能力和性能，而集合学习为提高预测性能提供了一种有效的方法。为了解决模型性能和数据分布的差异，我们采用了漂移感知集合学习框架，以适应性地选择和组合碳价格预测模型。首先，通过整合数据处理技术和多个预测模型，生成 30 个候选模型，以全面捕捉样本信息。其次，利用性能漂移检测机制动态执行候选模型的初始选择过程。在每次漂移检测之后，考虑到集合模型多样性的重要性，会进行第二阶段的选择。最后，通过滑动窗口加权平均将选定模型的输出结果组合起来，计算出最终预测结果。为了验证漂移感知动态集合（DDE）框架的有效性，我们使用了来自中国四个不同交易市场的碳价格数据。结果证明，DDE 可以成为碳交易市场运营和管理的一个令人信服的工具。

{"title":"A drift-aware dynamic ensemble model with two-stage member selection for carbon price forecasting","authors":"Liling Zeng , Huanling Hu , Qingkui Song , Boting Zhang , Ruibin Lin , Dabin Zhang","doi":"10.1016/j.energy.2024.133699","DOIUrl":"10.1016/j.energy.2024.133699","url":null,"abstract":"<div><div>Forecasting carbon prices is a pivotal topic in achieving the targets of carbon neutrality and carbon peaking. However, the complex and time-evolving characteristics inherent in carbon price series render precise forecasting a formidable undertaking. Numerous studies have demonstrated that distinct prediction models exhibit varying capabilities and performances, and ensemble learning offers an efficacious approach to enhance forecasting performance. To address variations in model performance and data distribution, a drift-aware ensemble learning framework is employed to adaptively select and combine models for carbon prices forecasting. First, thirty candidate models are generated by integrating data processing techniques with multiple forecast models to comprehensively capture sample information. Second, an initial selection process of candidate models is dynamically executed utilizing a performance drift detection mechanism. Following each drift detection, a second-stage selection is performed given the significance of diversity in ensemble models. Finally, final predictions are calculated by combining the outputs of selected models via a sliding-window weighted average. Carbon price data from four distinct trading markets in China are employed to validate the efficacy of the drift-aware dynamic ensemble (DDE) framework. The results substantiate that DDE can be a convincing tool for the operation and management of carbon trading markets.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133699"},"PeriodicalIF":9.0,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comprehensive enhancement of melting-solidifying process in latent heat storage based on eccentric fin-foam combination 基于偏心翅片-泡沫组合的潜热蓄能熔化-凝固过程综合强化技术

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2024-11-02 DOI: 10.1016/j.energy.2024.133693

Kuo Zeng , Junjie Gao , Yongwen Lu , Hongyang Zuo , Bowen Chi , Zheyu Fang , Jun Li , Huaqian Xu , Beiyang Li , Haiping Yang , Hanping Chen

A novel fin-foam combination, applying upward fins to accelerate natural convection and downward foams to dominate thermal conduction, was established to comprehensively enhance the melting and solidifying performance of horizontal shell-and-tube latent heat storage devices. Enhancement mechanisms of the current design were numerically investigated and compared with the typical eccentric and concentric design the whole melting-solidifying process. Among investigated enhancement designs, the fin-foam combination achieved the best results, reducing the melting time and the solidifying time by 47.9 % and 55.4 % respectively. Meanwhile, the relative difference between the melting and solidifying time was reduced to 12 %, indicating a significant mitigation of the buckets effect of solidifying caused by eccentric designs. Further, the effect of the total enhancement material usage was investigated. Results showed that the marginal effect of the heat transfer enhancement started at 9 fins and 0.91 porosity, but the relative difference between melting and solidifying time then dropped below 0.61 %. The economic assessment showed that increasing the amount of enhancement material can significantly improve the storage capacity per unit cost when the price ratio of the enhancement material to PCM is less than 10, indicating a considerable applicability and cost performance of fin-foam combination under different power density demands.

建立了一种新颖的翅片-泡沫组合，即利用向上的翅片加速自然对流，利用向下的泡沫主导热传导，从而全面提高水平管壳式潜热储存装置的熔化和凝固性能。对当前设计的增强机制进行了数值研究，并与典型的偏心和同心设计的整个熔化-凝固过程进行了比较。在所研究的增强设计中，翅片-泡沫组合效果最好，熔化时间和凝固时间分别缩短了 47.9% 和 55.4%。同时，熔化时间和凝固时间之间的相对差异减少到了 12%，这表明偏心设计造成的凝固桶效应得到了显著缓解。此外，还研究了总增强材料用量的影响。结果表明，传热增强的边际效应始于 9 片鳍片和 0.91 的孔隙率，但熔化和凝固时间的相对差异随后降至 0.61 % 以下。经济评估表明，当增强材料与 PCM 的价格比小于 10 时，增加增强材料的用量可显著提高单位成本的存储容量，这表明鳍片-泡沫组合在不同功率密度需求下具有相当的适用性和性价比。

