| 1. |
- Zhang, Zhixin, et al.
(författare)
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Vectorized rooftop area data for 90 cities in China
- 2022
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Ingår i: Scientific Data. - : Springer Nature. - 2052-4463. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- Reliable information on building rooftops is crucial for utilizing limited urban space effectively. In recent decades, the demand for accurate and up-to-date data on the areas of rooftops on a large-scale is increasing. However, obtaining these data is challenging due to the limited capability of conventional computer vision methods and the high cost of 3D modeling involving aerial photogrammetry. In this study, a geospatial artificial intelligence framework is presented to obtain data for rooftops using high-resolution open-access remote sensing imagery. This framework is used to generate vectorized data for rooftops in 90 cities in China. The data was validated on test samples of 180 km(2) across different regions with spatial resolution, overall accuracy, and F1 score of 1 m, 97.95%, and 83.11%, respectively. In addition, the generated rooftop area conforms to the urban morphological characteristics and reflects urbanization level. These results demonstrate that the generated dataset can be used for data support and decision-making that can facilitate sustainable urban development effectively.
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| 2. |
- Qian, Zhen, et al.
(författare)
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Vectorized dataset of roadside noise barriers in China using street view imagery
- 2022
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Ingår i: Earth System Science Data. - : Copernicus GmbH. - 1866-3508 .- 1866-3516. ; 14:9, s. 4057-4076
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Tidskriftsartikel (refereegranskat)abstract
- Roadside noise barriers (RNBs) are important urban infrastructures to ensure that cities remain liveable. However, the absence of accurate and large-scale geospatial data on RNBs has impeded the increasing progress of rational urban planning, sustainable cities, and healthy environments. To address this problem, this study creates a vectorized RNB dataset in China using street view imagery and a geospatial artificial intelligence framework. First, intensive sampling is performed on the road network of each city based on OpenStreetMap, which is used as the georeference for downloading 6 x 10(6) Baidu Street View (BSV) images. Furthermore, considering the prior geographic knowledge contained in street view images, convolutional neural networks incorporating image context information (IC-CNNs) based on an ensemble learning strategy are developed to detect RNBs from the BSV images. The RNB dataset presented by polylines is generated based on the identified RNB locations, with a total length of 2667.02 km in 222 cities. Last, the quality of the RNB dataset is evaluated from two perspectives, i.e., the detection accuracy and the completeness and positional accuracy. Specifically, based on a set of randomly selected samples containing 10 000 BSV images, four quantitative metrics are calculated, with an overall accuracy of 98.61 %, recall of 87.14 %, precision of 76.44 %, and F-1 score of 81.44 %. A total length of 254.45 km of roads in different cities are manually surveyed using BSV images to evaluate the mileage deviation and overlap level between the generated and surveyed RNBs. The root mean squared error for the mileage deviation is 0.08 km, and the intersection over union for overlay level is 88.08% +/- 2.95 %. The evaluation results suggest that the generated RNB dataset is of high quality and can be applied as an accurate and reliable dataset for a variety of large-scale urban studies, such as estimating the regional solar photovoltaic potential, developing 3D urban models, and designing rational urban layouts. Besides that, the benchmark dataset of the labeled BSV images can also support more work on RNB detection, such as developing more advanced deep learning algorithms, fine-tuning the existing computer vision models, and analyzing geospatial scenes in BSV. The generated vectorized RNB dataset and the benchmark dataset of labeled BSV imagery are publicly available at https://doi.org/10.11888/Others.tpdc.271914 (Chen, 2021).
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| 3. |
- Xu, Nan, et al.
