Applied Energy最新文献_第3页

A power load forecasting method in port based on VMD-ICSS-hybrid neural network 基于 VMD-ICSS 混合神经网络的港口电力负荷预测方法

IF 10.1 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2024-09-27 DOI: 10.1016/j.apenergy.2024.124246

Aiming at the problem of load fluctuation at the power end of large ports, we propose a hybrid neural network joint model based on Mode Decomposition (MD) and Change Point Detection (CPD) to accomplish the load forecasting. In this study, a two-stage joint prediction model is constructed. First, the number of Intrinsic Mode Functions (IMFs) in the Variational Mode Decomposition (VMD) process was dynamically adjusted by introducing an improved Signal Energy (SE) evaluation metric. Subsequently, a Bidirectional Gated Recurrent Unit (Bi-GRU) network is employed to predict these IMFs, and the potential effect of the breakpoints on the prediction outcomes is investigated using the Iterative Cumulative Sum of Squares (ICSS) method. Finally, the eigenmode functions are summed and reconstructed, and then combined with the breakpoint data as inputs for the second stage prediction. To ensure the efficiency of the second stage prediction, the Mogrifier Long-and Short-Term Memory (Mogrifier-LSTM) network structure is improved. In the two-stage model, the adaptive tuning of hyperparameters is implemented by a Hunter-Prey Optimization (HPO) algorithm based on a redesigned chaotic mapping strategy. During the simulation, various neural network topologies were employed to confirm the effectiveness of the model in port power load forecasting.

针对大型港口电力端的负荷波动问题，我们提出了一种基于模式分解（MD）和变化点检测（CPD）的混合神经网络联合模型来完成负荷预测。本研究构建了一个两阶段联合预测模型。首先，通过引入改进的信号能量（SE）评估指标，动态调整变异模式分解（VMD）过程中的本征模式函数（IMF）数量。随后，采用双向门控循环单元（Bi-GRU）网络预测这些 IMF，并使用迭代累积平方和（ICSS）方法研究断点对预测结果的潜在影响。最后，对特征模式函数进行求和与重构，然后与断点数据相结合，作为第二阶段预测的输入。为确保第二阶段预测的效率，改进了 Mogrifier 长短期记忆（Mogrifier-LSTM）网络结构。在两阶段模型中，超参数的自适应调整是通过基于重新设计的混沌映射策略的猎人-猎物优化（HPO）算法实现的。在仿真过程中，采用了各种神经网络拓扑结构，以证实该模型在港口电力负荷预测中的有效性。

{"title":"A power load forecasting method in port based on VMD-ICSS-hybrid neural network","authors":"","doi":"10.1016/j.apenergy.2024.124246","DOIUrl":"10.1016/j.apenergy.2024.124246","url":null,"abstract":"<div><div>Aiming at the problem of load fluctuation at the power end of large ports, we propose a hybrid neural network joint model based on Mode Decomposition (MD) and Change Point Detection (CPD) to accomplish the load forecasting. In this study, a two-stage joint prediction model is constructed. First, the number of Intrinsic Mode Functions (IMFs) in the Variational Mode Decomposition (VMD) process was dynamically adjusted by introducing an improved Signal Energy (SE) evaluation metric. Subsequently, a Bidirectional Gated Recurrent Unit (Bi-GRU) network is employed to predict these IMFs, and the potential effect of the breakpoints on the prediction outcomes is investigated using the Iterative Cumulative Sum of Squares (ICSS) method. Finally, the eigenmode functions are summed and reconstructed, and then combined with the breakpoint data as inputs for the second stage prediction. To ensure the efficiency of the second stage prediction, the Mogrifier Long-and Short-Term Memory (Mogrifier-LSTM) network structure is improved. In the two-stage model, the adaptive tuning of hyperparameters is implemented by a Hunter-Prey Optimization (HPO) algorithm based on a redesigned chaotic mapping strategy. During the simulation, various neural network topologies were employed to confirm the effectiveness of the model in port power load forecasting.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":null,"pages":null},"PeriodicalIF":10.1,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142328203","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

The importance of uncertainty sources in LCA for the reliability of environmental comparisons: A case study on public bus fleet electrification 生命周期评估中不确定因素对环境比较可靠性的重要性：公交车队电气化案例研究

IF 10.1 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2024-09-27 DOI: 10.1016/j.apenergy.2024.124593

Life Cycle Assessment (LCA) is widely used to externally compare environmental indicators across different systems. Although uncertainty analysis is required by standards, it is often neglected, which threatens the reliability of the comparisons. The authors highlights how different assumptions and uncertainty sources can shape LCA outcomes. A case study on public bus fleet electrification was conducted, involving 20 bus models with various modeling assumptions. The impact of following factors on LCA uncertainty was analyzed: LCI database, LCIA method, modeling approach, energy carrier consumption and lifetime. The most significant discrepancies, comparing with baseline models of diesel and electric bus, occurred when different LCIA methods were applied, with results varying by up to 649.0%. The use of alternate LCI caused changes of up to 99.4%. The maximum discrepancies due to modeling approach, energy carrier consumption, and lifetime were 33.0%, 35.7%, and 20.9%, respectively. The paper recommends that comprehensive LCA studies should include multiple indicators, and clearly explained uncertainty sources, assumptions and limitations. Modeling approaches, databases, and LCIA methods should align with the analysis goals. Standardization of LCA methodologies by EPD program operators are suggested to reduce variability. When comparing studies with different assumptions, recalculating results to harmonize assumptions is advised. Transparency and understanding of model uncertainties are essential for drawing reliable conclusions. The study demonstrated that comparing deterministic LCA results undermines reliability. As LCA gains importance in environmental and sustainability communications, increasing awareness of LCA uncertainty and applying the novel findings of this paper is essential for informed decision-making.

