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description Publicationkeyboard_double_arrow_right Article , Journal 2017Publisher:Institute of Electrical and Electronics Engineers (IEEE) Improving the accuracy of power system load forecasting is important for economic dispatch. However, a load sequence is highly nonstationary and hence makes accurate forecasting difficult. In this paper, a method based on wavelet decomposition (WD) and a second-order gray neural network combined with an augmented Dickey-Fuller (ADF) test is proposed to improve the accuracy of load forecasting. First, the load sequence is decomposed by WD to reduce the nonstationary load sequence. Then, the ADF test is adopted as the test method for the stationary load sequence of each decomposed component after WD in which the test results determine the best WD level. Finally, because forecasting the wavelet details characterized by high frequencies is difficult owing to its fluctuation, a second-order gray forecasting model is used to forecast each component after WD. Furthermore, to obtain the optimum parameters of the second-order gray forecasting model, the neural network mapping approach is used to build the second-order gray neural network forecasting model. The simulation result of a real load sequence verifies that the method proposed in this paper can effectively improve the load-forecasting accuracy.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/access.2017.2738029&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 122 citations 122 popularity Top 1% influence Top 1% impulse Top 1% Powered by BIP!
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/access.2017.2738029&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2025Publisher:Elsevier BV Authors: Sixun Zhou;Rujing Yan;
Rujing Yan
Rujing Yan in OpenAIREJing Zhang;
Yu He; +3 AuthorsJing Zhang
Jing Zhang in OpenAIRESixun Zhou;Rujing Yan;
Rujing Yan
Rujing Yan in OpenAIREJing Zhang;
Yu He; Xianxian Geng; Yuanbo Li; Changkun Yu;Jing Zhang
Jing Zhang in OpenAIREadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.renene.2025.122823&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.renene.2025.122823&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021Publisher:Institute of Electrical and Electronics Engineers (IEEE) Authors:Jing Zhang;
Jing Zhang
Jing Zhang in OpenAIREDian Qin;
Yongchun Ye; Yu He; +4 AuthorsDian Qin
Dian Qin in OpenAIREJing Zhang;
Jing Zhang
Jing Zhang in OpenAIREDian Qin;
Yongchun Ye; Yu He; Xiaofan Fu; Jing Yang; Guoyi Shi;Dian Qin
Dian Qin in OpenAIREHeng Zhang;
Heng Zhang
Heng Zhang in OpenAIREDue to the source and load prediction errors and uncertainties, the real operation state of microgrid may deviate significantly from the expected state, which leads to prevent the system from reaching its expected economic effects. In order to obtain the optimal economic effects for microgrid scheduling, an optimal microgrid scheduling model considered the demand responses is built in this paper firstly, and then a multi-time scale economic scheduling method based on day-ahead robust optimization and intraday model predictive control (MPC), is developed as well. Moreover, in the day-ahead stage, the long-time scale interval is set as 1 h and the robust optimization is used to address the low-frequency components in prediction errors and uncertainties. Meanwhile, the robust optimization enables to gain the day-head optimal economic scheduling plan for the microgrid and to keep the system operating effectively even when large-scale fluctuations happen. Furthermore, in the intraday stage, the short-time scale interval is set as 15 mins and MPC is adopted to track and correct the day-ahead economic scheduling plan, which enables to address the high-frequency components in prediction errors and uncertainties. Finally, simulation results demonstrate the feasibility of the proposed optimal microgrid scheduling model and the validity of the proposed multi-time scale economic scheduling method.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/access.2021.3118716&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 19 citations 19 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/access.2021.3118716&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2022Publisher:MDPI AG Authors:Weili Liu;
Weili Liu
Weili Liu in OpenAIREJing Zhang;
Wei Wei; Tao Qin; +3 AuthorsJing Zhang
Jing Zhang in OpenAIREWeili Liu;
Weili Liu
Weili Liu in OpenAIREJing Zhang;
Wei Wei; Tao Qin; Yuanchen Fan; Fei Long;Jing Zhang
Jing Zhang in OpenAIREJing Yang;
Jing Yang
Jing Yang in OpenAIREdoi: 10.3390/app12105221
