| 1. |
- Qiu, R., et al.
(författare)
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Roadmap to urban energy internet with wind electricity-natural gas nexus : Economic and environmental analysis
- 2022
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Ingår i: Energy. - : Elsevier. - 0360-5442 .- 1873-6785. ; 245
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Tidskriftsartikel (refereegranskat)abstract
- Electrolysis hydrogen generation technology is one of the feasible ways to alleviate the problem of wind electricity curtailment. One promising hydrogen value-added application is to blend hydrogen into the natural gas grid and sell it as the heat energy carrier. This paper aims to discuss the feasibility of a roadmap to urban energy internet with wind electricity-natural gas nexus. Firstly, a framework is raised to integrate wind electricity generation, electrolysis hydrogen generation, and hydrogen-natural gas blending systems. Secondly, a series of reasonable hydrogen supply profiles are provided based on annual electricity curtailment and realistic natural gas scheduling. Then, an energy optimisation model and a techno-economic model are applied to simulate the generation of electricity and hydrogen, as well as determine the most economical hydrogen supply scheme. Finally, a case study in the Beijing-Tianjin-Hebei region of China is taken to validate the benefits of the proposed roadmap. The preferred scheme is worked out with the net present value of 88.8 M$, including the economy configurations of the electricity-hydrogen hybrid generation system, as well as the hydrogen-natural gas blending plan. The results also indicate that annual electricity curtailment and annual carbon emission are decreased by 204 GWh (48.8%) and 40.2 kt (49.9%).
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| 2. |
- Liu, Z., et al.
(författare)
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Targeted opportunities to address the climate-trade dilemma in China
- 2016
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Ingår i: Nature Climate Change. - : Springer Science and Business Media LLC. - 1758-678X .- 1758-6798. ; 6:2, s. 201-206
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Tidskriftsartikel (refereegranskat)abstract
- International trade has become the fastest growing driver of global carbon emissions, with large quantities of emissions embodied in exports from emerging economies. International trade with emerging economies poses a dilemma for climate and trade policy: to the extent emerging markets have comparative advantages in manufacturing, such trade is economically efficient and desirable. However, if carbon-intensive manufacturing in emerging countries such as China entails drastically more CO 2 emissions than making the same product elsewhere, then trade increases global CO 2 emissions. Here we show that the emissions embodied in Chinese exports, which are larger than the annual emissions of Japan or Germany, are primarily the result of China's coal-based energy mix and the very high emissions intensity (emission per unit of economic value) in a few provinces and industry sectors. Exports from these provinces and sectors therefore represent targeted opportunities to address the climate-trade dilemma by either improving production technologies and decarbonizing the underlying energy systems or else reducing trade volumes.
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| 3. |
- Petropoulos, Fotios, et al.
(författare)
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Operational Research : methods and applications
- 2024
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Ingår i: Journal of the Operational Research Society. - : Taylor & Francis Group. - 0160-5682 .- 1476-9360. ; 75:3, s. 423-617
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Forskningsöversikt (refereegranskat)abstract
- Throughout its history, Operational Research has evolved to include methods, models and algorithms that have been applied to a wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first summarises the up-to-date knowledge and provides an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion and used as a point of reference by a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes.
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| 4. |
- Bao, Z., et al.
(författare)
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An optimal charging scheduling model and algorithm for electric buses
- 2023
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Ingår i: Applied Energy. - : Elsevier Ltd. - 0306-2619 .- 1872-9118. ; 332
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Tidskriftsartikel (refereegranskat)abstract
- Electrification poses a promising low-carbon or even zero-carbon transportation solution, serving as a strategic approach to reducing carbon emissions and promoting carbon neutrality in the transportation sector. Along the transportation electrification pathway, the goal of carbon neutrality can be further accelerated with an increasing amount of electricity being generated from renewable energies. The past decade observed the rapid development of battery technologies and deployment of electricity infrastructure worldwide, fostering transportation electrification to expand from railways to light and then heavy vehicles on roadways. In China, a massive number of electric buses have been employed and operated in dozens of metropolises. An important daily operations issue with these urban electric buses is how to coordinate their charging activities in a cost-effective manner, considering various physical, financial, institutional, and managerial constraints. This paper addresses a general charging scheduling problem for an electric bus fleet operated across multiple bus lines and charging depots and terminals, aiming at finding an optimal set of charging location and time decisions given the available charging windows. The charging windows for each bus are predetermined in terms of its layovers at depots and terminals and each of them is discretized into a number of charging slots with the same time duration. A mixed linear integer programming model with binary charging slot choice and continuous state-of-charge (SOC) variables is constructed for minimizing the total charging cost of the bus fleet subject to individual electricity consumption rates, electricity charging rates, time-based charging windows, battery SOC bounds, time-of-use (TOU) charging tariffs, and station-specific electricity load capacities. A Lagrangian relaxation framework is employed to decouple the joint charging schedule of a bus fleet into a number of independent single-bus charging schedules, which can be efficiently addressed by a bi-criterion dynamic programming algorithm. A real-world regional electric bus fleet of 122 buses in Shanghai, China is selected for validating the effectiveness and practicability of the proposed charging scheduling model and algorithm. The optimization results numerically reveal the impacts of TOU tariffs, station load capacities, charging infrastructure configurations, and battery capacities on the bus system performance as well as individual recharging behaviors, and justify the superior solution efficiency of our algorithm against a state-of-the-art commercial solver.