生命周期评估（LCA）被广泛用于对不同系统的环境指标进行外部比较。尽管标准要求进行不确定性分析，但这种分析往往被忽视，从而威胁到比较的可靠性。作者强调了不同的假设和不确定性来源如何影响生命周期评估的结果。作者进行了一项关于公交车队电气化的案例研究，涉及 20 个具有不同建模假设的公交车模型。分析了以下因素对生命周期评估不确定性的影响：LCI 数据库、LCIA 方法、建模方法、能源载体消耗和使用寿命。与柴油和电动公交车的基准模型相比，采用不同 LCIA 方法时出现的差异最大，结果相差高达 649.0%。使用替代 LCI 造成的变化高达 99.4%。由于建模方法、载能体消耗和使用寿命造成的最大差异分别为 33.0%、35.7% 和 20.9%。本文建议，全面的生命周期评估研究应包括多个指标，并明确解释不确定性来源、假设和限制。建模方法、数据库和 LCIA 方法应与分析目标保持一致。建议 EPD 项目操作人员将生命周期评估方法标准化，以减少变异性。在比较具有不同假设的研究时，建议重新计算结果，以统一假设。模型不确定性的透明度和理解对于得出可靠的结论至关重要。研究表明，比较确定性的生命周期评估结果会降低可靠性。随着生命周期评估在环境和可持续发展交流中的重要性日益增加，提高对生命周期评估不确定性的认识并应用本文的新发现对于做出明智的决策至关重要。

{"title":"The importance of uncertainty sources in LCA for the reliability of environmental comparisons: A case study on public bus fleet electrification","authors":"","doi":"10.1016/j.apenergy.2024.124593","DOIUrl":"10.1016/j.apenergy.2024.124593","url":null,"abstract":"<div><div>Life Cycle Assessment (LCA) is widely used to externally compare environmental indicators across different systems. Although uncertainty analysis is required by standards, it is often neglected, which threatens the reliability of the comparisons. The authors highlights how different assumptions and uncertainty sources can shape LCA outcomes. A case study on public bus fleet electrification was conducted, involving 20 bus models with various modeling assumptions. The impact of following factors on LCA uncertainty was analyzed: LCI database, LCIA method, modeling approach, energy carrier consumption and lifetime. The most significant discrepancies, comparing with baseline models of diesel and electric bus, occurred when different LCIA methods were applied, with results varying by up to 649.0%. The use of alternate LCI caused changes of up to 99.4%. The maximum discrepancies due to modeling approach, energy carrier consumption, and lifetime were 33.0%, 35.7%, and 20.9%, respectively. The paper recommends that comprehensive LCA studies should include multiple indicators, and clearly explained uncertainty sources, assumptions and limitations. Modeling approaches, databases, and LCIA methods should align with the analysis goals. Standardization of LCA methodologies by EPD program operators are suggested to reduce variability. When comparing studies with different assumptions, recalculating results to harmonize assumptions is advised. Transparency and understanding of model uncertainties are essential for drawing reliable conclusions. The study demonstrated that comparing deterministic LCA results undermines reliability. As LCA gains importance in environmental and sustainability communications, increasing awareness of LCA uncertainty and applying the novel findings of this paper is essential for informed decision-making.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":null,"pages":null},"PeriodicalIF":10.1,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142328204","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

Effect of cold welding on the inconsistencies and thermal safety of battery modules based on a constructed discharge model 基于构建的放电模型，冷焊对电池模块的不一致性和热安全性的影响

IF 10.1 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2024-09-27 DOI: 10.1016/j.apenergy.2024.124570

The thermal safety of battery systems is a common and key technical problem restricting industrial development. Welding is one of the most important electrical connection methods for lithium-ion battery groups, and the quality of welding directly determines the thermal safety of battery modules. In this research, the inconsistencies and thermal safety of cylindrical lithium-ion battery modules are studied based on cold welding technology. Secondly, the electrochemical characteristics and thermal runaway characteristics of the battery were experimentally studied. Finally, the battery (Table-Based) module launched by the SIMULINK tool of MATLAB software in 2018 was used to build a battery pack model simulating the discharge process to simulate and analyze the battery electrical characteristics. The relevant data show that the temperature difference between the batteries is less than 4 °C and the maximum battery temperature is less than 60 °C when the cold welded module is discharged at a current ratio(C) of 3 high rate, which has good temperature equalization and thermal safety. The output power is higher and the discharge energy increase by 3 % ~ 5 % when the cold-welded module is discharged at different rates. The results for heat abuse conditions show that the overall temperature rise of the cold-welded module is lower, the maximum temperature of the single battery is reduced by 10.7 %, and the maximum temperature rise rate is reduced by 41.2 %. The simulation results show that the current difference between the cells in the hot welding module is large, and there is an obvious overdischarge phenomenon in the late discharge period. The maximum SOC difference between the single battery of the cold-welded module is less than 0.02 when discharging at 3C. The requirements for SOC estimation are met. The above research results confirm that the relevant research will provide new ideas and theoretical value for the research of the consistency improvement of power battery packs, and solve the problem of the electrical/thermal balance difference of the existing resistance thermal welding process from another dimension based on the cold welding strategy.

