IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2024-11-09 DOI: 10.1016/j.energy.2024.133705

Linfei Yin, Yi Xiong

Deep reinforcement learning (DRL) has garnered growing attention as a data-driven control technique in the field of built environments. However, the existing DRL approaches for managing water systems cannot consider information from multiple time steps, are prone to overestimation, fall into the problem of locally optimal solutions, and fail to cope with time-varying environments, resulting in an inability to minimize energy consumption while considering water comfort and hygiene of occupants. Therefore, this study proposes an incremental learning user profile and deep reinforcement learning (ILUPDRL) method for controlling hot water systems. This study employs hot water user profiles to reflect the hot water demand (HWD) habits. The proposed ILUPDRL addresses the challenges arising from evolving HWD through incremental learning of hot water user profiles. Moreover, to enable the ILUPDRL to consider information from multiple time steps, this study proposes the recurrent proximal policy optimization (RPPO) algorithm and integrates the RPPO into the ILUPDRL. The simulation results show that the ILUPDRL achieves up to 67.53 % energy savings while considering the water comfort and water hygiene of occupants.

深度强化学习（DRL）作为一种数据驱动控制技术，在建筑环境领域受到越来越多的关注。然而，现有的水系统管理 DRL 方法无法考虑多个时间步骤的信息，容易出现高估，陷入局部最优解的问题，并且无法应对时变环境，导致无法在考虑用水舒适度和居住者卫生的同时最大限度地降低能耗。因此，本研究提出了一种增量学习用户配置文件和深度强化学习（ILUPDRL）方法来控制热水系统。本研究采用热水用户配置文件来反映热水需求（HWD）习惯。所提出的 ILUPDRL 通过对热水用户配置文件的增量学习，解决了不断变化的 HWD 所带来的挑战。此外，为了使 ILUPDRL 能够考虑多个时间步骤的信息，本研究提出了循环近似策略优化（RPPO）算法，并将 RPPO 集成到 ILUPDRL 中。仿真结果表明，ILUPDRL 在考虑居住者用水舒适度和用水卫生的同时，实现了高达 67.53% 的节能效果。

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引用次数: 0

Predictive combination model for CH4 separation and CO2 sequestration with CO2 injection into coal seams: VMD-STA-BiLSTM-ELM hybrid neural network modeling 将二氧化碳注入煤层进行甲烷分离和二氧化碳封存的预测组合模型：VMD-STA-BiLSTM-ELM 混合神经网络建模

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2024-11-08 DOI: 10.1016/j.energy.2024.133744

Haiteng Xue , Gongda Wang , Xijian Li , Feng Du

In the experimental process of separating coal seam gas using the CO₂ displacement method, establishing a predictive model for key variables is essential to optimize displacement parameters, increase coal seam gas recovery, and improve CO₂ sequestration efficiency. Traditional modeling methods often struggle with the complex nature of industrial data and are susceptible to overfitting due to multicollinearity caused by long-term datasets. This paper presents a hybrid predictive model based on variational mode decomposition (VMD), a spatiotemporal attention mechanism (STA), a bidirectional long short-term memory network (BiLSTM), and an extreme learning machine (ELM). During the offline phase, VMD is used to decompose raw data into intrinsic mode functions (IMFs). The hidden state from the last time step of the STA-BiLSTM is then added to the original data to enrich the features for ELM training. In the online prediction phase, the outputs from the VMD-STA-BiLSTM and VMD-STA-BiLSTM-ELM models are combined using an error reciprocal method to generate the final prediction. The proposed model is validated with experimental datasets from CO₂ displacement for coal seam CH₄ under various conditions, as well as with N₂-ECBM and CO₂-ECBM engineering datasets. The results show that the hybrid model surpasses VMD-ELM, STA-BiLSTM-ELM, BiLSTM, STA-BiLSTM, ELM, TCN, and Attention-TCN models in predictive accuracy. Even in multi-step and rolling predictions, the model exhibits minimal impact from cumulative errors, maintaining accurate forecasts with strong generalization and robustness. It effectively captures feature patterns across different datasets and accurately predicts unknown data. The model shows potential for application in diverse scenarios and complex environments, offering reliable support and decision-making for the field application of CO₂ displacement in coal seam CH₄ separation. It is an effective and promising predictive approach to enhance coal seam gas recovery and CO₂ sequestration efficiency.