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| 5. |
- Chen, B., et al.
(författare)
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Pathways for sustainable energy transition
- 2019
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Ingår i: Journal of Cleaner Production. - : Elsevier Ltd. - 0959-6526 .- 1879-1786. ; 228, s. 1564-1571
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Tidskriftsartikel (refereegranskat)abstract
- Energy transitions are ongoing processes all over the world. While sustainable solutions are envisioned for the future, many societies are still under high-carbon and high-pollution energy regime borne by fossil fuels. How to design pathways towards sustainable energy transition has attracted worldwide concerns. Understanding the possible transition pathways of the energy system requires the integration of new energy technologies, environmental sciences, economics and management. This Special Issue of Journal of Cleaner Production targets to collect the latest research results on sustainable energy systems, discover innovative avenues and inspiring models and share knowledge on energy system modelling and management. In this paper, we identify 4 themes on sustainable energy transition pathways including: (1)Sustainable energy economics and management; (2)Renewable energy generation and consumption; (3)Environmental impacts of energy systems; and (4)Electric vehicle and energy storage. Theories, technologies, innovative models, and successful experiences are discussed accordingly. It is suggested that creative, robust and audacious strategies in governance, management and education are needed to boost sustainable energy transition across various scales and sectors.
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| 6. |
- Chen, S., et al.
(författare)
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Operational flexibility of active distribution networks with the potential from data centers
- 2021
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Ingår i: Applied Energy. - : Elsevier Ltd. - 0306-2619 .- 1872-9118. ; 293
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Tidskriftsartikel (refereegranskat)abstract
- With the development of information technology, the scale and quantity of internet data centers (IDCs) are expanding rapidly. IDCs have emerged as the major electricity consumers in active distribution networks (ADNs), which dramatically increase the electricity load and have a significant impact on the operational flexibility of ADNs. Geographically distributed IDCs can participate in the operation of ADNs with the potential for spatio-temporal load regulation. This paper proposes flexible dispatch strategies of data centers to improve the operational flexibility of ADNs. First, a data-power model of IT equipment is proposed based on piecewise linearization to describe the power consumption characteristics of data centers. The flexible dispatch strategies for the delay-tolerant workload are further proposed from two aspects of temporal transfer and spatial allocation. Then, considering the potential for spatio-temporal load regulation, the operational flexibility analysis model with data centers is formulated to adapt to the operational requirements of ADNs in complex environments. Case studies show that through the spatio-temporal regulation of workload, the energy efficiency of IDCs can be effectively improved. The flexible dispatch of IDCs can also reduce the voltage violation and feeder load imbalance of ADNs, which can facilitate providing the high-quality power supply for IDCs.
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| 7. |
- Chen, Y., et al.
(författare)
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Colored and patterned silicon photovoltaic modules through highly transparent pearlescent pigments
- 2024
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Ingår i: Solar Energy Materials and Solar Cells. - : Elsevier B.V.. - 0927-0248 .- 1879-3398. ; 275
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Tidskriftsartikel (refereegranskat)abstract
- Building-integrated photovoltaic (BIPV) is crucial for emission reduction and energy transition in urban areas. However, the limited aesthetic appearance hinders the popularization of BIPV as traditional photovoltaic (PV) modules are usually black and dark blue, therefore, colorization of PV modules can solve the problem and pave the way for the further development of BIPV. In this study, some high-efficiency colored crystalline silicon (c-Si) PV modules prepared by screen printing the front glass with pearlescent pigments are developed. A suitable pigment for the colorization of PV modules, namely the synthetic mica-based interference pearlescent pigment, was finalized by analyzing the interference theories and comparing present and potential pigments. An adjusted coloring layer thickness from 15.50 μm to 57.17 μm was then realized, which contributed to a variable lightness (L*) from 39.3 to 46.9. Besides, a series of PV modules with various colors used for building facades that could retain 93.71 % of original power generation ability, were produced for different design choices. Moreover, 15 cm × 15 cm bicolor patterned PV modules with a precise motif were fabricated, which can achieve a satisfying power conversion efficiency (PCE) of 18.64 %, only a 5.44 % relative reduction of power generation ability compared with the reference PV module (PCE = 19.71 %). The colorization method for single-colored and patterned PV modules not only guarantees power generation ability but also provides an aesthetic appearance for BIPV applications.
