| publications-5061 |
Article |
2023 |
Prinsloo F.C.; Schmitz P.; Lombard A. |
System dynamics characterisation and synthesis of floating photovoltaics in terms of energy, environmental and economic parameters with WELF nexus sustainability features |
Sustainable Energy Technologies and Assessments |
10.1016/j.seta.2022.102901 |
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The invention of floatovoltaic technologies brought new meaning to the theoretical framing of sustainability as the technology delivers extended natural resource conservation benefits. However, planning assessments for this novel sustainable energy technology exposed knowledge gaps jeopardising global financial investments and regulatory approvals. Knowledge and methodological gaps cause inaccurate performance predictions in current geospatial-engineering modelling tools and fail to adequately quantify the diverse range of layered performance qualities and impacts of floating photovoltaics. This paper advances a geo-sensitive system dynamics framework to systemically integrate the energy, environmental and economic domain object functions in characterising the behaviour and sustainability of floating photovoltaic systems theoretically. The framework serves as computer logic in a geospatial digital twin to synthesise floatovoltaic operations to predict the technology's sustainability impact and offset attributes in balanced scorecard metrics and water–energy–land–food nexus indicators. Experimental evaluations with the proposed framework in a real-world setting demonstrate the value of the holistically integrated framework in analytical floatovoltaic project appraisal and planning support. The results highlight significant advantages when comparing a 1000 m2 floatovoltaic system with a similar-sized conventional photovoltaic alternative, including a 19.3% lifetime energy gain, a carbon emission displacement of CO2e=5168t and a freshwater evaporation benefit of 983 kL. Predictive energy, environmental and economic modelling also offers water–energy–land–food–resource analysis parameters, thus delivering multi-attribute performance profiles that solve many of the current problems with the β€_x009c_technology unknownsβ€_x009d_ of floatovoltaics that impede energy project commissioning and licensing approvals. Β© 2022 Elsevier Ltd |
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| publications-5062 |
Article |
2023 |
Yoon S.; Koo J. |
In situ model fusion for building digital twinning |
Building and Environment |
10.1016/j.buildenv.2023.110652 |
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Building digital twins are crucial in holistic, synthetic, and supervisory digital environments for intelligent and energy-efficient building operations. As buildings are designed, constructed, and operated for long-term periods with uncertainties, it is essential to model, verify, extend, and calibrate the digital twin models in situ over the building life cycle, unlike digital twin modeling in the manufacturing industries. Therefore, this study proposes in situ model fusion techniques for building digital twinning, which include (1) model coupling and (2) model assembly. The first model coupling technique enables nonintrusive in situ verification and calibration for prediction models without the model observations (Y). The second model assembly enables in situ modeling or a more accurate model construction by connecting the verified models through the model coupling technique to the input layer of the target model. In the case studies conducted in a central heating system, the prediction model for the secondary-side return water temperature was modeled and calibrated without relying on the model observation data (Y), thanks to the model coupling technique. The nonintrusive model showed an accuracy with a root mean square error (RMSE) of 0.53 Β°C, which was comparable to the intrusive gray-box models (around 0.5 Β°C RMSE) calibrated using intrusive datasets (Y). Additionally, the prediction model could improve the benchmark model's performance from 0.44 Β°C to 0.26 Β°C (RMSE) using the model assembly technique. The in situ model fusion would enable and enhance nonintrusive modeling approaches, providing a reliable and extensive model environment for digital twins in the building sector. Β© 2023 Elsevier Ltd |
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| publications-5063 |
Article |
2023 |
Mutawa A.M.; Tolba A.S. |
Digital Twin of a Data Center at an Educational Institution |
Journal of Engineering Research (Kuwait) |
10.36909/jer.15973 |
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Digital twins are among the most important trends of the fourth industrial revolution. They present a crucial tool for protecting critical mission systems and the development of new services, products, and processes. This paper presents the first digital twin for a data center. The rapid growth of the Internet of things and the areas of modeling and simulation results in high demand for the development of data center digital twins (DCDT) to ensure the safety/protection of critical and costly mission infrastructure and guarantee business continuity, enhance efficiency, and sustain development. This paper presents the design and implementation of a digital twin for a university data center. Different sensory data like temperature, humidity, smoke, and water leakage are analyzed using an intelligent event detection approach, which detects abnormalities using an Extreme Learning Machine (ELM) fed with the minimum ratio between successive real-time data streams. The performance of ELM has outperformed that of both Learning Vector Quantization and Radial Basis Function-based neural network classifiers and proved much faster in abnormal event detection. Β© 2023 University of Kuwait. All rights reserved. |
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| publications-5064 |
Article |
2023 |
Barrett T.R.; Bamford M.; Chuilon B.; Deighan T.; Efthymiou P.; Fletcher L.; Gorley M.; Grant T.; Hall T.; Horsley D.; Kovari M.; Tindall M. |
The CHIMERA facility development programme |
Fusion Engineering and Design |
