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Publications (10 of 18) Show all publications
Du, J., Zheng, J., Liang, Y., Liao, Q., Wang, B., Sun, X., . . . Yan, J. (2023). A theory-guided deep-learning method for predicting power generation of multi-region photovoltaic plants. Engineering applications of artificial intelligence, 118, Article ID 105647.
Open this publication in new window or tab >>A theory-guided deep-learning method for predicting power generation of multi-region photovoltaic plants
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2023 (English)In: Engineering applications of artificial intelligence, ISSN 0952-1976, E-ISSN 1873-6769, Vol. 118, article id 105647Article in journal (Refereed) Published
Abstract [en]

Recently, clean solar energy has aroused wide attention due to its excellent potential for electricity production. A highly accurate prediction of photovoltaic power generation (PVPG) is the basis of the production and transmission of electricity. However, the current works neglect the regional correlation characteristics of PVPG and few studies propose an effective framework by incorporating prior knowledge for more physically reasonable results. In this work, a hybrid deep learning framework is proposed for simultaneously capturing the spatial correlations among different regions and temporal dependency patterns with various importance. The scientific theory and domain knowledge are incorporated into the deep learning model to make the predicted results possess physical reasonability. Subsequently, the theory-guided and attention-based CNN-LSTM (TG-A-CNN-LSTM) is constructed for PVPG prediction. In the training process, data mismatch and boundary constraint are incorporated into the loss function, and the positive constraint is utilized to restrict the output of the model. After receiving the parameters of the neural network, a TG-A-CNN-LSTM model, whose predicted results obey the physical law, is constructed. A real energy system in five regions is used to verify the accuracy of the proposed model. The predicted results indicate that TG-A-CNN-LSTM can achieve higher precision of PVPG prediction than other prediction models, with RMSE being 11.07, MAE being 4.98, and R2 being 0.94, respectively. Moreover, the performance of prediction models with sparse data is tested to illustrate the stability and robustness of TG-A-CNN-LSTM. 

Place, publisher, year, edition, pages
Elsevier Ltd, 2023
Keywords
Local dependency, Multi-region, Photovoltaic power generation prediction, TG-A-CNN-LSTM, Theory guided, Time series, Domain Knowledge, Electric power generation, Forecasting, Learning systems, Long short-term memory, Solar energy conversion, Solar power generation, Generation predictions, Learning methods, Photovoltaic power generation, Prediction modelling, Times series, Solar energy
National Category
Energy Engineering
Identifiers
urn:nbn:se:mdh:diva-61153 (URN)10.1016/j.engappai.2022.105647 (DOI)000894964700008 ()2-s2.0-85142808671 (Scopus ID)
Available from: 2022-12-07 Created: 2022-12-07 Last updated: 2023-01-25Bibliographically approved
Qiu, R., Liang, Y., Liao, Q., Wei, X., Zhang, H., Jiao, Y. & Zhang, H. (2022). A model-experience-driven method for the planning of refined product primary logistics. Chemical Engineering Science, 254, Article ID 117607.
Open this publication in new window or tab >>A model-experience-driven method for the planning of refined product primary logistics
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2022 (English)In: Chemical Engineering Science, ISSN 0009-2509, E-ISSN 1873-4405, Vol. 254, article id 117607Article in journal (Refereed) Published
Abstract [en]

Logistics planning is regarded as the most complex part of supply chain management for refined products. A vital knowledge gap still exists in understanding the trade-offs between the economy and the practicability of logistics schemes. Focus on this issue, this paper proposes a model-experience-driven method for the planning of refined product primary logistics. The method couples three sub-modules: (1) use coordinator's preference information and convex function interpolation to construct satisfaction indicator; (2) set up a multi-objective model for logistics coordination and optimization considering supply adjustment and secondary delivery; (3) adopt the augmented ɛ-constraint method to obtain the Pareto solutions and balance the economy and satisfaction indicators. The method is verified by a small-scale system, where the satisfaction degree increases by 77% while the logistics cost remains unchanged. The method is also successfully applied to a large-scale system with 29 refineries and 196 market depots, where Pareto logistics schemes are obtained and the supply–demand imbalance is greatly eased. The proposed method can help provide theoretical guidance for real-world logistics planning.