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| 8. |
- Chen, Y., et al.
(författare)
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Theory-guided hard constraint projection (HCP) : A knowledge-based data-driven scientific machine learning method
- 2021
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Ingår i: Journal of Computational Physics. - : Academic Press Inc.. - 0021-9991 .- 1090-2716. ; 445
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Tidskriftsartikel (refereegranskat)abstract
- Machine learning models have been successfully used in many scientific and engineering fields. However, it remains difficult for a model to simultaneously utilize domain knowledge and experimental observation data. The application of knowledge-based symbolic artificial intelligence (AI) represented by expert systems is limited by the expressive ability of the model, and data-driven connectionism AI represented by neural networks is prone to produce predictions that might violate physical principles. In order to fully integrate domain knowledge with observations and make full use of the strong fitting ability of neural networks, this study proposes theory-guided hard constraint projection (HCP). This deep learning model converts physical constraints, such as governing equations, into a form that is easy to handle through discretization, and then implements hard constraint optimization through projection in a patch. Based on rigorous mathematical proofs, theory-guided HCP can ensure that model predictions strictly conform to physical mechanisms in the constraint patch. The training process of theory-guided HCP only needs a small amount of labeled data (sparse observation), and it can supervise the model by combining the coordinates (label-free data) with domain knowledge. The performance of the theory-guided HCP is verified by experiments based on a published heterogeneous subsurface flow problem. The experiments show that theory-guided HCP requires fewer data, and achieves higher prediction accuracy and stronger robustness to noisy observations, than the fully connected neural networks and soft constraint models. Furthermore, due to the application of domain knowledge, theory-guided HCP possesses the ability to extrapolate and can accurately predict points outside of the range of the training dataset.
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| 9. |
- Enshaei, N., et al.
(författare)
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ICPHM'23 Benchmark Vibration Dataset Applicable in Machine Learning for Systems' Health Monitoring
- 2024
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Ingår i: 2024 IEEE International Conference on Prognostics and Health Management, ICPHM 2024. - : Institute of Electrical and Electronics Engineers Inc.. - 9798350374476 ; , s. 1-8
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Konferensbidrag (refereegranskat)abstract
- Vibration signal analysis is an effective tool for fault diagnosis in industrial/manufacturing machinery. Gearboxes are a fundamental component of many industrial machines, and their failure can cause significant downtime, production losses, and safety hazards. Analyzing vibration signals makes it possible to detect, classify, and diagnose faults in gearboxes, enabling timely maintenance and preventing catastrophic failures. Vibration signals are sensitive to changes in the operating conditions and internal components of gearboxes, making them a reliable indicator of potential faults. This paper introduces a new vibration signal data set, referred to as VibraFault, which has been the focus of the ICPHM23 data challenge. The dataset contains vibration signals acquired from a test rig consisting of a driving motor, a two-stage planetary gearbox, a two-stage parallel gearbox, and a magnetic brake. The experiments include various operating conditions and focus on common sun gear faults on the planetary gearbox, such as surface wear, chipped, crack, and tooth-missing. For each operating condition, normal and fault vibration signals have been recorded at a sampling frequency of 10 kHz. Vibration signals have been collected in three directions to facilitate more comprehensive research studies on mapping between different types of faults and the system's vibration response. The dataset has the potential to promote research in fault diagnosis, particularly in the development of advanced solutions based on Machine Learning (ML) and Deep Neural Networks (DNN).
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| 10. |
- Ji, H., et al.
(författare)
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Robust operation for minimizing power consumption of data centers with flexible substation integration
- 2022
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Ingår i: Energy. - : Elsevier Ltd. - 0360-5442 .- 1873-6785. ; 248
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Tidskriftsartikel (refereegranskat)abstract
- The rapid development of digital economy has led to a dramatic increasement of internet data centers (IDCs), which consume a large amount of electricity. The diverse data-processing demands, high power consumption and workload uncertainty put forward a high requirement for the economical and secure operation of IDCs. As information technology (IT) devices are driven by direct current (DC), flexible substation (FS) has been gradually utilized to provide DC power for IDCs. This paper proposes robust operation strategies for minimizing IDC power consumption with FS integration. First, the linearized IDC power consumption model based on the technology of dynamic voltage and frequency scaling (DVFS) is proposed to describe the operating state of IT devices. Then, considering the FS-based coordinated operation of IDC, photovoltaic (PV) station and energy storage system (ESS), the deterministic power consumption minimization model of IDCs is established. Considering the workload uncertainty, the operation strategies based on distributionally robust optimization (DRO) for IDCs are further proposed. Finally, the effectiveness of proposed method is validated on a modified practical network with IDCs integrated. Results show that through the dispatch of workload and power flow regulation of FS, the power consumption and dropping workload of IDCs are effectively reduced.
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