电池系统的热安全是制约工业发展的一个普遍而关键的技术问题。焊接是锂离子电池组最重要的电气连接方式之一，焊接质量直接决定了电池模块的热安全。本研究基于冷焊技术，对圆柱形锂离子电池模块的不一致性和热安全性进行了研究。其次，实验研究了电池的电化学特性和热失控特性。最后，利用MATLAB软件的SIMULINK工具2018年最新注册送彩金推出的电池（Table-Based）模块，建立了模拟放电过程的电池组模型，对电池电特性进行了仿真分析。相关数据显示，冷焊模块在3高倍率电流比（C）下放电时，电池温差小于4 ℃，电池最高温度小于60 ℃，具有良好的温度均衡性和热安全性。冷焊模块以不同速率放电时，输出功率较高，放电能量增加 3 % ~ 5 %。热滥用条件下的结果表明，冷焊模块的整体温升较低，单体电池的最高温度降低了 10.7%，最大温升速率降低了 41.2%。仿真结果表明，热焊模块电池之间的电流差较大，在放电后期存在明显的过放电现象。冷焊模块单个电池在 3C 放电时的最大 SOC 差值小于 0.02。符合 SOC 估算的要求。上述研究结果证实，相关研究将为动力电池组一致性改进研究提供新的思路和理论价值，并基于冷焊策略从另一个维度解决现有电阻热焊工艺的电/热平衡差异问题。

{"title":"Effect of cold welding on the inconsistencies and thermal safety of battery modules based on a constructed discharge model","authors":"","doi":"10.1016/j.apenergy.2024.124570","DOIUrl":"10.1016/j.apenergy.2024.124570","url":null,"abstract":"<div><div>The thermal safety of battery systems is a common and key technical problem restricting industrial development. Welding is one of the most important electrical connection methods for lithium-ion battery groups, and the quality of welding directly determines the thermal safety of battery modules. In this research, the inconsistencies and thermal safety of cylindrical lithium-ion battery modules are studied based on cold welding technology. Secondly, the electrochemical characteristics and thermal runaway characteristics of the battery were experimentally studied. Finally, the battery (Table-Based) module launched by the SIMULINK tool of MATLAB software in 2018 was used to build a battery pack model simulating the discharge process to simulate and analyze the battery electrical characteristics. The relevant data show that the temperature difference between the batteries is less than 4 °C and the maximum battery temperature is less than 60 °C when the cold welded module is discharged at a current ratio(C) of 3 high rate, which has good temperature equalization and thermal safety. The output power is higher and the discharge energy increase by 3 % ~ 5 % when the cold-welded module is discharged at different rates. The results for heat abuse conditions show that the overall temperature rise of the cold-welded module is lower, the maximum temperature of the single battery is reduced by 10.7 %, and the maximum temperature rise rate is reduced by 41.2 %. The simulation results show that the current difference between the cells in the hot welding module is large, and there is an obvious overdischarge phenomenon in the late discharge period. The maximum SOC difference between the single battery of the cold-welded module is less than 0.02 when discharging at 3C. The requirements for SOC estimation are met. The above research results confirm that the relevant research will provide new ideas and theoretical value for the research of the consistency improvement of power battery packs, and solve the problem of the electrical/thermal balance difference of the existing resistance thermal welding process from another dimension based on the cold welding strategy.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":null,"pages":null},"PeriodicalIF":10.1,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142326714","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

Predictive energy management strategy with optimal stack start/stop control for fuel cell vehicles 针对燃料电池汽车的预测性能源管理策略与最佳堆栈启动/停止控制

IF 10.1 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2024-09-26 DOI: 10.1016/j.apenergy.2024.124513

Energy management strategies (EMSs) for fuel cell vehicles aim at high fuel efficiency but must also consider the lifetimes of the fuel cell system (FCS) and the battery. Regarding both objectives, fuel cell stack shutdowns play a decisive role in real-world driving situations with low or negative power demand. However, each stack start/stop event is associated with degradation, which is why it is important to keep the number of starts/stops low. This work proposes a predictive EMS with optimal stack start/stop control that takes advantage of a route-based prediction of the entire driving mission to minimize both the fuel consumption and the number of start/stop events. Before departure, the prediction of the entire driving mission is processed in a single offline optimization with dynamic programming. This optimization yields maps providing the real-time EMS with optimal control information that continuously adapts depending on the position along the driving mission and the battery state of charge. Considering this predictive information, the real-time EMS optimizes start/stop actions and the stack power such that the cost-to-go, i.e., the fuel consumption for the trip remainder including start/stop penalties, is implicitly minimized in each instant. In this way, the EMS continuously adapts to the actual conditions, making it robust against unpredicted disturbances, e.g., due to traffic. The superior performance of the proposed strategy compared to state-of-the-art start/stop methods is demonstrated in numerical studies based on real-world driving missions for different vehicle classes with single and multi-stack FCSs.

燃料电池汽车的能源管理策略（EMS）旨在提高燃料效率，但也必须考虑燃料电池系统（FCS）和电池的使用寿命。就这两个目标而言，燃料电池堆的关闭在低功率或负功率需求的实际驾驶情况中起着决定性作用。然而，每次电堆启动/停止事件都会导致性能下降，因此必须减少启动/停止次数。这项工作提出了一种具有最佳堆栈启动/停止控制功能的预测性 EMS，它利用基于路线的整个驾驶任务预测，最大限度地减少燃油消耗和启动/停止事件的次数。在出发前，整个驾驶任务的预测将通过动态编程的单一离线优化进行处理。该优化生成的地图可为实时 EMS 提供最佳控制信息，并根据行驶任务的位置和电池充电状态不断进行调整。考虑到这些预测信息，实时 EMS 会优化启动/停止操作和堆栈功率，从而在每个瞬间隐式地将行驶成本（即包括启动/停止惩罚在内的剩余行程的燃料消耗）降到最低。这样，EMS 就能不断适应实际情况，使其能够抵御交通等不可预知的干扰。根据不同级别车辆的实际驾驶任务，对单层和多层 FCS 进行了数值研究，结果表明，与最先进的启动/停止方法相比，所提出的策略具有更优越的性能。