在利用二氧化碳置换法分离煤层气的实验过程中，建立关键变量的预测模型对于优化置换参数、提高煤层气采收率和二氧化碳封存效率至关重要。传统的建模方法往往难以应对工业数据的复杂性，并且容易因长期数据集造成的多重共线性而导致过拟合。本文提出了一种基于变模分解（VMD）、时空注意力机制（STA）、双向长短期记忆网络（BiLSTM）和极端学习机（ELM）的混合预测模型。在离线阶段，VMD 用于将原始数据分解为内在模式函数（IMF）。然后，将 STA-BiLSTM 最后一个时间步的隐藏状态添加到原始数据中，以丰富 ELM 训练的特征。在在线预测阶段，使用误差倒数法将 VMD-STA-BiLSTM 和 VMD-STA-BiLSTM-ELM 模型的输出结合起来，生成最终预测结果。利用各种条件下煤层 CH4 的二氧化碳置换实验数据集以及 N2-ECBM 和 CO2-ECBM 工程数据集对所提出的模型进行了验证。结果表明，混合模型的预测精度超过了 VMD-ELM、STA-BiLSTM-ELM、BiLSTM、STA-BiLSTM、ELM、TCN 和 Attention-TCN 模型。即使在多步预测和滚动预测中，该模型也能将累积误差的影响降至最低，从而保持准确的预测结果，并具有很强的泛化能力和鲁棒性。它能有效捕捉不同数据集的特征模式，并准确预测未知数据。该模型显示了在不同场景和复杂环境中的应用潜力，为煤层甲烷分离中二氧化碳置换的现场应用提供了可靠的支持和决策。它是提高煤层气采收率和二氧化碳封存效率的一种有效且有前景的预测方法。

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引用次数: 0

Experimental and numerical investigations on NH3/H2 fueled combustion in the combustor with block for improved micro power generation 带块燃烧器中 NH3/H2 燃料燃烧的实验和数值研究，以改进微型发电技术

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2024-11-08 DOI: 10.1016/j.energy.2024.133733

Peng Teng, Qingguo Peng, Long Zhang, Ruixue Yin, Xinghua Tian, Hao Wang, Zhixin Huang

To advance the application of zero-carbon fuels in micro combustion, enhance energy conversion, and reduce NO_x emissions in NH₃/H₂-fueled micro power generators, a micro-combustor with an inserted block is proposed and tested under various chamber configurations and operational conditions. Experimental and numerical tests are conducted in micro-combustors with varied block settings, burner dimensions, NH₃ blended ratios (m_N), and fuel flow rates (V_f). The results indicate that m_N significantly impacts the generation and consumption of H, O, and OH radicals, as well as NO, affecting flame regime and heat transfer. Specifically, adding 5∼15 % NH₃ improves the operating performance of the burner, with the highest mean temperature achieved in combustor #24C3-0.4 at m_N = 15 %. Block insertion alters flame characteristics and enhances gas-wall heat transfer, and the combustor with thinner blocks at higher m_N and thicker blocks at lower m_N contributes to better thermal performance. Furthermore, combustors with thinner blocks exhibit lower NO emissions. The working performance of the micro-thermophotovoltaic system can be enhanced by selecting the appropriate burner length with block thickness W = 0.4 mm and position L_b = 7 mm based on V_f. The maximum electrical power of 3.7 W is achieved with a burner length of 28 mm for the system using InGaAsSb cells at V_f = 1200 mL/min.

为了推动零碳燃料在微型燃烧中的应用、提高能量转换率并减少以 NH3/H2 为燃料的微型发电机中的氮氧化物排放，我们提出了一种带有插入式燃烧块的微型燃烧器，并在不同的燃烧室配置和运行条件下进行了测试。在具有不同炉块设置、燃烧器尺寸、NH3 混合比 (mN) 和燃料流速 (Vf) 的微型燃烧器中进行了实验和数值测试。结果表明，mN 对 H、O、OH 自由基以及 NO 的生成和消耗有很大影响，并影响火焰状态和传热。具体来说，添加 5-15 % 的 NH3 可改善燃烧器的运行性能，在 mN = 15 % 时，24C3-0.4#燃烧器的平均温度最高。燃烧块的插入改变了火焰特性并增强了气壁传热，在 mN 较高时，燃烧块较薄，而在 mN 较低时，燃烧块较厚，这有助于提高热性能。此外，采用较薄燃烧块的燃烧器的氮氧化物排放量较低。根据 Vf，选择合适的燃烧器长度（燃烧块厚度 W = 0.4 毫米，位置 Lb = 7 毫米），可以提高微型热光电系统的工作性能。在 Vf = 1200 mL/min 条件下，使用 InGaAsSb 电池的系统在燃烧器长度为 28 mm 时可获得 3.7 W 的最大功率。

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引用次数: 0

Process simulation, thermodynamic and system optimization for the low-carbon alcohols production via gasification of second-generation biomass 通过气化第二代生物质生产低碳酒精的过程模拟、热力学和系统优化

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2024-11-08 DOI: 10.1016/j.energy.2024.133770

Wenyu Mo , Beichen Yu , Long Jiang , Kai Xu , Jun Xu , Yi Wang , Sheng Su , Song Hu , Jun Xiang

Biomass-to-liquid fuels technology offers a promising method for high-value biomass conversion, addressing environmental toxicity and fossil fuel non-renewability. However, challenges such as low system efficiency and identifying efficiency losses persist. In this study, a comprehensive process model of a low-carbon alcohols production system via biomass gasification was developed, based on the first demonstration project in China. The innovation of this study lies in its detailed experimental validation, as the model simulation was performed using laboratory data and verified with pilot-scale platform data ensuring high accuracy. Additionally, the study conducted a thorough sensitivity analysis of system parameters, energy, and exergy assessments to find the proper operating conditions, including equivalent ratio, biomass type, and reactor temperature and pressure. The simulation results demonstrated an energy efficiency of 34.67 % and an exergy efficiency of 31.24 %. Through operating parameters and heat recovery measures, these efficiencies increased by 11.66 % and 8 %, respectively. This research not only obtains improved operating parameters for the pilot-scale platform but also provides actionable insights for enhancing the yields of target products and upgrading low-grade energy utilization. These findings offer valuable guidance for the commercialization of bio-syngas alcohols production systems, highlighting significant advancements in efficiency and system performance.

生物质转化为液体燃料技术为高价值生物质转化提供了一种前景广阔的方法，解决了环境毒性和化石燃料不可再生的问题。然而，系统效率低和识别效率损失等挑战依然存在。本研究以中国首个示范项目为基础，建立了生物质气化低碳酒精生产系统的综合工艺模型。本研究的创新之处在于其详细的实验验证，因为模型模拟是利用实验室数据进行的，并通过中试规模平台数据进行了验证，确保了高精度。此外，该研究还对系统参数、能量和放能评估进行了全面的敏感性分析，以找到合适的运行条件，包括当量比、生物质类型、反应器温度和压力。模拟结果表明，能源效率为 34.67%，放能效率为 31.24%。通过操作参数和热回收措施，这些效率分别提高了 11.66 % 和 8 %。这项研究不仅改进了中试规模平台的运行参数，还为提高目标产品产量和提升低品位能源利用率提供了可行的见解。这些研究结果为生物合成气酒精生产系统的商业化提供了宝贵的指导，突出了在效率和系统性能方面的显著进步。

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引用次数: 0

Self-superheated combined flash binary geothermal cycle using transcritical-CO2 power cycle with LNG heat sink as the secondary cycle 使用跨临界二氧化碳动力循环的自过热联合闪蒸二元地热循环，以液化天然气散热器作为二次循环

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2024-11-08 DOI: 10.1016/j.energy.2024.133742

Subha Mondal , Sudipta De

Combined flash binary geothermal cycle (CFBGC) is an efficient geothermal energy conversion technology. Natural gas (NG) is a preferred fuel in the current energy scenario. LNG gasification is a needed step for delivering NG among the end users. In the present study, a self-superheated single-flash geothermal steam cycle, a transcritical CO₂ power cycle and an LNG gasification unit are integrated into a CFBGC. This study shows that the LNG gasification rate and power output can be increased simultaneously by increasing the steam turbine inlet pressure. At a higher steam turbine inlet pressure, desirable steam quality (i.e., 0.9) at the steam turbine exit is maintained by implementing self superheating of the steam. It is observed that 15 °C DSH of steam enables the CFBGC to operate at a steam turbine inlet pressure that substantially enhances the output power without a noticeable increase in levelized electricity cost (LEC). The CFBGC operating at this condition yields 9.97 % higher power output compared to that of the CFBGC operating at steam turbine inlet pressure requiring no DSH of steam. As a geothermal-based power plant emits very low CO₂, the proposed energy system may emerge as a future sustainable energy option.