{"title":"Comprehensive enhancement of melting-solidifying process in latent heat storage based on eccentric fin-foam combination","authors":"Kuo Zeng , Junjie Gao , Yongwen Lu , Hongyang Zuo , Bowen Chi , Zheyu Fang , Jun Li , Huaqian Xu , Beiyang Li , Haiping Yang , Hanping Chen","doi":"10.1016/j.energy.2024.133693","DOIUrl":"10.1016/j.energy.2024.133693","url":null,"abstract":"<div><div>A novel fin-foam combination, applying upward fins to accelerate natural convection and downward foams to dominate thermal conduction, was established to comprehensively enhance the melting and solidifying performance of horizontal shell-and-tube latent heat storage devices. Enhancement mechanisms of the current design were numerically investigated and compared with the typical eccentric and concentric design the whole melting-solidifying process. Among investigated enhancement designs, the fin-foam combination achieved the best results, reducing the melting time and the solidifying time by 47.9 % and 55.4 % respectively. Meanwhile, the relative difference between the melting and solidifying time was reduced to 12 %, indicating a significant mitigation of the buckets effect of solidifying caused by eccentric designs. Further, the effect of the total enhancement material usage was investigated. Results showed that the marginal effect of the heat transfer enhancement started at 9 fins and 0.91 porosity, but the relative difference between melting and solidifying time then dropped below 0.61 %. The economic assessment showed that increasing the amount of enhancement material can significantly improve the storage capacity per unit cost when the price ratio of the enhancement material to PCM is less than 10, indicating a considerable applicability and cost performance of fin-foam combination under different power density demands.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133693"},"PeriodicalIF":9.0,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance evaluation and multi-objective optimization of hydrogen-based integrated energy systems driven by renewable energy sources 可再生能源驱动的氢基综合能源系统的性能评估和多目标优化

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2024-11-02 DOI: 10.1016/j.energy.2024.133698

Fanhua Rong , Zeting Yu , Kaifan Zhang , Jingyi Sun , Daohan Wang

This study proposes an integrated energy system using hydrogen storage to realize the efficient utilization of renewable energy sources and reduce the fluctuation when renewable energy is connected to grid. The system utilizes solar and wind energy to realize hydrogen production, desalination, and CCHP. First, the energy, exergy, and economic evaluations for the proposed system are carried out, and then an in-depth analysis of the key operating parameters is performed. The system achieves energy efficiency, exergy efficiency, and cost rate of 48.49 %, 19.98 %, and 7.969 $/h, respectively. And the exergy analysis shows that the main exergy destructions are caused by the parabolic trough solar collector and the transcritical CO₂ power cycle. The parametric analysis demonstrates when solar radiation flux and wind speed increase, the exergy efficiency and hydrogen production are increased, but the cost rate is increased accordingly. Finally, two sets of multi-objective optimization schemes are performed combining the artificial neural network with the Non-dominant genetic algorithm-II. For the optimized fresh water output, cost rate, and exergy efficiency, it is achieving improvements of 51.73 %, 8.4 %, and 3.6 %, and for the optimized hydrogen production, cost rate, and exergy efficiency, it is increased by 12.53 %, 0.564 %, and 0.75 %, respectively.

本研究提出了一种利用氢储存的综合能源系统，以实现可再生能源的高效利用，并减少可再生能源并网时的波动。该系统利用太阳能和风能实现制氢、海水淡化和冷热电三联供。首先，对提出的系统进行了能量、放能和经济性评估，然后对关键运行参数进行了深入分析。该系统的能效、放能效率和成本率分别为 48.49 %、19.98 % 和 7.969 美元/小时。放能分析表明，抛物槽式太阳能集热器和跨临界 CO2 功率循环是造成放能破坏的主要原因。参数分析表明，当太阳辐射通量和风速增加时，放能效率和制氢量都会增加，但成本率也会相应增加。最后，结合人工神经网络和非优势遗传算法-II，进行了两套多目标优化方案。优化后的淡水产量、成本率和放能效分别提高了 51.73 %、8.4 % 和 3.6 %，优化后的氢气产量、成本率和放能效分别提高了 12.53 %、0.564 % 和 0.75 %。