The technology of wireless sensor networks (WSNs) is developing rapidly, and it has been applied in diverse fields, such as medicine, environmental control, climate prediction, monitoring, etc. Location is one of the critical fields in WSNs. Time difference of arrival (TDOA) has been widely used to locate targets because it has a simple model, and it is easy to implement. Aiming at the problems of large deviation and low accuracy of the nonlinear equation solution for TDOA, many metaheuristic algorithms have been proposed to address the problems. By analyzing the available literature, it can be seen that the swarm intelligence metaheuristic has achieved remarkable results in this domain. The aim of this paper is to achieve further improvements in solving the localization problem by TDOA. To achieve this goal, we proposed a hybrid bald eagle search (HBES) algorithm, which can improve the performance of the bald eagle search (BES) algorithm by using strategies such as chaotic mapping, Lévy flight, and opposition-based learning. To evaluate the performance of HBES, we compared HBES with particle swarm algorithm, butterfly optimization algorithm, COOT algorithm, Grey Wolf algorithm, and sine cosine algorithm based on 23 test functions. The comparison results show that the proposed algorithm has better search performance than other reputable metaheuristic algorithms. Additionally, the HBES algorithm was used to solve the TDOA location problem by simulating the deployment of different quantities of base stations in a noise situation. The results show that the proposed method can obtain more consistent and precise locations of unknown target nodes in the TDOA localization than that of others.
Applied Sciences arrow_drop_down Applied SciencesOther literature type . 2022License: CC BYFull-Text: http://www.mdpi.com/2076-3417/12/10/5221/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/app12105221&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 11 citations 11 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Applied Sciences arrow_drop_down Applied SciencesOther literature type . 2022License: CC BYFull-Text: http://www.mdpi.com/2076-3417/12/10/5221/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/app12105221&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal , Other literature type 2019Publisher:MDPI AG doi: 10.3390/en12153012
As renewable energy sources connecting to power systems continue to improve and new-type loads, such as electric vehicles, grow rapidly, direct current (DC) microgrids are attracting great attention in distribution networks. In order to satisfy the voltage stability requirements of island DC microgrids, the problem of inaccurate load power dispatch caused by line resistance must be solved and the defects of centralized communication and control must be overcome. A hierarchical, coordinated, multiple-mode control strategy based on the switch of different operation modes is proposed in this paper and a three-layer control structure is designed for the control strategy. Based on conventional droop control, a current-sharing layer and a multi-mode switching layer are used to ensure the stable operation of the DC microgrid. Accurate load power dispatch is satisfied using a difference discrete consensus algorithm. Furthermore, virtual bus voltage information is applied to guarantee smooth switching between various modes, which safeguards voltage stability. Simulation verification is carried out for the proposed control strategy by power systems computer aided design/electromagnetic transients including DC (PSCAD/EMTDC). The results indicate that the proposed control strategy guarantees the voltage stability of island DC microgrids and accurate load power dispatch under different operation modes.
Energies arrow_drop_down EnergiesOther literature type . 2019License: CC BYFull-Text: http://www.mdpi.com/1996-1073/12/15/3012/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en12153012&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 8 citations 8 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert Energies arrow_drop_down EnergiesOther literature type . 2019License: CC BYFull-Text: http://www.mdpi.com/1996-1073/12/15/3012/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en12153012&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal , Other literature type 2021Publisher:MDPI AG Luqin Fan;Jing Zhang;
Yu He; Ying Liu; Tao Hu;Jing Zhang
Jing Zhang in OpenAIREHeng Zhang;
Heng Zhang
Heng Zhang in OpenAIREdoi: 10.3390/en14030584
Microgrid has flexible composition, a complex operation mechanism, and a large amount of data while operating. However, optimization methods of microgrid scheduling do not effectively accumulate and utilize the scheduling knowledge at present. This paper puts forward a microgrid optimal scheduling method based on Deep Deterministic Policy Gradient (DDPG) and Transfer Learning (TL). This method uses Reinforcement Learning (RL) to learn the scheduling strategy and accumulates the corresponding scheduling knowledge. Meanwhile, the DDPG model is introduced to extend the microgrid scheduling strategy action from the discrete action space to the continuous action space. On this basis, this paper holds that a microgrid optimal scheduling TL algorithm on the strength of the actual supply and demand similarity is proposed with a purpose of making use of the existing scheduling knowledge effectively. The simulation results indicate that this paper can provide optimal scheduling strategy for microgrid with complex operation mechanism flexibly and efficiently through the effective accumulation of scheduling knowledge and the utilization of scheduling knowledge through TL.