联合闪蒸二元地热循环（CFBGC）是一种高效的地热能转换技术。天然气（NG）是当前能源领域的首选燃料。液化天然气气化是向终端用户输送天然气的必要步骤。本研究将自过热单闪蒸地热蒸汽循环、跨临界二氧化碳发电循环和液化天然气气化装置集成到 CFBGC 中。研究表明，通过提高蒸汽轮机进口压力，可同时提高液化天然气气化率和功率输出。在较高的蒸汽轮机入口压力下，通过蒸汽的自过热，蒸汽轮机出口处可保持理想的蒸汽品质（即 0.9）。据观察，15 °C 的蒸汽自过热可使 CFBGC 在蒸汽轮机入口压力下运行，从而大幅提高输出功率，而不会明显增加平准化电力成本（LEC）。在此条件下运行的 CFBGC 与在蒸汽轮机进口压力下运行的 CFBGC 相比，输出功率高出 9.97%。由于地热发电厂的二氧化碳排放量极低，拟议的能源系统可能成为未来的可持续能源选择。

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引用次数: 0

Frequency security constraint in unit commitment with detailed frequency response behavior of wind turbines 机组承诺中的频率安全约束与风力涡轮机的详细频率响应行为

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2024-11-08 DOI: 10.1016/j.energy.2024.133735

Jianshu Yu, Pei Yong, Juan Yu, Zhifang Yang

With the high penetration of wind turbines, the necessity of incorporating frequency security considerations into power system scheduling rises. Existing methods achieve the explicit modeling of frequency security constraints by simplifying the frequency response behavior of wind turbines. However, simplifications might lead to inaccuracy. To address this issue, this paper models the frequency response from wind turbines in detail and proposes a novel framework to construct the frequency security constraint for unit commitment (UC). First, the frequency security constraint is positioned at the segment that is effective for the dispatch decision instead of the whole boundary, which is unnecessary and complicated. Then, an analytical linear surrogate expression of the frequency security boundary is constructed through a data-driven approach. To ensure the accuracy of the surrogate constraint, a neighborhood sampling strategy is proposed to collect balanced samples. Furthermore, to reduce the linearization error of the surrogate constraints, supplementary constraints are added to restrict the width of the surrogate constraint. Finally, to address the modeling errors that may deviate from the frequency security requirements, a correction strategy is proposed. Case studies validate the proposed method and verify that it exceeds existing methods in the modeling accuracy of the power system frequency security.

随着风力涡轮机的高渗透率，将频率安全因素纳入电力系统调度的必要性日益增加。现有方法通过简化风力涡轮机的频率响应行为来实现频率安全约束的显式建模。然而，简化可能会导致不准确。为解决这一问题，本文对风力发电机的频率响应进行了详细建模，并提出了一种新的框架来构建机组承诺（UC）的频率安全约束。首先，频率安全约束被定位在对调度决策有效的区段，而不是整个边界，这既不必要又复杂。然后，通过数据驱动法构建频率安全边界的解析线性代用表达式。为确保代约束的准确性，提出了一种邻域采样策略来收集均衡样本。此外，为了减少代用约束的线性化误差，还增加了补充约束来限制代用约束的宽度。最后，针对可能偏离频率安全要求的建模误差，提出了一种修正策略。案例研究验证了所提出的方法，并证明该方法在电力系统频率安全建模精度方面超过了现有方法。

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引用次数: 0

Thermal-hydraulic characteristics of an earth air heat exchanger: An experimental analysis 土空气热交换器的热液压特性：实验分析

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2024-11-08 DOI: 10.1016/j.energy.2024.133766

Emad M.S. El-Said

The pipe layout design has a great effect on the thermal-hydraulic characteristics of earth air heat exchanger (EAHE) systems. So, in the current study proposed four new buried pipe design configurations; low to high to low, high to low to high, spiral, and circular, in addition to the straight or uniform for comparison. These five configurations are tested and analyzed experimentally depending on the thermo-hydraulic performance for summer cooling requirements with variation of Re in the range of 18041–40843. The results show that changing the uniform design of the EAHE with fixed pipe length enhances both the heat transfer process and pressure loss values. At the same operating conditions, the circular design has the best performance compared to the other ones. For all pipe shapes, the cooling effect increases with the increase of air Re. The thermal-hydraulic performance of the circular design pipe is higher than that of the other pipe designs. The highest coefficient of performance (COP) average values that can be obtained at Re = 18041 is 3.05 for circular shape and enhances by 48.08 % compared to uniform shape. The effectiveness of EAHE with circular shape is improved by about 3.52 % compared to uniform shape at Re = 18041. Spiral design is optimum design based on the Nu value which reaches about 48 with enhancement 12.56 % and 0.34 % compared to uniform and circular shapes respectively, at Re = 40843. The hydrothermal performance factor is highest in the case of circular shape with value about 21.9 at Re = 21257. By increasing Re, the drawbacks of the increasing in the total entropy generation are reflected negatively on the exergy efficiency. The specific cost of the circular shape at Re = 40843 is the optimum value by about 0.7 $/W. Spiral and circular shapes have a decrease of CO₂ emissions less than uniform shape by percentage varied from 2.93 % to 13.84 % for decrease in the Re from 21257 to 40843. It is concluded that using EAHE with four new shapes is highly efficient in increasing cooling capacity and energy consumption in buildings.