{"title":"Performance evaluation and multi-objective optimization of hydrogen-based integrated energy systems driven by renewable energy sources","authors":"Fanhua Rong , Zeting Yu , Kaifan Zhang , Jingyi Sun , Daohan Wang","doi":"10.1016/j.energy.2024.133698","DOIUrl":"10.1016/j.energy.2024.133698","url":null,"abstract":"<div><div>This study proposes an integrated energy system using hydrogen storage to realize the efficient utilization of renewable energy sources and reduce the fluctuation when renewable energy is connected to grid. The system utilizes solar and wind energy to realize hydrogen production, desalination, and CCHP. First, the energy, exergy, and economic evaluations for the proposed system are carried out, and then an in-depth analysis of the key operating parameters is performed. The system achieves energy efficiency, exergy efficiency, and cost rate of 48.49 %, 19.98 %, and 7.969 $/h, respectively. And the exergy analysis shows that the main exergy destructions are caused by the parabolic trough solar collector and the transcritical CO<sub>2</sub> power cycle. The parametric analysis demonstrates when solar radiation flux and wind speed increase, the exergy efficiency and hydrogen production are increased, but the cost rate is increased accordingly. Finally, two sets of multi-objective optimization schemes are performed combining the artificial neural network with the Non-dominant genetic algorithm-II. For the optimized fresh water output, cost rate, and exergy efficiency, it is achieving improvements of 51.73 %, 8.4 %, and 3.6 %, and for the optimized hydrogen production, cost rate, and exergy efficiency, it is increased by 12.53 %, 0.564 %, and 0.75 %, respectively.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133698"},"PeriodicalIF":9.0,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dual-loop segmented piston trajectory control of free piston linear generator based on sliding mode control 基于滑模控制的自由活塞式线性发生器双回路分段活塞轨迹控制

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2024-11-01 DOI: 10.1016/j.energy.2024.133684

Yingdong Cheng , Jiaqi Li , Jin Xiao , Chen Zhang , Lei Zhu , Zhen Huang

Free piston linear generator (FPLG) can be applied as range extender for electrical vehicles to reduce greenhouse gas emissions attributed to its fuel flexibility and ultimate freedom of piston motion. However, FPLG still faces several challenges in control such as misfire and collision due to the eliminate of mechanical crankshaft. To fully utilize the potential of the ultimate freedom of piston motion, this paper presents a novel piston trajectory control strategy which employs the piston trajectory on the entire operation process of FPLG as the control objective. Considering disturbances and high coupling of FPLG, a sliding mode controller is employed to track reference piston trajectory. Additionally, a segmented control strategy is implemented to decouple the control of combustion pressure force and electromagnetic force. In order to ascertain the effectiveness of the proposed controller, a prototype of single-piston FPLG and a corresponding numerical model are constructed. The experimental and simulation results demonstrate the proposed controller shows fast response, precise tracking performance, and good robustness at various reference piston trajectories. Furthermore, the experimental results illustrate that the system can achieve cold start through the seamless transition between operation states and long-term stable operation by the controller.

自由活塞线性发电机（FPLG）因其燃料灵活性和活塞运动的终极自由度，可用作电动汽车的增程器，以减少温室气体排放。然而，自由活塞线性发电机在控制方面仍面临一些挑战，如由于机械曲轴的消除而导致的失火和碰撞。为了充分利用活塞运动极限自由度的潜力，本文提出了一种新颖的活塞轨迹控制策略，以 FPLG 整个运行过程中的活塞轨迹为控制目标。考虑到 FPLG 的干扰和高耦合性，采用滑模控制器来跟踪参考活塞轨迹。此外，还实施了分段控制策略，以解耦燃烧压力力和电磁力的控制。为了确定所提控制器的有效性，构建了单活塞 FPLG 原型和相应的数值模型。实验和仿真结果表明，所提出的控制器在各种参考活塞轨迹下均表现出快速响应、精确跟踪性能和良好的鲁棒性。此外，实验结果表明，通过控制器在运行状态之间的无缝转换和长期稳定运行，系统可以实现冷启动。

{"title":"Dual-loop segmented piston trajectory control of free piston linear generator based on sliding mode control","authors":"Yingdong Cheng , Jiaqi Li , Jin Xiao , Chen Zhang , Lei Zhu , Zhen Huang","doi":"10.1016/j.energy.2024.133684","DOIUrl":"10.1016/j.energy.2024.133684","url":null,"abstract":"<div><div>Free piston linear generator (FPLG) can be applied as range extender for electrical vehicles to reduce greenhouse gas emissions attributed to its fuel flexibility and ultimate freedom of piston motion. However, FPLG still faces several challenges in control such as misfire and collision due to the eliminate of mechanical crankshaft. To fully utilize the potential of the ultimate freedom of piston motion, this paper presents a novel piston trajectory control strategy which employs the piston trajectory on the entire operation process of FPLG as the control objective. Considering disturbances and high coupling of FPLG, a sliding mode controller is employed to track reference piston trajectory. Additionally, a segmented control strategy is implemented to decouple the control of combustion pressure force and electromagnetic force. In order to ascertain the effectiveness of the proposed controller, a prototype of single-piston FPLG and a corresponding numerical model are constructed. The experimental and simulation results demonstrate the proposed controller shows fast response, precise tracking performance, and good robustness at various reference piston trajectories. Furthermore, the experimental results illustrate that the system can achieve cold start through the seamless transition between operation states and long-term stable operation by the controller.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133684"},"PeriodicalIF":9.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Numerical investigation on the effect of ignition timing on a low-temperature hydrogen-fueled Wankel rotary engine with passive pre-chamber ignition 关于点火正时对采用被动式前腔点火的低温氢燃料万克尔旋转发动机的影响的数值研究

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2024-11-01 DOI: 10.1016/j.energy.2024.133686

Changwei Ji, Hanlin Li, Jinxin Yang, Hao Meng

Adopting the low-temperature hydrogen evaporated from the liquid hydrogen is capable of improving volumetric efficiency for the Wankel rotary engine (WRE). Considering the difficulty in ignition and slow flame propagation of low-temperature hydrogen-air mixtures, the passive pre-chamber is used to improve ignition and combustion. A three-dimensional computational fluid dynamics model for a turbulent jet ignition (TJI) WRE fueled by low-temperature hydrogen was established. The effects of low temperature and TJI on the in-cylinder flow field, combustion, emissions and leakage in the TJI-WRE fueled by low-temperature hydrogen were studied under different ignition timings. The results indicated that low-temperature tends to suppress the flame propagation, whereas TJI can accelerate the flame speed and promote flame propagation to the unburned zone in the combustion chamber. Combining low-temperature hydrogen with the passive pre-chamber can achieve high engine thermal efficiency and power while significantly reducing leakage. With the ignition timing set at 18 °CA before the top dead center, the indicated thermal efficiency reached 39.49 % and the indicated mean effective pressure peaked at 0.77 MPa. Compared to the original engine, fresh mixture leakage through spark plug cavities and adjacent chambers was reduced by 72.13 % and 78.79 %, respectively.

采用从液氢中蒸发出的低温氢气能够提高万克尔旋转发动机（WRE）的容积效率。考虑到低温氢气-空气混合物的点火困难和火焰传播缓慢，采用了被动前室来改善点火和燃烧。建立了以低温氢气为燃料的湍流喷射点火（TJI）WRE 三维计算流体动力学模型。研究了在不同点火时间下，低温和 TJI 对以低温氢气为燃料的 TJI-WRE 的缸内流场、燃烧、排放和泄漏的影响。结果表明，低温倾向于抑制火焰传播，而 TJI 则能加快火焰速度并促进火焰向燃烧室内的未燃区传播。将低温氢气与被动式前室相结合，可实现较高的发动机热效率和功率，同时显著减少泄漏。将点火正时设定在上死点前 18 °CA，指示热效率达到 39.49 %，指示平均有效压力达到峰值 0.77 MPa。与原发动机相比，通过火花塞腔和邻近气室的新鲜混合气泄漏分别减少了 72.13 % 和 78.79 %。

{"title":"Numerical investigation on the effect of ignition timing on a low-temperature hydrogen-fueled Wankel rotary engine with passive pre-chamber ignition","authors":"Changwei Ji, Hanlin Li, Jinxin Yang, Hao Meng","doi":"10.1016/j.energy.2024.133686","DOIUrl":"10.1016/j.energy.2024.133686","url":null,"abstract":"<div><div>Adopting the low-temperature hydrogen evaporated from the liquid hydrogen is capable of improving volumetric efficiency for the Wankel rotary engine (WRE). Considering the difficulty in ignition and slow flame propagation of low-temperature hydrogen-air mixtures, the passive pre-chamber is used to improve ignition and combustion. A three-dimensional computational fluid dynamics model for a turbulent jet ignition (TJI) WRE fueled by low-temperature hydrogen was established. The effects of low temperature and TJI on the in-cylinder flow field, combustion, emissions and leakage in the TJI-WRE fueled by low-temperature hydrogen were studied under different ignition timings. The results indicated that low-temperature tends to suppress the flame propagation, whereas TJI can accelerate the flame speed and promote flame propagation to the unburned zone in the combustion chamber. Combining low-temperature hydrogen with the passive pre-chamber can achieve high engine thermal efficiency and power while significantly reducing leakage. With the ignition timing set at 18 °CA before the top dead center, the indicated thermal efficiency reached 39.49 % and the indicated mean effective pressure peaked at 0.77 MPa. Compared to the original engine, fresh mixture leakage through spark plug cavities and adjacent chambers was reduced by 72.13 % and 78.79 %, respectively.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133686"},"PeriodicalIF":9.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Energy最新文献