Place, publisher, year, edition, pages
Elsevier Ltd, 2022
Keywords
Coordination and optimization, Model-experience-driven, Primary logistics planning, Refined product, Supply and demand imbalance
National Category
Energy Engineering
Identifiers
urn:nbn:se:mdh:diva-57736 (URN)10.1016/j.ces.2022.117607 (DOI)000793231400006 ()2-s2.0-85126879773 (Scopus ID)
Available from: 2022-04-06 Created: 2022-04-06 Last updated: 2022-06-01Bibliographically approved
Wu, Y., Xia, T., Wang, Y., Zhang, H., Feng, X., Song, X. & Shibasaki, R. (2022). A synchronization methodology for 3D offshore wind farm layout optimization with multi-type wind turbines and obstacle-avoiding cable network. Renewable energy, 185, 302-320
Open this publication in new window or tab >>A synchronization methodology for 3D offshore wind farm layout optimization with multi-type wind turbines and obstacle-avoiding cable network
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2022 (English)In: Renewable energy, ISSN 0960-1481, E-ISSN 1879-0682, Vol. 185, p. 302-320Article in journal (Refereed) Published
Abstract [en]

Offshore wind farms are increasingly becoming the focus of clean sources market because of the huge energy potential and fast-maturing technology. The existing researches normally optimize the wind turbine layout and two-dimensional cable routing independently. This work focuses on the synchronization optimization of site selection of the offshore wind farm, three-dimensional wind turbine layout and three-dimensional cable network routing based on meta-heuristic algorithms and geographic information systems. Several practical issues, i.e., restricted areas, power generation, cable network and energy loss, are taken into consideration. A two-layer model is proposed. The outer layer model is for the site selection and the wind turbine layout optimization. The inner layer model is for the obstacle-avoiding cable routing optimization. In this stage, the seabed terrain is considered for the first time. The proposed integrated model is complex and non-convex. Thus, a hybrid method including an improved ant colony optimization combined with genetic algorithm, dual-simplex method and Kruskal algorithm is proposed to search the solution more efficiently. The initialization stage of the hybrid method is improved from random assignment to directional assignment. The directional solution is obtained by the widely used genetic algorithm. A case study based on a real offshore wind farm is established to prove the effectiveness of the proposed methodology. The results show an over one million dollars increase in annual benefit compared with conventional methods.

Place, publisher, year, edition, pages
Elsevier Ltd, 2022
Keywords
Cable network, Meta-heuristic algorithms, Multi-type wind turbine, Offshore wind farm, Seabed terrain, Ant colony optimization, Cables, Electric utilities, Energy dissipation, Genetic algorithms, Heuristic algorithms, Linear programming, Offshore oil well production, Site selection, Wind turbines, Cable networks, Cable routing, Hybrid method, Layer model, Meta-heuristics algorithms, Obstacle-avoiding, Turbine layouts, Wind farm layout optimizations, Offshore wind farms, algorithm, methodology, network analysis, optimization, three-dimensional modeling, wind farm, wind turbine
National Category
Energy Engineering
Identifiers
urn:nbn:se:mdh:diva-56875 (URN)10.1016/j.renene.2021.12.057 (DOI)000778545900012 ()2-s2.0-85121619076 (Scopus ID)
Available from: 2022-01-12 Created: 2022-01-12 Last updated: 2022-05-04Bibliographically approved
Wei, X., Liang, Y., Qiu, R., Liao, Q., zhang, B., Jiao, Y. & Zhang, H. (2022). Assessing benefits in the flexibility of refined oil logistics from pipeline network integration reform: A case from South China. Chemical Engineering Science, 253, Article ID 117605.
Open this publication in new window or tab >>Assessing benefits in the flexibility of refined oil logistics from pipeline network integration reform: A case from South China
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2022 (English)In: Chemical Engineering Science, ISSN 0009-2509, E-ISSN 1873-4405, Vol. 253, article id 117605Article in journal (Refereed) Published
Abstract [en]