(författare)
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Global optimization energy management for multi-energy source vehicles based on "Information layer - Physical layer - Energy layer- Dynamic programming" (IPE-DP)
- 2022
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Ingår i: Applied Energy. - : Elsevier BV. - 0306-2619 .- 1872-9118. ; 312
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Tidskriftsartikel (refereegranskat)abstract
- To reveal the energy-saving mechanisms of global energy management, we propose a global optimization framework of "information layer-physical layer-energy layer-dynamic programming " (IPE-DP), which can realize the unity of different information scenarios, different vehicle configurations and energy conversions. The deterministic dynamic programing (DP) and adaptive dynamic programming (ADP) are taken as the core algorithms. As a benchmark for assessing the optimality, DP strategy has four main challenges: standardization, real-time application, accuracy, and satisfactory drivability. To solve the above problems, the IPE-DP optimization framework is established, which consists of three main layers, two interface layers and an application layer. To be specific, the full-factor trip information is acquired from three scenarios in the information layer, and then the feasible work modes of the vehicle are determined in the physical layer based on the proposed conservation framework of "kinetic/potential energy & onboard energy ". The above lays a foundation for the optimal energy distribution in the energy layer. Then, a global domain-searching algorithm and action dependent heuristic dynamic programming (ADHDP) model are developed for different information acquisition scenarios to obtain the optimal solution. To improve the computational efficiency under the deterministic information, a fast DP is developed based on the statistical rules of DP behavior, the core of which is to restrict the exploring region based on a reference SOC trajectory. Regarding the stochastic trip information, the ADHDP model is established, including determining the utility function, network design and training process. Finally, two case studies are given to compare the economic performance of the vehicle under different information acquisition scenarios, which lays a foundation for analyzing the relationship between the amount of information input and energy-saving potential of the vehicle. Simulation results demonstrate that the proposed method gains a better performance in both real-time performance and global optimality.
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| 4. |
- Zhang, Chi, et al.
(författare)
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Can Solar Energy be an Alternative Choice of Milk Production in Dairy Farms? : -A Case study of Integrated PVWP System with Alfalfa and Milk Production in Dairy Farms in China
- 2017
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Ingår i: 8th International Conference on Applied Energy, ICAE 2016; Beijing; China; 8 October 2016 through 11 October 2016. - : Elsevier. ; 105, s. 3953-3959
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Konferensbidrag (refereegranskat)abstract
- As China's dairy consumption grows, both the domestic milk production and the importation of dairy products are increasing to meet market demands. The objective of this study was to quantify electricity usage and cost of milk production with data analysis of dairy farms and evaluate the potential alternative energy supply-solar energy generated by PV water pumping system (PVWP). We collected data in milk production processes from 11 dairy farms in China. By selecting the optimal dairy farm, we simulate the scenario of solar power generation with PVWP system to provide power both for milk and alfalfa production. With estimations of electricity saving, economic cost saving and CO2 saving on every kg milk produced under PVWP system, we conclude that scenario PVWP with alfalfa and milk production can results in value add-ins, new sources of revenue, energy supply and emission reductions.
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| 5. |
- Zhang, Z., et al.
(författare)
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Carbon mitigation potential afforded by rooftop photovoltaic in China
- 2023
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Ingår i: Nature Communications. - : Nature Research. - 2041-1723. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Rooftop photovoltaics (RPVs) are crucial in achieving energy transition and climate goals, especially in cities with high building density and substantial energy consumption. Estimating RPV carbon mitigation potential at the city level of an entire large country is challenging given difficulties in assessing rooftop area. Here, using multi-source heterogeneous geospatial data and machine learning regression, we identify a total of 65,962 km2 rooftop area in 2020 for 354 Chinese cities, which represents 4 billion tons of carbon mitigation under ideal assumptions. Considering urban land expansion and power mix transformation, the potential remains at 3-4 billion tons in 2030, when China plans to reach its carbon peak. However, most cities have exploited less than 1% of their potential. We provide analysis of geographical endowment to better support future practice. Our study provides critical insights for targeted RPV development in China and can serve as a foundation for similar work in other countries.
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| 6. |
- Zhu, L., et al.
(författare)
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Unpacking the effects of natural gas price transmission on electricity prices in Nordic countries
- 2024
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Ingår i: iScience. - : Elsevier Inc.. - 2589-0042. ; 27:6
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Tidskriftsartikel (refereegranskat)abstract
- Since the Russia-Ukraine war in February 2022, European electricity prices have experienced considerable turbulence, primarily attributed to a shortage in the natural gas supply. We investigate the relationship between natural gas prices in the European continent and electricity prices in Nordic countries before and after the outbreak of war. Despite the low proportion of natural gas electricity generation, the empirical analysis reveals both direct and indirect transmission paths for natural gas prices in Nordic countries. Meanwhile, the theoretical analysis demonstrates how Nordic renewable (wind and solar) and other non-gas generators exercise market power through price bidding in the anticipation of an increase in gas prices or a shortage of gas supply, which results in higher electricity prices. Understanding the underlying factors and dynamics driving substantial price fluctuations in the Nordic electricity market is essential for comprehending the intricate interconnections within the European energy landscape.
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| 7. |
- Bai, Fan, et al.