10.1016/j.fusengdes.2023.113689 |
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The CHIMERA fusion technology facility will enable testing of large in-vessel component modules under reactor-like conditions of combined in-vacuum thermal power density and magnetic field. With an integral large superconducting magnet and a PWR-like water loop, CHIMERA is also ideally placed for experiments on liquid metal breeding blanket prototypes. Facility construction is underway at the UKAEA site in South Yorkshire. The superconducting magnet is fully wound and terminated, and the bespoke pulsed magnet power supply has been delivered. Even before construction and commissioning is complete, a parallel and supporting research and development programme is in progress and is reported here. A bespoke infrared heating system has been developed, capable of applying 0.5 MW/m2 to component surfaces up to the size of the ITER test blanket module first wall. The modules of this heater are highly specialised and designed to endure the high magnetic forces from the CHIMERA static and pulsed magnets. CHIMERA will feature a range of diagnostics, including load cells to measure static and pulsed magnetic forces, and induced current sensors, all of which have been tested to confirm acceptable operation in the pulsed magnetic field. Manufacture of the test mock-up to be used for facility commissioning is underway. Testing will be enhanced with simulation ‘digital twin’ capability, and a development project is now producing first virtual test results, informing commissioning of the CHIMERA device. © 2023 |
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| publications-5065 |
Article |
2023 |
Guo Z.; Ye Z.; Ni P.; Cao C.; Wei X.; Zhao J.; He X. |
Intelligent Digital Twin Modelling for Hybrid PV-SOFC Power Generation System |
Energies |
10.3390/en16062806 |
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Hydrogen (H2) energy is an ideal non-polluting renewable energy and can achieve long-term energy storage, which can effectively regulate the intermittence and seasonal fluctuation of solar energy. Solid oxide fuel cells (SOFC) can generate electricity from H2 with only outputs of water, waste heat, and almost no pollution. To solve the power generation instability and discontinuity of solar photovoltaic (PV) systems, a hybrid PV-SOFC power generation system has become one feasible solution. The β€_x009c_digital twinβ€_x009d_, which integrates physical systems and information technology, offers a new view to deal with the current problems encountered during smart energy development. In particular, an accurate and reliable system model is the basis for achieving this vision. As core components, the reliable modelling of the PV cells and fuel cells (FCs) is crucial to the whole hybrid PV-SOFC power generation system’s optimal and reliable operation, which is based on the reliable identification of unknown model parameters. Hence, in this study, an artificial rabbits optimization (ARO)-based parameter identification strategy was proposed for the accurate modelling of PV cells and SOFCs, which was then validated on the PV double diode model (DDM) and SOFC electrochemical model under various operation scenarios. The simulation results demonstrated that ARO shows a more desirable performance in optimization accuracy and stability compared to other algorithms. For instance, the root mean square error (RMSE) obtained by ARO are 1.81% and 13.11% smaller than that obtained by ABC and WOA algorithms under the DDM of a PV cell. Meanwhile, for SOFC electrochemical model parameter identification under the 5 kW cell stack dataset, the RMSE obtained by ARO was only 2.72% and 4.88% to that of PSO for the (1 atm, 1173 K) and (3 atm, 1273 K) conditions, respectively. By establishing a digital twin model for PV cells and SOFCs, intelligent operation and management of both can be further achieved. Β© 2023 by the authors. |
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| publications-5066 |
Conference paper |
2023 |
Feng H.; Pan Z.; Zhang H.; Ye J.; Zhang C.; Xu Y. |
Quaternary System of New Power System: Concept and Practice |
2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023 |
10.1109/EI259745.2023.10512360 |
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The new power system has shown new characteristics in frequency control mode, control methods, and pricing mechanisms. Construction of the new power system requires collaborative efforts on the primary, secondary, tertiary, and quaternary systems. The quaternary system is a collaborative and open platform for all elements built on the strong and reliable physical power grid primary system, sensitive and accurate relay protection secondary system, and intelligent and flexible dispatch automation tertiary system. The quaternary system takes the real-time measurement center and intelligent decision center as the core, with the digital twin power grid as the technical foundation, to build a new ecosystem of organic integration, collaborative regulation, and open and win-win situation between the power system and social elements. Lishui Power Supply Company has conducted preliminary practices of the quaternary system, achieving certain results in areas such as one map of power system, water solar collaborative low-carbon balance, and intelligent control operation of virtual units. Β© 2023 IEEE. |
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| publications-5067 |
Conference paper |
2023 |
Wang H.; Ahmed O.; Desomber K.; Sasthav C.; Storli P.-T.S.; Dahlhaug O.G.; Skjelbred H.I.; Vilberg I. |
Adaptive Hybrid 1D Modeling for Digital Twin of Hydropower Systems |
Proceedings of the IAHR World Congress |
10.3850/978-90-833476-1-5_iahr40wc-p1289-cd |