The pipeline network integration reform enables unified management of pipelines from different entities. For refined oil logistics, this paper proposes a framework based on the MILP optimization model to quantify its flexibility. Considering the uncertainty, three disturbances occur in the logistics concurrently, and 10,000 simulations are performed to obtain the turnover cost. The ratio of pipeline transportation cost to the calculated average turnover cost is defined as the flexibility indicator. Taking China's largest refined oil pipeline network as an example, the results show that the flexibility rises 8.9% after the reform. The paper also quantifies the impact of the reform on logistics flexibility in South China, which is embodied in achieving lower freights and GHG emissions, lower impact by fluctuations, higher pipeline utilization, more efficient oil product turnover, and the avoiding of depot shortages when facing logistical disturbances. The underlying reasons for the results and 3E analysis are analyzed.

Place, publisher, year, edition, pages
Elsevier Ltd, 2022
Keywords
3E analysis, Flexibility indicator, Policy quantification, Refined oil logistics optimization, Uncertainty
National Category
Energy Engineering
Identifiers
urn:nbn:se:mdh:diva-57711 (URN)10.1016/j.ces.2022.117605 (DOI)000793216600002 ()2-s2.0-85126587811 (Scopus ID)
Available from: 2022-03-30 Created: 2022-03-30 Last updated: 2022-05-25Bibliographically approved
Zhang, H. & Yan, J. (2022). Co-benefits of renewable energy development: A brighter sky brings greater renewable power. Joule, 6(6), 1142-1144
Open this publication in new window or tab >>Co-benefits of renewable energy development: A brighter sky brings greater renewable power
2022 (English)In: Joule, E-ISSN 2542-4351, Vol. 6, no 6, p. 1142-1144Article in journal, Editorial material (Refereed) Published
Abstract [en]

Air pollution reduction is one of the most straightforward co-benefits of PV development, but its mechanism is complex. In a recent One Earth paper, Chen et al. analyzed the respective effects of different factors on solar power performance and show that the co-benefits of air pollution control policies for PV over the past decade would be grossly underestimated. 

Place, publisher, year, edition, pages
Cell Press, 2022
National Category
Other Earth and Related Environmental Sciences
Identifiers
urn:nbn:se:mdh:diva-59454 (URN)10.1016/j.joule.2022.05.017 (DOI)000823446500002 ()2-s2.0-85132358518 (Scopus ID)
Available from: 2022-06-29 Created: 2022-06-29 Last updated: 2022-08-03Bibliographically approved
Zhang, H., Li, P., Zhang, Z., Li, W., Chen, J., Song, X., . . . Yan, J. (2022). Epidemic versus economic performances of the COVID-19 lockdown: A big data driven analysis. Cities, 120, Article ID 103502.
Open this publication in new window or tab >>Epidemic versus economic performances of the COVID-19 lockdown: A big data driven analysis
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2022 (English)In: Cities, ISSN 0264-2751, E-ISSN 1873-6084, Vol. 120, article id 103502Article in journal (Refereed) Published
Abstract [en]

Lockdown measures have been a “panacea” for pandemic control but also a violent “poison” for economies.Lockdown policies strongly restrict human mobility but mobility reduce does harm to economics. Governmentsmeet a thorny problem in balancing the pros and cons of lockdown policies, but lack comprehensive andquantified guides. Based on millions of financial transaction records, and billions of mobility data, we trackedspatio-temporal business networks and human daily mobility, then proposed a high-resolution two-sidedframework to assess the epidemiological performance and economic damage of different lockdown policies. Wefound that the pandemic duration under the strictest lockdown is less about two months than that under thelightest lockdown, which makes the strictest lockdown characterize both epidemiologically and economicallyefficient. Moreover, based on the two-sided model, we explored the spatial lockdown strategy. We argue thatcutting off intercity commuting is significant in both epidemiological and economical aspects, and finally helpedgovernments figure out the Pareto optimal solution set of lockdown strategy.