管道布局设计对土风换热器（EAHE）系统的热工水力特性有很大影响。因此，本研究提出了四种新的地埋管设计配置：低到高到低、高到低到高、螺旋和圆形，此外还有直管或均匀管供比较。根据夏季制冷要求的热工水力性能，对这五种配置进行了实验测试和分析，Re 变化范围为 18041-40843 。结果表明，改变管道长度固定的 EAHE 的均匀设计可提高传热过程和压力损失值。在相同的运行条件下，圆形设计与其他设计相比性能最佳。对于所有形状的管道，冷却效果都随着空气 Re 的增加而增加。圆形设计管道的热液压性能高于其他管道设计。在 Re = 18041 时，圆形管道的最高性能系数（COP）平均值为 3.05，比均匀形状的管道提高了 48.08%。在 Re = 18041 时，圆形 EAHE 的效率比均匀形状提高了约 3.52%。在 Re = 40843 条件下，根据 Nu 值，螺旋形设计是最佳设计，其 Nu 值约为 48，与均匀形和圆形相比，分别提高了 12.56 % 和 0.34 %。在 Re = 21257 时，圆形的水热性能系数最高，约为 21.9。随着 Re 值的增加，总熵产生量增加的缺点会对放热效率产生负面影响。在 Re = 40843 时，圆形的具体成本是最佳值，约为 0.7 美元/瓦。当 Re 值从 21257 降至 40843 时，螺旋形和圆形比均匀形的二氧化碳排放量减少了 2.93 % 至 13.84 %。由此得出结论，使用四种新形状的 EAHE 能够高效地提高建筑物的制冷能力和能耗。

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引用次数: 0

Dynamic thermal simulation of a tree-shaped district heating network based on discrete event simulation 基于离散事件模拟的树状区域供热网络动态热模拟

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2024-11-08 DOI: 10.1016/j.energy.2024.133775

Zichan Xie , Haichao Wang , Pengmin Hua , Maximilian Björkstam , Risto Lahdelma

The computational complexity involved in modelling district heating (DH) networks impedes the integration of network operations into comprehensive DH system studies. We developed a flexible, accurate, and fast dynamic thermal simulation model utilising discrete event simulation (DES). This model is versatile, suitable for any tree-shaped DH network with a central heating plant and can estimate node temperatures and calculate pipe heat losses. The speed of the model is improved via using variable time steps and by incorporating two advanced techniques: lazy evaluation and a customised priority queue. To further improve the computational speed, we developed a technique to eliminate redundant sampling points. This model was tested and demonstrated excellent consistency with actual measurements. Remarkably, reducing sampling points can speed up the simulation by a factor of three without compromising the temperature accuracy. A 72-day simulation of a network with 102 pipes was completed within 0.219 s. Our findings highlight the significant potential of the DES model for large-scale dynamic network simulations and offer a promising solution for DH network simulations and system optimisation.

区域供热（DH）网络建模所涉及的计算复杂性阻碍了将网络运行纳入全面的 DH 系统研究。我们利用离散事件仿真（DES）开发了一种灵活、准确、快速的动态热仿真模型。该模型用途广泛，适用于任何带有集中供暖设备的树状 DH 网络，可估算节点温度并计算管道热损失。通过使用可变时间步长并结合两种先进技术：懒惰评估和定制优先队列，该模型的速度得到了提高。为了进一步提高计算速度，我们开发了一种消除冗余采样点的技术。经过测试，该模型与实际测量结果具有极佳的一致性。值得注意的是，在不影响温度精度的情况下，减少采样点可将模拟速度提高三倍。我们的研究结果凸显了 DES 模型在大规模动态网络模拟方面的巨大潜力，并为 DH 网络模拟和系统优化提供了一个前景广阔的解决方案。

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引用次数: 0

A geographic multi-scale machine learning framework for predicting solar irradiation on tilted surfaces 用于预测倾斜表面太阳辐照的地理多尺度机器学习框架