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This paper summarizes the dynamic modeling of hydropower systems for the development of digital twin (DT) for hydropower systems. The obtained modeling suite covers the penstock dynamics, turbine and generator dynamics, and linkages to the grid, where linearized models have been developed for various components in the NTNU testing system. In this context, a discretized input and output model for the turbine shaft speed control has been obtained as a starting point to build the adaptively learned models representing the relationship between the guide vane opening, shaft speed, and water head. This allows the establishment of adaptive learning strategy where the data from any reference hydropower generation unit can be used to learn the model parameters. To enhance the robustness of the online learning of model parameters, a modeling error dead-zone based recursive least squares algorithm has been developed. In terms of the synchronous generator, a standard dynamic model has been used. Both the real-time data driven modeling and synchronous generator simulation have been performed and desired results have been obtained. © 2023 IAHR – International Association for Hydro-Environment Engineering and Research. |
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| publications-5068 |
Article |
2023 |
Chen D.; Zhang X.; Zhang W.; Yin X. |
Integrated Node Infrastructure for Future Smart City Sensing and Response |
Remote Sensing |
10.3390/rs15143699 |
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Emerging smart cities and digital twins are currently built from heterogenous cutting-edge low-power remote sensing systems limited by diverse inefficient communication and information technologies. Future smart cities delivering time-critical services and responses must transition towards utilizing massive numbers of sensors and more efficient integrated systems that rapidly communicate intelligent self-adaptation for collaborative operations. Here, we propose a critical futuristic integrated communication element named City Sensing Base Station (CSBS), inspired by base stations for cell phones that address similar concerns. A CSBS is designed to handle massive volumes of heterogeneous observation data that currently need to be upgraded by middleware or registered. It also provides predictive and interpolation modelling for the control of sensors and response units such as emergency services and drones. A prototype of CSBS demonstrated that it could unify readily available heterogeneous sensing devices, including surveillance video, unmanned aerial vehicles, and ground sensor webs. Collaborative observation capability was also realized by integrating different object detection sources using advanced computer-vision technologies. Experiments with a traffic accident and water pipeline emergency showed sensing and intelligent analyses were greatly improved. CSBS also significantly reduced redundant Internet connections while maintaining high efficiency. This innovation successfully integrates high-density, high-diversity, and high-precision sensing in a distributed way for the future digital twin of cities. Β© 2023 by the authors. |
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| publications-5069 |
Article |
2023 |
Qaiser M.T.; Ejaz J.; Osen O.; Hasan A. |
Digital twin-driven energy modeling of Hywind Tampen floating wind farm |
Energy Reports |
10.1016/j.egyr.2023.09.023 |
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This paper presents energy modeling of Hywind Tampen floating wind farm based on digital twin technology. Upon its completion, the Hywind Tampen wind farm is the largest floating wind farm in the World and the first floating wind farm to supply electricity for oil and gas fields. The wind farm is located about 140 km off the Norwegian coast with water depth between 260 and 300 m and consists of eleven wind turbines with a capacity of 8.6 MW each. Together with ten gas turbines, it will supply electricity for two oil and gas fields at the Norwegian Continental Shelf (NCS), namely the Gullfaks field with three platforms and the Snorre field with two platforms. In this paper, digital twins of the wind turbines and the oil platforms are created in Unity 3D. Energy from the wind farm is modeled from the first principle and is calculated using inputs from the historic weather data all year round. Simulation results show the wind farm can supply up to one-third of the total electricity needed by the oil and gas platforms almost constantly, which associated with reduction of 200,000 tonnes of CO2 emissions and 1000 tonnes of NOx emissions annually. Β© 2023 The Authors |
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| publications-5070 |
Article |
2023 |
Li W.; Wang Y.; Yang H.; Ye Z.; Li P.; Aron Liu Y.; Wang L. |
Development of a mixed reality method for underground pipelines in digital mechanics experiments |
Tunnelling and Underground Space Technology |
10.1016/j.tust.2022.104833 |
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The underground pipeline network (UPN) is an essential underground structure and infrastructure. Its full-cycle digital twin system is an important part of the smart city. However, traditional information transmission between humans and computers lacks understanding and interaction in the digital twin experiments. From the perspective of perception, a space interaction system based on mixed reality (MR) technology is used to solve the problem of interaction for traditional mechanical experiments. Firstly, during the design phase, Building Information Modeling (BIM) is used to integrate models and information storage, including physical geometry data and material information. Secondly, the analytical algorithm is constructed for sensors by data filtering and material mechanics theory; based on sensors communication, C#/C++, and Socket to develop human–computer interactive methods through Game Engines and Mixed Reality Toolkits (MRTK). Finally, based on comparing the mechanical parameters, the testing of digital pipeline experiments by spatial anchors. Twenty-four experimenters are selected to test this method. The advantages and prospects of spatial interaction with MR are summarized through qualitative and quantitative analysis. This study realizes the data perception of the UPN and maps it to the real environment, which can provide a technical reference for engineering digital experiments. © 2022 Elsevier Ltd |
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