National Category
Public Health, Global Health, Social Medicine and Epidemiology
Identifiers
urn:nbn:se:mdh:diva-57199 (URN)10.1016/j.cities.2021.103502 (DOI)000792678800002 ()2-s2.0-85118714443 (Scopus ID)
Available from: 2022-02-02 Created: 2022-02-02 Last updated: 2022-05-25Bibliographically approved
Yu, Q., Xie, Y., Li, W., Zhang, H., Liu, X., Shang, W.-L. -., . . . Yan, J. (2022). GPS data in urban bicycle-sharing: Dynamic electric fence planning with assessment of resource-saving and potential energy consumption increasement. Applied Energy, 322, Article ID 119533.
Open this publication in new window or tab >>GPS data in urban bicycle-sharing: Dynamic electric fence planning with assessment of resource-saving and potential energy consumption increasement
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2022 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 322, article id 119533Article in journal (Refereed) Published
Abstract [en]

As a newly-emerging option of shared transportation, Internet-enabled dockless bicycle sharing is well accepted by the public. The implementation of electric fences has great potential to tackle the problem of random parking in bicycle sharing services. However, the deployment of electric fences would have a negative impact on the convenience of bicycle sharing services, which might lead to an increase in energy consumption among customers who switch their methods of transportation. This paper proposes a dynamic electric fence planning method with an assessment of resource-saving and potential energy consumption increasement. An agent-based model is proposed to simulate the trips and evaluated the performance of static and dynamic electric fences. The results show that dynamic electric fences require significantly shorter walking distances than static electric fences. The implementation of electric fences in the city center can significantly avoid random parking and improve the parking tidiness of bicycles. The implementation of dynamic and static electric fences can averagely save 25.31% and 27.76% bicycle resources. By estimating travel mode shifting, dynamic electric fence can reduce energy consumption by 5.79% per day compared to the static electric fence situation. 

Place, publisher, year, edition, pages
Elsevier, 2022
Keywords
Agent-based model, Bicycle resource-saving, Bicycle-sharing, Electric fence, Spatial analysis
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mdh:diva-59531 (URN)10.1016/j.apenergy.2022.119533 (DOI)000828540800001 ()2-s2.0-85132859241 (Scopus ID)
Available from: 2022-07-06 Created: 2022-07-06 Last updated: 2022-08-03Bibliographically approved
Jiao, Y., Qiu, R., Liang, Y., Liao, Q., Tu, R., Wei, X. & Zhang, H. (2022). Integration optimization of production and transportation of refined oil: A case study from China. Chemical engineering research & design, 188, 39-49
Open this publication in new window or tab >>Integration optimization of production and transportation of refined oil: A case study from China
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2022 (English)In: Chemical engineering research & design, ISSN 0263-8762, E-ISSN 1744-3563, Vol. 188, p. 39-49Article in journal (Refereed) Published
Abstract [en]

The logistics management of refined oil under a separation of production and transportation leads to high logistics costs and a mismatch between the supply and demand sides. This paper intends to develop a general framework to assess the impact of the integration of the production and transportation in terms of economic, environmental, and energy benefits. Firstly, this paper proposes a tactical-level mathematical model for optimizing the integration of production and transportation of refined oil to minimize the total cost. In the model, several factors, such as level of market demand, production capacity limits, transportation modes, and transportation capacity, are taken into consideration. Then, the energy, economy, and environment analysis method are applied to assess the impact of the integration on the field of refined oil logistics. Four scenarios are set up and a comparative analysis is carried out in detail in China. The optimal resource allocation scheme and production adjustment scheme for each scenario are obtained. The results show that after the integration, the logistics cost is reduced by 6.8 %− 11 %, the greenhouse gas emission is reduced by 7.3 %− 17.7 %, and the energy consumption per unit turnover is reduced by 4.4 %− 7.4 %. This proves that the integration of production and transportation guided by the proposed method performs positive economic, environmental, and energy benefits. Finally, policy implications are provided.

Place, publisher, year, edition, pages
Institution of Chemical Engineers, 2022
Keywords
3E analysis, Integration of production and transportation, Logistics optimization, Mathematical model, Refined oil
National Category
Other Mechanical Engineering
Identifiers
urn:nbn:se:mdh:diva-60202 (URN)10.1016/j.cherd.2022.09.037 (DOI)000911319800004 ()2-s2.0-85138769272 (Scopus ID)
Available from: 2022-10-12 Created: 2022-10-12 Last updated: 2023-02-01Bibliographically approved
Zou, X., Qiu, R., Zhang, B., Klemeš, J. J., Wang, B., Liao, Q., . . . Zhang, H. (2022). Roadmap to urban energy internet: Techno-enviro-economic analysis of renewable electricity and natural gas integrated energy system. Journal of Cleaner Production, 373, Article ID 133888.
Open this publication in new window or tab >>Roadmap to urban energy internet: Techno-enviro-economic analysis of renewable electricity and natural gas integrated energy system
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2022 (English)In: Journal of Cleaner Production, ISSN 0959-6526, E-ISSN 1879-1786, Vol. 373, article id 133888Article in journal (Refereed) Published
Abstract [en]

The integrated energy system which coordinates natural gas, renewable energy, and other energy subsystems is an effective way to promote a low-carbon economy. An effective framework for system assessment and optimisation is a critical issue. This paper takes a natural gas-wind-photovoltaic integrated energy system as the research object and uses the simulation software to analyse its techno-enviro-economic feasibility. Firstly, a mathematical model is customised to optimise the system installation and operation plans. Renewable electricity replaces some natural gas, resulting in pipeline pressure fluctuation. Here, the Stoner Pipeline Simulator software is used to simulate pipeline network operation to quantify the aforementioned pressure fluctuations. The proportion of renewable energy is gradually reduced until the network pressure fluctuation is less than 20% to ensure the stability of pipeline operation. Then, the optimal operation scheme can be determined. Taking three cities in Shandong, China, as cases, the results show that the proposed system is beneficial for urban energy internet development: (i) the total net present cost is reduced by 19.7%, 19.8%, and 20.8%, (ii) annual CO2 emission is reduced by 23.7%, 18.4%, and 12.2%; (iii) the levelised cost of energy is 0.142 $/kWh, 0.143$/kWh, and 0.153$/kWh. 

Place, publisher, year, edition, pages
Elsevier Ltd, 2022
Keywords
Energy internet, Integrated energy system, Natural gas, Pressure fluctuation, Renewable energy, Techno-enviro-economic analysis, Computer software, Gases, Pipelines, Renewable energy resources, Economics analysis, Energy, Integrated energy systems, Renewable electricity, Renewable energies, Roadmap, Techno-enviro-economic analyse, Urban energy, Economic analysis
National Category
Energy Systems
Identifiers
urn:nbn:se:mdh:diva-59936 (URN)10.1016/j.jclepro.2022.133888 (DOI)000863192300001 ()2-s2.0-85137261791 (Scopus ID)
Available from: 2022-09-14 Created: 2022-09-14 Last updated: 2022-11-17Bibliographically approved
Qiu, R., Liao, Q., Klemeš, J. J., Liang, Y., Guo, Z., Chen, J. & Zhang, H. (2022). Roadmap to urban energy internet with wind electricity-natural gas nexus: Economic and environmental analysis. Energy, 245
Open this publication in new window or tab >>Roadmap to urban energy internet with wind electricity-natural gas nexus: Economic and environmental analysis
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2022 (English)In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 245Article in journal (Refereed) Published
Abstract [en]

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%).

Place, publisher, year, edition, pages
Elsevier, 2022
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:mdh:diva-57429 (URN)10.1016/j.energy.2022.123231 (DOI)000792587100003 ()2-s2.0-85123927856 (Scopus ID)
Available from: 2022-02-16 Created: 2022-02-16 Last updated: 2022-06-01Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0002-4641-0641

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