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2024-11-08 DOI: 10.1016/j.energy.2024.133767

Sameer Al-Dahidi , Bilal Rinchi , Raghad Dababseh , Osama Ayadi , Mohammad Alrbai

This study addresses the challenge of improving Global Tilted Irradiation (GTI) predictions, with Jordan serving as the case study. The novelty of the work lies in developing machine learning models that predict GTI at national, regional (3 regions), and city-specific (12 cities) levels, a previously unexplored approach in the literature. The research examines the comparative efficiency of using a single model for an entire country versus tailored models for individual regions and cities, shedding light on the trade-offs in model evaluation. Various regression models, including Neural Networks (NNs), Linear Regression (LR), Regression Trees (RTs), Ensemble of Regression Trees (ERTs), Support Vector Machine (SVM), and Kernel Approximation, were evaluated using performance metrics such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and coefficient of determination (R²). NNs consistently performed best, achieving the lowest RMSE (1.5787 kWh/m²) and highest R² (99.8600 %) at the regional level. Sensitivity analysis further explored the impact of different time resolutions, revealing that monthly data outperformed daily data in terms of accuracy and computational efficiency. Ultimately, we conclude that region-specific models and monthly data resolution are optimal for practical GTI prediction.

本研究以约旦为案例，探讨了改进全球倾斜辐照（GTI）预测的挑战。这项工作的新颖之处在于开发了机器学习模型，可在国家、地区（3 个地区）和城市（12 个城市）层面预测全球倾斜辐照度，这是此前文献中尚未探索过的方法。该研究考察了针对整个国家使用单一模型与针对个别地区和城市使用定制模型的效率比较，从而揭示了模型评估中的权衡问题。研究利用均方根误差 (RMSE)、平均绝对误差 (MAE)、平均绝对百分比误差 (MAPE) 和判定系数 (R2) 等性能指标对各种回归模型进行了评估，包括神经网络 (NN)、线性回归 (LR)、回归树 (RT)、回归树集合 (ERT)、支持向量机 (SVM) 和核逼近模型。NN 始终表现最佳，在区域层面实现了最低的 RMSE（1.5787 kWh/m2）和最高的 R2（99.8600 %）。敏感性分析进一步探讨了不同时间分辨率的影响，结果表明月度数据在准确性和计算效率方面优于日度数据。最终，我们得出结论，针对特定地区的模型和月度数据分辨率是实际 GTI 预测的最佳选择。

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引用次数: 0

A systematic methodology for selecting optimal technology for waste heat utilization in food processing industry 选择食品加工业余热利用最佳技术的系统方法学

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2024-11-08 DOI: 10.1016/j.energy.2024.133751

Mladen Josijevic, Vladimir Vukasinovic, Dusan Gordic, Vanja Sustersic, Dubravka Zivkovic, Jelena Nikolic

Utilizing waste heat that is rejected from thermal processes can greatly enhance the industry's energy balance. Identifying potential waste heat sources in the food and beverage processing industry and making estimations for their possible utilization can be an extremely challenging undertaking. To determine waste heat potentials in the food processing industry and to select an optimal technology for its utilization a novel systematic methodology based on the comprehensive energy audit and mathematical optimization has been developed. The developed mixed integer nonlinear programming model incorporates all novel and the most commonly employed technologies to utilize waste heat.

The developed systematic methodology is tested on a case study, of a milk and dairy production facility. Obtained results have shown that up to 53 % of the available waste heat can be used in the scenario of limited investment costs. Otherwise, in the scenario when investment costs are not set as a limitation, 75 % of waste heat can be used, according to plant demands. Harmonising production processes is necessary to use all the waste heat. The developed systematic methodology can be applied to any food processing industry and other facilities producing waste heat because it presents a universal approach.

利用热加工过程中排出的余热可以大大提高行业的能源平衡。在食品和饮料加工业中确定潜在的废热源并对其可能的利用率进行估算是一项极具挑战性的工作。为了确定食品加工业的余热潜力，并为其利用选择最佳技术，我们开发了一种基于综合能源审计和数学优化的新型系统方法。所开发的混合整数非线性编程模型包含了所有新型和最常用的余热利用技术。结果表明，在投资成本有限的情况下，最多可利用 53% 的可用余热。否则，在投资成本不受限制的情况下，根据工厂需求，75% 的余热可被利用。要利用所有余热，必须协调生产流程。所开发的系统方法适用于任何食品加工业和其他产生余热的设施，因为它提供了一种通用方法。

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