{"title":"Predictive energy management strategy with optimal stack start/stop control for fuel cell vehicles","authors":"","doi":"10.1016/j.apenergy.2024.124513","DOIUrl":"10.1016/j.apenergy.2024.124513","url":null,"abstract":"<div><div>Energy management strategies (EMSs) for fuel cell vehicles aim at high fuel efficiency but must also consider the lifetimes of the fuel cell system (FCS) and the battery. Regarding both objectives, fuel cell stack shutdowns play a decisive role in real-world driving situations with low or negative power demand. However, each stack start/stop event is associated with degradation, which is why it is important to keep the number of starts/stops low. This work proposes a predictive EMS with optimal stack start/stop control that takes advantage of a route-based prediction of the entire driving mission to minimize both the fuel consumption and the number of start/stop events. Before departure, the prediction of the entire driving mission is processed in a single offline optimization with dynamic programming. This optimization yields maps providing the real-time EMS with optimal control information that continuously adapts depending on the position along the driving mission and the battery state of charge. Considering this predictive information, the real-time EMS optimizes start/stop actions and the stack power such that the cost-to-go, i.e., the fuel consumption for the trip remainder including start/stop penalties, is implicitly minimized in each instant. In this way, the EMS continuously adapts to the actual conditions, making it robust against unpredicted disturbances, e.g., due to traffic. The superior performance of the proposed strategy compared to state-of-the-art start/stop methods is demonstrated in numerical studies based on real-world driving missions for different vehicle classes with single and multi-stack FCSs.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":null,"pages":null},"PeriodicalIF":10.1,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323049","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

Explaining the emergence and absence of Seasonal Thermal Energy Storage in the UK: Evidence from local case studies 解释英国季节性热能储存的出现和缺失：地方案例研究的证据

IF 10.1 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2024-09-26 DOI: 10.1016/j.apenergy.2024.124322

Large-scale energy storage is highlighted as key for decarbonisation, yet there lacks consensus on the optimal types of storage required. Seasonal Thermal Energy Storage (STES) is an established feature of effective energy transitions in some countries, such as Denmark and the Netherlands, but it remains a marginal technology in the UK. This paper contributes to understanding how STES may develop in the UK, and the mechanisms and challenges for widescale STES deployment, through case studies of five local heat projects.

Based on an analysis of both the emergence and absence of STES in local energy projects, we identify key factors enabling and inhibiting STES deployment, intersecting technological, economic, organisational and governance. We conclude that the limited extent of STES in the UK reflects the inconsistent alignment of these factors in local level heat projects, and disconnects between national energy policy, local energy planning, and project-level contingencies. Our findings suggest that without resolving these tensions, the UK heat transition will continue to be haphazard rather than strategic. While the situatedness of low carbon heat supply, storage and demand suggests moves towards more local energy governance, this needs to be accompanied by multi-level alignment and capacity building.

大规模储能被强调为去碳化的关键，但人们对所需的最佳储能类型缺乏共识。在丹麦和荷兰等一些国家，季节性热能储存（STES）是有效能源转型的一个既定特征，但在英国，它仍然是一项边缘技术。本文通过对五个地方供热项目的案例研究，有助于了解季节性热能储存技术在英国的发展情况，以及大规模部署季节性热能储存技术的机制和挑战。基于对地方能源项目中出现和未出现季节性热能储存技术的分析，我们确定了促进和抑制季节性热能储存技术部署的关键因素，这些因素涉及技术、经济、组织和管理等多个方面。我们的结论是，英国 STES 的有限程度反映了这些因素在地方级供热项目中的不一致，以及国家能源政策、地方能源规划和项目级应急措施之间的脱节。我们的研究结果表明，如果不解决这些矛盾，英国的供热转型仍将是杂乱无章的，而非战略性的。虽然低碳供热、储存和需求的地理位置表明，地方能源管理的发展方向更加明确，但同时还需要多层次的协调和能力建设。

{"title":"Explaining the emergence and absence of Seasonal Thermal Energy Storage in the UK: Evidence from local case studies","authors":"","doi":"10.1016/j.apenergy.2024.124322","DOIUrl":"10.1016/j.apenergy.2024.124322","url":null,"abstract":"<div><div>Large-scale energy storage is highlighted as key for decarbonisation, yet there lacks consensus on the optimal types of storage required. Seasonal Thermal Energy Storage (STES) is an established feature of effective energy transitions in some countries, such as Denmark and the Netherlands, but it remains a marginal technology in the UK. This paper contributes to understanding how STES may develop in the UK, and the mechanisms and challenges for widescale STES deployment, through case studies of five local heat projects.</div><div>Based on an analysis of both the emergence and absence of STES in local energy projects, we identify key factors enabling and inhibiting STES deployment, intersecting technological, economic, organisational and governance. We conclude that the limited extent of STES in the UK reflects the inconsistent alignment of these factors in local level heat projects, and disconnects between national energy policy, local energy planning, and project-level contingencies. Our findings suggest that without resolving these tensions, the UK heat transition will continue to be haphazard rather than strategic. While the situatedness of low carbon heat supply, storage and demand suggests moves towards more local energy governance, this needs to be accompanied by multi-level alignment and capacity building.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":null,"pages":null},"PeriodicalIF":10.1,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323050","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

A dynamic multi-objective optimization model for inner-industry carbon responsibility allocation based on carbon tax and carbon offsets accounting 基于碳税和碳抵消核算的产业内部碳责任分配动态多目标优化模型

IF 10.1 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2024-09-26 DOI: 10.1016/j.apenergy.2024.124571

The setting of Intergovernmental Panel on Climate Change (IPCC) raises concerns on curbing the excessive carbon emissions, and European Union (EU) has been proactively attempting “green” initiatives striving to achieve carbon neutrality. The current Carbon Border Adjustment Mechanism (CBAM) only works on short-term carbon reduction without much “greenness” investment incentives so far, and few studies focus on the long-standing inner-industrial carbon reduction coordination. To address these issues, this paper creatively presents a dynamic multi-objective carbon responsibility allocation model (CRAM) for EU carbon market, allows the carbon trade with a taxation based on carbon offsets accounting, and considers the final targets of sustainable “greenness” investment incentives. To find the optimal results of the designed dynamic CRAM, an improved KT-NSGA-II algorithm is proposed to detect the Pareto frontiers of each successive periods. Data from EU Cement and Aluminium industries are then selected for empirical analysis to compare the proposed CRAM to conventional CBAM model. The findings demonstrate that the superiority of CRAM in carbon emissions reduction, economic benefits improvement and green invests encouragement. With the adjustment of the inner-industrial carbon allowance trade, total carbon emissions decreased by 28.03% and the “greenness” investment initiative increased by 39.24% in contrast to the CBAM. The sensitivity analysis of the model also provides suggestions on the settings of carbon quota and tax with different industrial production process, and proposes policy recommendations for CRAM implementation.

政府间气候变化专门委员会（IPCC）的设定引起了人们对抑制过量碳排放的关注，欧盟（EU）也一直在积极尝试 "绿色 "举措，努力实现碳中和。目前的碳边界调整机制（CBAM）只适用于短期碳减排，没有太多的 "绿色 "投资激励措施，也很少有研究关注长期的工业内部碳减排协调。针对这些问题，本文创造性地提出了欧盟碳市场的动态多目标碳责任分配模型（CRAM），允许碳交易与基于碳抵消核算的税收，并考虑了可持续 "绿色 "投资激励的最终目标。为了找到所设计的动态 CRAM 的最优结果，提出了一种改进的 KT-NSGA-II 算法来检测每个连续时期的帕累托前沿。然后选取欧盟水泥业和铝业的数据进行实证分析，比较所提出的 CRAM 与传统的 CBAM 模型。研究结果表明，CRAM 在减少碳排放、提高经济效益和鼓励绿色投资方面具有优势。与 CBAM 相比，通过调整工业内部碳配额交易，碳排放总量减少了 28.03%，"绿色 "投资积极性提高了 39.24%。模型的敏感性分析还为不同工业生产过程的碳配额和碳税设置提供了建议，并为 CRAM 的实施提出了政策建议。

{"title":"A dynamic multi-objective optimization model for inner-industry carbon responsibility allocation based on carbon tax and carbon offsets accounting","authors":"","doi":"10.1016/j.apenergy.2024.124571","DOIUrl":"10.1016/j.apenergy.2024.124571","url":null,"abstract":"<div><div>The setting of Intergovernmental Panel on Climate Change (IPCC) raises concerns on curbing the excessive carbon emissions, and European Union (EU) has been proactively attempting “green” initiatives striving to achieve carbon neutrality. The current Carbon Border Adjustment Mechanism (CBAM) only works on short-term carbon reduction without much “greenness” investment incentives so far, and few studies focus on the long-standing inner-industrial carbon reduction coordination. To address these issues, this paper creatively presents a dynamic multi-objective carbon responsibility allocation model (CRAM) for EU carbon market, allows the carbon trade with a taxation based on carbon offsets accounting, and considers the final targets of sustainable “greenness” investment incentives. To find the optimal results of the designed dynamic CRAM, an improved KT-NSGA-II algorithm is proposed to detect the Pareto frontiers of each successive periods. Data from EU Cement and Aluminium industries are then selected for empirical analysis to compare the proposed CRAM to conventional CBAM model. The findings demonstrate that the superiority of CRAM in carbon emissions reduction, economic benefits improvement and green invests encouragement. With the adjustment of the inner-industrial carbon allowance trade, total carbon emissions decreased by 28.03% and the “greenness” investment initiative increased by 39.24% in contrast to the CBAM. The sensitivity analysis of the model also provides suggestions on the settings of carbon quota and tax with different industrial production process, and proposes policy recommendations for CRAM implementation.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":null,"pages":null},"PeriodicalIF":10.1,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323585","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

Development of an SPH-based numerical wave–current tank and application to wave energy converters 开发基于 SPH 的数值波流槽并应用于波浪能转换器

IF 10.1 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2024-09-26 DOI: 10.1016/j.apenergy.2024.124508

This research proposes a high-fidelity based numerical tank designed to analyze the modified hydrodynamics that develops in waves–current fields, aimed at generating power matrices for wave energy converters (WEC). This tank is developed within the open source DualSPHysics Lagrangian framework using the Smoothed Particle Hydrodynamics (SPH) method, validated with physical data, and applied to simulate a point-absorber WEC. Our proposed numerical facility implements open boundary conditions, employing third-order consistent wave theory for direct generation, with flow field constrained by a Doppler correlation function. Reference data is collected from dedicated physical tests for monochromatic waves; the wave–current numerical basin demonstrates very high accuracy in terms of wave transformation and velocity field. In the second segment of this paper, a current-aware power transfer function is computed for the taut-moored point-absorber Uppsala University WEC (UUWEC). Parametrically defined regular waves with uniform currents are utilized to map an operational sea state featuring currents of different directions and intensities. In terms of power capture capabilities, the modified dynamics observed in presence of currents translates in a dependence of the WEC’s power matrix not only on wave parameters, but also on current layouts. The UUWEC’s power output has revealed that regardless of current directionality, annual output consistently decreases, with a registered power drop as high as 10% when an expected current field is introduced.

本研究提出了一种基于高保真的数值水槽，旨在分析波流场中形成的修正流体力学，从而为波浪能转换器（WEC）生成功率矩阵。该水槽是在开源的 DualSPHysics 拉格朗日框架内使用平滑粒子流体动力学（SPH）方法开发的，通过物理数据进行了验证，并应用于模拟点吸收式波浪能转换器。我们建议的数值设备采用开放边界条件，采用三阶一致波理论直接生成，流场受多普勒相关函数约束。参考数据收集自专门的单色波物理测试；波流数值盆地在波变换和速度场方面表现出极高的精度。本文第二部分计算了乌普萨拉大学水电站（UUWEC）绷锚式点吸收器的电流感知功率传递函数。利用参数定义的具有均匀海流的规则波来绘制具有不同方向和强度海流的运行海况图。就功率捕获能力而言，在海流存在的情况下观察到的改良动态不仅取决于波浪参数，还取决于海流布局。UUWEC 的功率输出显示，无论电流方向如何，年输出功率都会持续下降，当引入预期电流场时，记录的功率下降高达 10%。

{"title":"Development of an SPH-based numerical wave–current tank and application to wave energy converters","authors":"","doi":"10.1016/j.apenergy.2024.124508","DOIUrl":"10.1016/j.apenergy.2024.124508","url":null,"abstract":"<div><div>This research proposes a high-fidelity based numerical tank designed to analyze the modified hydrodynamics that develops in waves–current fields, aimed at generating power matrices for wave energy converters (WEC). This tank is developed within the open source DualSPHysics Lagrangian framework using the Smoothed Particle Hydrodynamics (SPH) method, validated with physical data, and applied to simulate a point-absorber WEC. Our proposed numerical facility implements open boundary conditions, employing third-order consistent wave theory for direct generation, with flow field constrained by a Doppler correlation function. Reference data is collected from dedicated physical tests for monochromatic waves; the wave–current numerical basin demonstrates very high accuracy in terms of wave transformation and velocity field. In the second segment of this paper, a current-aware power transfer function is computed for the taut-moored point-absorber Uppsala University WEC (UUWEC). Parametrically defined regular waves with uniform currents are utilized to map an operational sea state featuring currents of different directions and intensities. In terms of power capture capabilities, the modified dynamics observed in presence of currents translates in a dependence of the WEC’s power matrix not only on wave parameters, but also on current layouts. The UUWEC’s power output has revealed that regardless of current directionality, annual output consistently decreases, with a registered power drop as high as 10% when an expected current field is introduced.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":null,"pages":null},"PeriodicalIF":10.1,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323045","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

Building electricity load forecasting based on spatiotemporal correlation and electricity consumption behavior information 基于时空相关性和用电行为信息的建筑电力负荷预测

IF 10.1 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2024-09-26 DOI: 10.1016/j.apenergy.2024.124580

Accurate prediction of building electricity load is essential for grid management and building optimization operations. This paper proposes a novel approach based on spatiotemporal correlations and electricity consumption behavior information. The K-Medoids algorithm and the Derivative Dynamic Time Warping (DDTW) distance are employed to explore the correlation between electricity consumption behaviors among different partitions and floors. Different partitions and floors are clustered and grouped, followed by modifying the adjacency matrix with electricity consumption behaviors. The hybrid model and K-Medoids-LSTM model are proposed separately for clusterable nodes and non-clustered nodes. For clusterable nodes, spatial-temporal features are extracted, trained, and predicted with the hybrid model based on graph neural networks (GNNs) and LSTM models. A K-Medoids-LSTM model based on the K-Medoids algorithm is proposed to predict the electricity load of the non-clustered nodes. To explore the model's practicality, we predicted the building electrical load under different dataset sizes. The model achieves an R² above 0.89, and the MAE, MSE, and RMSE of the GCN-LSTM and GAT-LSTM models all remain below 0.1, indicating strong predictive capabilities. The results demonstrate that, without relying on other external features, the proposed method can accurately predict the building electricity load for different partitions and floors simultaneously.

准确预测建筑物用电负荷对于电网管理和建筑物优化运行至关重要。本文提出了一种基于时空相关性和用电行为信息的新方法。本文采用 K-Medoids 算法和衍生动态时间扭曲（DDTW）距离来探索不同分区和楼层之间用电行为的相关性。对不同分区和楼层进行聚类和分组，然后根据用电行为修改邻接矩阵。针对可聚类节点和非聚类节点，分别提出了混合模型和 K-Medoids-LSTM 模型。对于可聚类节点，使用基于图神经网络（GNN）和 LSTM 模型的混合模型提取、训练和预测时空特征。提出了基于 K-Medoids 算法的 K-Medoids-LSTM 模型，用于预测非集群节点的电力负荷。为了探索该模型的实用性，我们预测了不同数据集规模下的建筑物电力负荷。该模型的 R2 高于 0.89，GCN-LSTM 模型和 GAT-LSTM 模型的 MAE、MSE 和 RMSE 均低于 0.1，表明该模型具有很强的预测能力。结果表明，在不依赖其他外部特征的情况下，所提出的方法可以同时准确预测不同分区和楼层的建筑用电负荷。

{"title":"Building electricity load forecasting based on spatiotemporal correlation and electricity consumption behavior information","authors":"","doi":"10.1016/j.apenergy.2024.124580","DOIUrl":"10.1016/j.apenergy.2024.124580","url":null,"abstract":"<div><div>Accurate prediction of building electricity load is essential for grid management and building optimization operations. This paper proposes a novel approach based on spatiotemporal correlations and electricity consumption behavior information. The K-Medoids algorithm and the Derivative Dynamic Time Warping (DDTW) distance are employed to explore the correlation between electricity consumption behaviors among different partitions and floors. Different partitions and floors are clustered and grouped, followed by modifying the adjacency matrix with electricity consumption behaviors. The hybrid model and K-Medoids-LSTM model are proposed separately for clusterable nodes and non-clustered nodes. For clusterable nodes, spatial-temporal features are extracted, trained, and predicted with the hybrid model based on graph neural networks (GNNs) and LSTM models. A K-Medoids-LSTM model based on the K-Medoids algorithm is proposed to predict the electricity load of the non-clustered nodes. To explore the model's practicality, we predicted the building electrical load under different dataset sizes. The model achieves an R<sup>2</sup> above 0.89, and the MAE, MSE, and RMSE of the GCN-LSTM and GAT-LSTM models all remain below 0.1, indicating strong predictive capabilities. The results demonstrate that, without relying on other external features, the proposed method can accurately predict the building electricity load for different partitions and floors simultaneously.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":null,"pages":null},"PeriodicalIF":10.1,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323047","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 frequency-secured planning method for integrated electricity-heat microgrids with virtual inertia suppliers 具有虚拟惯性供应商的电热一体化微电网频率保障规划方法

IF 10.1 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2024-09-26 DOI: 10.1016/j.apenergy.2024.124540

The integrated electricity-heat microgrid (IEHM) is characterized by low inertia and a high share of renewable generation. Although sector coupling in the IEHM enhances energy efficiency, the integration of electricity and heat systems restricts the primary frequency regulation (PFR) ability of coupling equipment, further threatening frequency security. This paper presents a frequency-secured planning method for virtual inertia suppliers and combined heat and power (CHP) units in the IEHM. First, we examine the PFR in IEHMs from both device and system perspectives. We develop steady-state models for sector-coupled equipment, specifically CHP units and large-scale heat pumps, for PFR and sizing purposes. To describe the system’s frequency response under emergency conditions, we explicitly derive frequency constraints that account for varying system inertia of heterogeneous resources. Furthermore, we conduct a comprehensive analysis of the impact of PFR on heating systems within the IEHM. Second, we propose a frequency-constrained planning model for IEHMs based on the aforementioned modeling framework. This model balances the power supply, heating supply, and PFR reserves deployment of IEHM by properly sizing the regulation resources. It also leverages distributionally robust (DR) chance constraints to address uncertain wind power generation. To improve the tractability of this model, we introduce a well-tailored reformulation approach that handles the nonconvexity of system inertia and DR chance constraints. Case studies conducted on two test systems demonstrate the effectiveness of the proposed method in securing frequency stability while improving the economic performance of IEHM. This method ensures both dynamic and static frequency security across 100% of time steps by optimally deploying system inertia and PFR reserves. Moreover, by coordinating heterogeneous PFR resources with time-varying system inertia, the proposed approach yields superior economic performance, achieving over a 9% reduction in total capacity compared to average benchmarks.

电热一体化微电网（IEHM）的特点是低惯性和高比例的可再生能源发电。虽然 IEHM 中的扇区耦合提高了能效，但电力和热力系统的集成限制了耦合设备的一次频率调节（PFR）能力，进一步威胁频率安全。本文针对 IEHM 中的虚拟惯性供应商和热电联产（CHP）机组提出了一种频率安全规划方法。首先，我们从设备和系统两个角度研究了 IEHM 中的 PFR。我们为部门耦合设备（特别是热电联产机组和大型热泵）开发了稳态模型，以实现 PFR 和选型目的。为了描述紧急状况下的系统频率响应，我们明确推导出频率约束，以考虑异构资源的不同系统惯性。此外，我们还全面分析了 PFR 对 IEHM 内供热系统的影响。其次，在上述建模框架的基础上，我们提出了一种基于频率约束的 IEHM 规划模型。该模型通过合理确定调节资源的大小，平衡 IEHM 的供电、供热和 PFR 储备部署。它还利用分布稳健（DR）机会约束来解决不确定的风力发电问题。为了提高该模型的可操作性，我们引入了一种量身定制的重拟方法，以处理系统惯性和 DR 偶然性约束的非凸性问题。在两个测试系统上进行的案例研究表明，所提出的方法在确保频率稳定性的同时，还能提高 IEHM 的经济效益。该方法通过优化部署系统惯性和 PFR 储备，确保了 100%时间步长内的动态和静态频率安全。此外，通过协调具有时变系统惯性的异构 PFR 资源，所提出的方法产生了卓越的经济性能，与平均基准相比，总容量减少了 9% 以上。

{"title":"A frequency-secured planning method for integrated electricity-heat microgrids with virtual inertia suppliers","authors":"","doi":"10.1016/j.apenergy.2024.124540","DOIUrl":"10.1016/j.apenergy.2024.124540","url":null,"abstract":"<div><div>The integrated electricity-heat microgrid (IEHM) is characterized by low inertia and a high share of renewable generation. Although sector coupling in the IEHM enhances energy efficiency, the integration of electricity and heat systems restricts the primary frequency regulation (PFR) ability of coupling equipment, further threatening frequency security. This paper presents a frequency-secured planning method for virtual inertia suppliers and combined heat and power (CHP) units in the IEHM. First, we examine the PFR in IEHMs from both device and system perspectives. We develop steady-state models for sector-coupled equipment, specifically CHP units and large-scale heat pumps, for PFR and sizing purposes. To describe the system’s frequency response under emergency conditions, we explicitly derive frequency constraints that account for varying system inertia of heterogeneous resources. Furthermore, we conduct a comprehensive analysis of the impact of PFR on heating systems within the IEHM. Second, we propose a frequency-constrained planning model for IEHMs based on the aforementioned modeling framework. This model balances the power supply, heating supply, and PFR reserves deployment of IEHM by properly sizing the regulation resources. It also leverages distributionally robust (DR) chance constraints to address uncertain wind power generation. To improve the tractability of this model, we introduce a well-tailored reformulation approach that handles the nonconvexity of system inertia and DR chance constraints. Case studies conducted on two test systems demonstrate the effectiveness of the proposed method in securing frequency stability while improving the economic performance of IEHM. This method ensures both dynamic and static frequency security across 100% of time steps by optimally deploying system inertia and PFR reserves. Moreover, by coordinating heterogeneous PFR resources with time-varying system inertia, the proposed approach yields superior economic performance, achieving over a 9% reduction in total capacity compared to average benchmarks.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":null,"pages":null},"PeriodicalIF":10.1,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323583","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

