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Dr. Chuanbo Xu
North China Electric Power University School of Economics and Management

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Research Keywords & Expertise

0 Low Carbon
0 Decision Making under Uncertainty
0 Renewable and Sustainable Energy
0 project management
0 multi-criteria decision making problem

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Short Biography

1. Xu CB et al., Data-driven configuration optimization of an off-grid wind/PV/hydrogen system based on modified NSGA-II and CRITIC-TOPSIS, Energy Conversion and Management, 2020 2. Xu CB et al., What are the critical barriers to the development of hydrogen refueling stations in China? A modified fuzzy DEMATEL approach, Energy Policy, 2020 3. Wu YN, Xu CB*, et al., Portfolio selection of distributed energy generation projects considering uncertainty and project interaction under different enterprise strategic scenarios. Applied Energy, 2019.

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Journal article
Published: 22 January 2021 in Sustainability
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Accurate wind power forecasting is essential to reduce the negative impact of wind power on the operation of the grid and the operation cost of the power system. Day-ahead wind power forecasting plays an important role in the day-ahead electricity spot trading market. However, the instability of the wind power series makes the forecast difficult. To improve forecast accuracy, a hybrid optimization algorithm is established in this study, which combines variational mode decomposition (VMD), maximum relevance & minimum redundancy algorithm (mRMR), long short-term memory neural network (LSTM), and firefly algorithm (FA) together. Firstly, the original historical wind power sequence is decomposed into several characteristic model functions with VMD. Then, mRMR is applied to obtain the best feature set by analyzing the correlation between each component. Finally, the FA is used to optimize the various parameters LSTM. Adding the forecasting results of all sub-sequences acquires the forecasting result. It turns out that the proposed hybrid algorithm is superior to the other six comparison algorithms. At the same time, an additional case is provided to further verify the adaptability and stability of the proposed hybrid model.

ACS Style

Guangyu Qin; QingYou Yan; Jingyao Zhu; Chuanbo Xu; Daniel Kammen. Day-Ahead Wind Power Forecasting Based on Wind Load Data Using Hybrid Optimization Algorithm. Sustainability 2021, 13, 1164 .

AMA Style

Guangyu Qin, QingYou Yan, Jingyao Zhu, Chuanbo Xu, Daniel Kammen. Day-Ahead Wind Power Forecasting Based on Wind Load Data Using Hybrid Optimization Algorithm. Sustainability. 2021; 13 (3):1164.

Chicago/Turabian Style

Guangyu Qin; QingYou Yan; Jingyao Zhu; Chuanbo Xu; Daniel Kammen. 2021. "Day-Ahead Wind Power Forecasting Based on Wind Load Data Using Hybrid Optimization Algorithm." Sustainability 13, no. 3: 1164.

Journal article
Published: 07 September 2020 in Journal of Cleaner Production
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The construction of distributed photovoltaic power stations (DPVPS) along high-speed railway can supply power for the traction power supply system (TPSS) of high-speed railway. The DPVPS site selection is a natural call from the practice with the consideration of full use of solar PV. This paper addresses a multi-criteria decision-making (MCDM) framework for DPVPS site selection along high-speed railway for the first time. In this framework, an evaluation criteria system is established. Considering the particularity of DPVPS site selection problem along high-speed railway, two new criteria namely power consumption capacity of high-speed railway TPSS and impact on high-speed railway TPSS are presented innovatively. In view of the strong grey correlations among criteria, the fuzzy grey relational projection (FGRP) method is applied to select the optimal site which is greatly suitable to deal with the grey correlations. A case in Hebei Province with sensitivity analysis also illustrates the robustness and effectiveness of the framework. The calculation results of the case indicate that the sub-criteria of impact on high-speed railway TPSS (C26) has the largest comprehensive weight, which is 0.129. Among the four candidate sites, G1 gets the highest final score of 0.653. This paper puts forward an effective tool for railway companies to choose the most suitable site to build DPVPS along high-speed railway, which has the certain practical significance.

ACS Style

Chentao Li; Chuanbo Xu; Xingmei Li. A multi-criteria decision-making framework for site selection of distributed PV power stations along high-speed railway. Journal of Cleaner Production 2020, 277, 124086 .

AMA Style

Chentao Li, Chuanbo Xu, Xingmei Li. A multi-criteria decision-making framework for site selection of distributed PV power stations along high-speed railway. Journal of Cleaner Production. 2020; 277 ():124086.

Chicago/Turabian Style

Chentao Li; Chuanbo Xu; Xingmei Li. 2020. "A multi-criteria decision-making framework for site selection of distributed PV power stations along high-speed railway." Journal of Cleaner Production 277, no. : 124086.

Journal article
Published: 13 May 2020 in Energy Conversion and Management
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This paper proposes a data-driven two-stage multi-criteria decision-making (MCDM) framework to investigate the optimal configuration of a stand-alone wind/PV/hydrogen system. In the first stage, a modified non-dominated sorting genetic algorithm (NSGA)-II based on reinforcement learning is utilized to determine a set of Pareto solutions. The objectives considered are to minimize the levelized cost of energy (LCOE), the loss of power supply possibility (LPSP) and the power abandonment rate (PAR), simultaneously. In the second stage, the Criteria Importance Though Intercrieria Correlation (CRITIC) method is utilized to determine the weight of the three objectives, while the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach is employed to select the unique best solution from Pareto solutions. To verify the effectiveness, the framework is applied to the wind/PV/hydrogen system located in Aksay Kazak Autonomous County, Gansu Province, China to meet an off-grid industrial park’s load demand of 1603 kWh/day and peak load of 117.17 kW. The result states that the optimal system, which consists of 83.2 kW PV panels, 160 kW wind turbines, 20 kW fuel cells, 54 kW electrolyzers and 450 m3 hydrogen storage tanks, owns the LCOE of 0.226 $/kWh, the LPSP of 4.01% and the PAR of 2.15%.

ACS Style

Chuanbo Xu; Yiming Ke; Yanbin Li; Han Chu; Yunna Wu. Data-driven configuration optimization of an off-grid wind/PV/hydrogen system based on modified NSGA-II and CRITIC-TOPSIS. Energy Conversion and Management 2020, 215, 112892 .

AMA Style

Chuanbo Xu, Yiming Ke, Yanbin Li, Han Chu, Yunna Wu. Data-driven configuration optimization of an off-grid wind/PV/hydrogen system based on modified NSGA-II and CRITIC-TOPSIS. Energy Conversion and Management. 2020; 215 ():112892.

Chicago/Turabian Style

Chuanbo Xu; Yiming Ke; Yanbin Li; Han Chu; Yunna Wu. 2020. "Data-driven configuration optimization of an off-grid wind/PV/hydrogen system based on modified NSGA-II and CRITIC-TOPSIS." Energy Conversion and Management 215, no. : 112892.

Journal article
Published: 19 April 2020 in Energy Policy
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Hydrogen fuel cell vehicle is one of the important modalities of the next generation of new energy vehicles. As the basic infrastructure of hydrogen fuel cell vehicles, hydrogen refueling stations (HRSs) have drawn attention from all social circles. However, hindered by various barriers, the development of HRSs is much slower than the Chinese government's expectation. Hence, this study aims to explore critical barriers of the HRS development in China based on a modified fuzzy decision-making trial and evaluation laboratory (DEMATEL) method. Firstly, a barrier list is identified through a literature survey and expert consultation, which consists of four categories (economic, technological, social and political-regulatory aspect) and 12 potential barriers. Later, considering the subjectivity of threshold setting in the traditional fuzzy DEMATEL method, the K-means clustering algorithm is utilized to optimize the threshold value, and thus a modified fuzzy DEMATEL approach is proposed to investigate the prominence of these barriers and the cause-effect relationships among them. The results show that six barriers are regarded as key barriers to China's HRS development, and corresponding policy measures are formulated to mitigate or eliminate these critical barriers.

ACS Style

Chuanbo Xu; Yunna Wu; Shuyu Dai. What are the critical barriers to the development of hydrogen refueling stations in China? A modified fuzzy DEMATEL approach. Energy Policy 2020, 142, 111495 .

AMA Style

Chuanbo Xu, Yunna Wu, Shuyu Dai. What are the critical barriers to the development of hydrogen refueling stations in China? A modified fuzzy DEMATEL approach. Energy Policy. 2020; 142 ():111495.

Chicago/Turabian Style

Chuanbo Xu; Yunna Wu; Shuyu Dai. 2020. "What are the critical barriers to the development of hydrogen refueling stations in China? A modified fuzzy DEMATEL approach." Energy Policy 142, no. : 111495.

Journal article
Published: 01 March 2018 in Energy
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ACS Style

Yunna Wu; Chuanbo Xu; Ting Zhang. Evaluation of renewable power sources using a fuzzy MCDM based on cumulative prospect theory: A case in China. Energy 2018, 147, 1227 -1239.

AMA Style

Yunna Wu, Chuanbo Xu, Ting Zhang. Evaluation of renewable power sources using a fuzzy MCDM based on cumulative prospect theory: A case in China. Energy. 2018; 147 ():1227-1239.

Chicago/Turabian Style

Yunna Wu; Chuanbo Xu; Ting Zhang. 2018. "Evaluation of renewable power sources using a fuzzy MCDM based on cumulative prospect theory: A case in China." Energy 147, no. : 1227-1239.

Journal article
Published: 12 May 2017 in Information
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This paper presents a new approach to solve the multi-criteria group decision making (MCGDM) problem where criteria values take the form of 2-tuple linguistic information. Firstly, a 2-tuple hybrid ordered weighted geometric (THOWG) operator is proposed, which synthetically considers the importance of both individual and the ordered position so as to overcome the defects of existing operators. Secondly, combining the advantages of the cloud model and 2-tuple linguistic variable, a new generating cloud method is proposed to transform 2-tuple linguistic variables into clouds. Thirdly, we further define some new cloud algorithms, such as cloud possibility degree and cloud support degree which can be respectively used to compare clouds and determine the criteria weights. Furthermore, a new approach for 2-tuple linguistic group decision making is presented on the basis of the THOWG operator, the improved generating cloud method as well as the new cloud algorithms. Finally, an example of assessing the social effects of biomass power plants (BPPS) is illustrated to verify the application and feasible of the developed approach, and a comparative analysis is also conducted to validate the effectiveness of the proposed method.

ACS Style

Haobo Zhang; Yunna Wu; Jianwei Gao; Chuanbo Xu. A Method for Multi-Criteria Group Decision Making with 2-Tuple Linguistic Information Based on Cloud Model. Information 2017, 8, 54 .

AMA Style

Haobo Zhang, Yunna Wu, Jianwei Gao, Chuanbo Xu. A Method for Multi-Criteria Group Decision Making with 2-Tuple Linguistic Information Based on Cloud Model. Information. 2017; 8 (2):54.

Chicago/Turabian Style

Haobo Zhang; Yunna Wu; Jianwei Gao; Chuanbo Xu. 2017. "A Method for Multi-Criteria Group Decision Making with 2-Tuple Linguistic Information Based on Cloud Model." Information 8, no. 2: 54.

Journal article
Published: 19 October 2016 in Energies
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The site selection plays an important role in the entire life cycle of a tidal power plant (TPP) project. However, some problems decrease the evaluation quality of TPP site selection: (a) suitable and effective methods are scarce since the TPP site selection involves multiple forms of data; (b) there is no comprehensive evaluation index system due to the unilateralism of existing criteria. In this paper, we firstly propose a novel method based on interval number with probability distribution weighted operation and stochastic dominance degree. It takes all stakeholders’ preferences into consideration and can simultaneously deal with different forms of data in the TPP site selection; then, a comprehensive evaluation index system for TPP site selection is constructed on the basis of academic literature, feasibility research reports and expert opinions in different fields. It takes the factors of construction conditions, existing policies, social impacts as well as ecological and environmental impacts which reflects the inherent characteristics of TPP site selection fully into account. Finally, a Chinese case study is given to illustrate the applicability and effectiveness of the proposed method.

ACS Style

Yunna Wu; Chuanbo Xu; Hu Xu. Optimal Site Selection of Tidal Power Plants Using a Novel Method: A Case in China. Energies 2016, 9, 832 .

AMA Style

Yunna Wu, Chuanbo Xu, Hu Xu. Optimal Site Selection of Tidal Power Plants Using a Novel Method: A Case in China. Energies. 2016; 9 (10):832.

Chicago/Turabian Style

Yunna Wu; Chuanbo Xu; Hu Xu. 2016. "Optimal Site Selection of Tidal Power Plants Using a Novel Method: A Case in China." Energies 9, no. 10: 832.