(författare)
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Application of similarity theory in modeling the output characteristics of proton exchange membrane fuel cell
- 2021
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Ingår i: International journal of hydrogen energy. - : PERGAMON-ELSEVIER SCIENCE LTD. - 0360-3199 .- 1879-3487. ; 46:74, s. 36940-36953
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Tidskriftsartikel (refereegranskat)abstract
- Proton Exchange Membrane Fuel Cell (PEMFC) has attracted widespread interest. In the present work, similarity analysis is adopted for a three-dimensional single-phase isothermal model of PEMFC to derive similarity criteria. Seven kinds of input criteria (Pi(1) similar to Pi(7)) are obtained, relevant to the fluid flow, pressure drop, flow resistance in a porous medium, activity loss, diffusion mass transfer, convective mass transfer and ohmic loss in PEMFC respectively. Dimensionless voltage and dimensionless current density are defined as two output criteria. Numerical verifications show that if the seven criteria keep their individual values with their components vary in a wide range, the dimensionless polarization curves keep the same with a deviation about 1%, showing the validity and feasibility of the present analysis. From the effect on the dimensionless polarization curve, sensibility analysis shows that the seven criteria can be divided into three categories: strong (Pi(4) and Pi(7), -94.9% similar to +349.2%), mild to minor (Pi(5) and Pi(6), -4.5% similar to +5.0%), and negligible (Pi(1), Pi(2) and Pi(3), -1.2% similar to +1.1%). The similarity analysis approach can greatly save computation time in modeling the output characteristics of PEMFC. (C) 2021 Published by Elsevier Ltd on behalf of Hydrogen Energy Publications LLC.
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| 8. |
- Campana, Pietro Elia, et al.
(författare)
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Economic optimization of photovoltaic water pumping systems for irrigation
- 2015
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Ingår i: Energy Conversion and Management. - : Elsevier BV. - 0196-8904 .- 1879-2227. ; 95, s. 32-41
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Tidskriftsartikel (refereegranskat)abstract
- Photovoltaic water pumping technology is considered as a sustainable and economical solution to provide water for irrigation, which can halt grassland degradation and promote farmland conservation in China. The appropriate design and operation significantly depend on the available solar irradiation, crop water demand, water resources and the corresponding benefit from the crop sale. In this work, a novel optimization procedure is proposed, which takes into consideration not only the availability of ground-water resources and the effect of water supply on crop yield, but also the investment cost of photovoltaic water pumping system and the revenue from crop sale. A simulation model, which combines the dynamics of photovoltaic water pumping system, groundwater level, water supply, crop water demand and crop yield, is employed during the optimization. To prove the effectiveness of the new optimization approach, it has been applied to an existing photovoltaic water pumping system. Results show that the optimal configuration can guarantee continuous operations and lead to a substantial reduction of photovoltaic array size and consequently of the investment capital cost and the payback period. Sensitivity studies have been conducted to investigate the impacts of the prices of photovoltaic modules and forage on the optimization. Results show that the water resource is a determinant factor.
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| 9. |
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| 10. |
- Campana, Pietro Elia, et al.
(författare)
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Managing agricultural drought in Sweden using a novel spatially-explicit model from the perspective of water-food-energy nexus
- 2018
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Ingår i: Journal of Cleaner Production. - : Elsevier. - 0959-6526 .- 1879-1786. ; 197, s. 1382-1393
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Tidskriftsartikel (refereegranskat)abstract
- Using a multi-disciplinary approach, this paper integrated spatial analysis with agricultural and energy system modelling to assess the impacts of drought on crop water demand, water availability, crop yield, and electricity requirements for irrigation. This was done by a novel spatially-explicit and integrated water-food-energy nexus model, using the spatial climatic data generated by the mesoscale MESAN and STRANG models. In this study, the model was applied to quantify the effects of drought on the Swedish irrigation sector in 2013, a typical drought year, for a specific crop. The results show that drought can severely affect the crop yield if irrigation is not applied, with a peak yield reduction of 18 t/ha, about 50 % loss as compared to the potential yield in irrigated conditions. Accordingly, the water and energy requirements for irrigation to halt the negative drought effects and maintain high yields are significant, with the peaks up to 350 mm and 700 kWh per hectare. The developed model can be used to provide near real-time guidelines for a comprehensive drought management system. The model also has significant potentials for applications in precision agriculture, especially using high-resolution satellite data.
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