Non-stationary GNNCrossformer: Transformer with graph information for non-stationary multivariate Spatio-Temporal wind power data forecasting 非稳态 GNNCrossformer：用于非稳态多变量时空风电数据预测的图信息变换器

IF 10.1 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2024-09-26 DOI: 10.1016/j.apenergy.2024.124492

The spatiotemporal prediction of wind power is of great significance for the grid connected operation of multiple wind farms in the wind power system. However, due to the complex temporal and spatial dependencies among multiple wind farms, developing advanced models to make accurate wind power predictions under their mutual influence is equally challenging. Furthermore, most of existing models are not ideal for long-term prediction of multivariate and non-stationary wind farm power datasets. To solve these problems, this paper proposes a novel Transformer-based model named Non-stationary GNNCrossformer for non-stationary multivariate Spatio-Temporal forecasting, utilizing Nonstationary-Two-Stage-Attention for both non-stationary cross-time dependency and cross-dimension dependency, as well as using the new graph convolutional neural network with Chebyshev interpolation for extracting temporally conditioned topological information from multiple wind farms efficiently. To tackle the dilemma between series predictability and model capability, we also propose Series Stationarization to complement Nonstationary-Two-Stage-Attention. While series stationarization makes sequence representation more generalized, the Nonstationary-Two-Stage-Attention can be devised to recover the intrinsic non-stationary information into temporal dependencies by approximating distinguishable attentions learned from raw series. Besides, the new graph convolutional neural network with Chebyshev interpolation can converge faster, be more robust, and have stronger generalization ability than the traditional one with Chebyshev approximation. In our experiment, two real-world wind power datasets were used to validate the proposed model. Numerical experiments have demonstrated the effectiveness and robustness of the proposed method compared to state-of-the-art spatiotemporal models.

风力发电的时空预测对于风力发电系统中多个风电场的并网运行具有重要意义。然而，由于多个风电场之间存在复杂的时空依赖关系，开发先进的模型来准确预测它们相互影响下的风力发电量同样具有挑战性。此外，大多数现有模型并不适合对多变量和非稳态风电场功率数据集进行长期预测。为了解决这些问题，本文提出了一种基于变换器的新型模型，命名为非稳态 GNNCrossformer，用于非稳态多变量时空预测，利用非稳态两阶段注意（Nonstationary-Two-Stage-Attention）来处理非稳态跨时间依赖性和跨维度依赖性，并利用新的图卷积神经网络与切比雪夫插值（Chebyshev interpolation）来有效提取多个风电场的时间条件拓扑信息。为了解决序列可预测性和模型能力之间的两难问题，我们还提出了序列静止化来补充非静止-两阶段注意。序列静止化使序列表示更加概括，而非静止-两阶段注意力则可以通过近似从原始序列中学习到的可区分注意力，将固有的非静止信息恢复为时间依赖关系。此外，采用切比雪夫插值的新型图卷积神经网络与采用切比雪夫近似的传统图卷积神经网络相比，收敛速度更快、鲁棒性更高、泛化能力更强。在实验中，我们使用了两个真实的风力发电数据集来验证所提出的模型。与最先进的时空模型相比，数值实验证明了所提出方法的有效性和鲁棒性。

{"title":"Non-stationary GNNCrossformer: Transformer with graph information for non-stationary multivariate Spatio-Temporal wind power data forecasting","authors":"","doi":"10.1016/j.apenergy.2024.124492","DOIUrl":"10.1016/j.apenergy.2024.124492","url":null,"abstract":"<div><div>The spatiotemporal prediction of wind power is of great significance for the grid connected operation of multiple wind farms in the wind power system. However, due to the complex temporal and spatial dependencies among multiple wind farms, developing advanced models to make accurate wind power predictions under their mutual influence is equally challenging. Furthermore, most of existing models are not ideal for long-term prediction of multivariate and non-stationary wind farm power datasets. To solve these problems, this paper proposes a novel Transformer-based model named Non-stationary GNNCrossformer for non-stationary multivariate Spatio-Temporal forecasting, utilizing Nonstationary-Two-Stage-Attention for both non-stationary cross-time dependency and cross-dimension dependency, as well as using the new graph convolutional neural network with Chebyshev interpolation for extracting temporally conditioned topological information from multiple wind farms efficiently. To tackle the dilemma between series predictability and model capability, we also propose Series Stationarization to complement Nonstationary-Two-Stage-Attention. While series stationarization makes sequence representation more generalized, the Nonstationary-Two-Stage-Attention can be devised to recover the intrinsic non-stationary information into temporal dependencies by approximating distinguishable attentions learned from raw series. Besides, the new graph convolutional neural network with Chebyshev interpolation can converge faster, be more robust, and have stronger generalization ability than the traditional one with Chebyshev approximation. In our experiment, two real-world wind power datasets were used to validate the proposed model. Numerical experiments have demonstrated the effectiveness and robustness of the proposed method compared to state-of-the-art spatiotemporal models.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":null,"pages":null},"PeriodicalIF":10.1,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323605","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