Energies arrow_drop_down EnergiesOther literature type . 2021License: CC BYFull-Text: http://www.mdpi.com/1996-1073/14/3/584/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en14030584&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 27 citations 27 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Energies arrow_drop_down EnergiesOther literature type . 2021License: CC BYFull-Text: http://www.mdpi.com/1996-1073/14/3/584/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en14030584&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024Publisher:MDPI AG Authors: Junqiu Fan;Jing Zhang;
Long Yuan; Rujing Yan; +3 AuthorsJing Zhang
Jing Zhang in OpenAIREJunqiu Fan;Jing Zhang;
Long Yuan; Rujing Yan;Jing Zhang
Jing Zhang in OpenAIREYu He;
Weixing Zhao; Nang Nin;doi: 10.3390/su16135722
Integrating carbon capture and storage (CCS) technology into an integrated energy system (IES) can reduce its carbon emissions and enhance its low-carbon performance. However, the full CCS of flue gas displays a strong coupling between lean and rich liquor as carbon dioxide liquid absorbents. Its integration into IESs with a high penetration level of renewables results in insufficient flexibility and renewable curtailment. In addition, integrating split-flow CCS of flue gas facilitates a short capture time, giving priority to renewable energy. To address these limitations, this paper develops a carbon capture, utilization, and storage (CCUS) method, into which storage tanks for lean and rich liquor and a two-stage power-to-gas (P2G) system with multiple utilizations of hydrogen including a fuel cell and a hydrogen-blended CHP unit are introduced. The CCUS is integrated into an IES to build an electricity–heat–hydrogen–gas IES. Accordingly, a deep low-carbon economic optimization strategy for this IES, which considers stepwise carbon trading, coal consumption, renewable curtailment penalties, and gas purchasing costs, is proposed. The effects of CCUS, the two-stage P2G system, and stepwise carbon trading on the performance of this IES are analyzed through a case-comparative analysis. The results show that the proposed method allows for a significant reduction in both carbon emissions and total operational costs. It outperforms the IES without CCUS with an 8.8% cost reduction and a 70.11% reduction in carbon emissions. Compared to the IES integrating full CCS, the proposed method yields reductions of 6.5% in costs and 24.7% in emissions. Furthermore, the addition of a two-stage P2G system with multiple utilizations of hydrogen further amplifies these benefits, cutting costs by 13.97% and emissions by 12.32%. In addition, integrating CCUS into IESs enables the full consumption of renewables and expands hydrogen utilization, and the renewable consumption proportion in IESs can reach 69.23%.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16135722&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 3 citations 3 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16135722&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024Publisher:Elsevier BV Rujing Yan;
Rujing Yan
Rujing Yan in OpenAIREMou Wu;
Junqiu Fan; Chengxu Sun;Jiangjiang Wang;
Yu He; Hongpeng Liu; Pei Li;Jiangjiang Wang
Jiangjiang Wang in OpenAIREJing Zhang;
Jing Zhang
Jing Zhang in OpenAIREEnergy Conversion an... arrow_drop_down Energy Conversion and ManagementArticle . 2024 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.enconman.2024.118263&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu7 citations 7 popularity Average influence Average impulse Top 10% Powered by BIP!
more_vert Energy Conversion an... arrow_drop_down Energy Conversion and ManagementArticle . 2024 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.enconman.2024.118263&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2025Publisher:Elsevier BV Junqiu Fan; Rujing Yan; Yu He;Jing Zhang;
Weixing Zhao; Mingshun Liu; Su An; Qingfeng Ma;Jing Zhang
Jing Zhang in OpenAIREadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.renene.2025.122466&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu3 citations 3 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.renene.2025.122466&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu