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Sen Guo
School of Economics and Management, North China Electric Power University, Beijing 102206, China and Beijing Key Laboratory of New Energy and Low-Carbon Development (North China Electric Power University), Changping Beijing, 102206

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Journal article
Published: 20 August 2021 in IEEE Access
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Fuzzy best-worst method (BWM) has emerged as an efficient choice because of its comparison consistency to model the real-life and the consideration of fuzziness and uncertainties of decision-makers (DMs). However, how to extend the fuzzy BWM to group decision-making (GDM) environment has become an important topic because there are usually more than one decision-maker. For the GDM, decision makers may use different concepts to establish their individual assessment information due to the difference of cultural background and priori knowledge. To overcome this challenge, this article proposed a novel fuzzy best-worst multi-criteria group decision-making method to solve the GDM problem with multi-granular linguistic approach, which is an effective and promising technique to tackle this issue. In the proposed method, the selectable multi-granularity linguistic term sets (LTS) are firstly provided for experts to expressed their individual assessment information. Then, the improved fuzzy BWM is employed to calculate the weights of criteria with the form of fuzzy numbers. In current several studies using the BWM for group decision-making, only two unified best and worst criteria are given, which cannot reflect the evaluation of the best and worst criteria by different experts, resulting in the omission of information. Moreover, the difference between the best and worst criteria initially given and the experts’ ideas will cause the experts to be inaccurate in the comparison of each criterion. Therefore, in this article, in order not to omit too much information, each expert will determine the best and the worst criteria. Each expert’s assessment information which is based on his/her best and worst criteria is integrated into two vectors. What’s more, an improved input-based consistency measurement is proposed, which can provide the DMs with a clear guideline on the revision of the inconsistent judgement(s). Finally, two examples are given to illustrate the effectiveness and applicability of the proposed method.

ACS Style

Sen Guo; Ze Qi. A Fuzzy Best-Worst Multi-Criteria Group Decision-Making Method. IEEE Access 2021, PP, 1 -1.

AMA Style

Sen Guo, Ze Qi. A Fuzzy Best-Worst Multi-Criteria Group Decision-Making Method. IEEE Access. 2021; PP (99):1-1.

Chicago/Turabian Style

Sen Guo; Ze Qi. 2021. "A Fuzzy Best-Worst Multi-Criteria Group Decision-Making Method." IEEE Access PP, no. 99: 1-1.

Journal article
Published: 13 July 2021 in Mathematics
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The accurate prediction of electricity-heat-cooling-gas loads on the demand side in the integrated energy system (IES) can provide significant reference for multiple energy planning and stable operation of the IES. This paper combines the multi-task learning (MTL) method, the Bootstrap method, the improved Salp Swarm Algorithm (ISSA) and the multi-kernel extreme learning machine (MKELM) method to establish the uncertain interval prediction model of electricity-heat-cooling-gas loads. The ISSA introduces the dynamic inertia weight and chaotic local searching mechanism into the basic SSA to improve the searching speed and avoid falling into local optimum. The MKELM model is established by combining the RBF kernel function and the Poly kernel function to integrate the superior learning ability and generalization ability of the two functions. Based on the established model, weather, calendar information, social–economic factors, and historical load are selected as the input variables. Through empirical analysis and comparison discussion, we can obtain: (1) the prediction results of workday are better than those on holiday. (2) The Bootstrap-ISSA-MKELM based on the MTL method has superior performance than that based on the STL method. (3) Through comparing discussion, we discover the established uncertain interval prediction model has the superior performance in combined electricity-heat-cooling-gas loads prediction.

ACS Style

Haoran Zhao; Sen Guo. Uncertain Interval Forecasting for Combined Electricity-Heat-Cooling-Gas Loads in the Integrated Energy System Based on Multi-Task Learning and Multi-Kernel Extreme Learning Machine. Mathematics 2021, 9, 1645 .

AMA Style

Haoran Zhao, Sen Guo. Uncertain Interval Forecasting for Combined Electricity-Heat-Cooling-Gas Loads in the Integrated Energy System Based on Multi-Task Learning and Multi-Kernel Extreme Learning Machine. Mathematics. 2021; 9 (14):1645.

Chicago/Turabian Style

Haoran Zhao; Sen Guo. 2021. "Uncertain Interval Forecasting for Combined Electricity-Heat-Cooling-Gas Loads in the Integrated Energy System Based on Multi-Task Learning and Multi-Kernel Extreme Learning Machine." Mathematics 9, no. 14: 1645.

Conference paper
Published: 12 May 2021 in E3S Web of Conferences
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With the growth of residential electricity consumption and the development of power energy conservation, exploring the factors that affect residential electricity consumption is of great significance for promoting the sustainable development of the regional economy-power system. This paper examines the influencing factors of residential electricity consumption according to the data in 6 provinces in North China over 2008-2018, and two panels named urban panel and rural panel are constructed. Three conventional influencing factors are selected in this paper, namely, population (POP), per capita disposable income (DI) and per capita consumption expenditure (PCCE). Furthermore, considering that household characteristics have an impact on residential electricity consumption, this paper adds the number of household appliances (HA) and the per capita housing area (LS) into the factor set. Heterogeneous panel analysis techniques are applied to achieve the analysis, finding that household characteristics have significant impacts on electricity consumption of urban and rural residents, and the impact on electricity consumption of urban residents is greater than that on rural residents. Based on the empirical results, this paper puts forward several policy recommendations to effectively improve the residential electricity consumption and reduce the gap between urban and rural residential electricity consumption.

ACS Style

Mingliang Liang; Wenxuan Li; Jie Ji; Lili Liu; Shiying Zhang; Huiru Zhao; Sen Guo. Nexus between residential electricity consumption and household characteristics: heterogeneous urban and rural panel evidences from North China. E3S Web of Conferences 2021, 257, 02011 .

AMA Style

Mingliang Liang, Wenxuan Li, Jie Ji, Lili Liu, Shiying Zhang, Huiru Zhao, Sen Guo. Nexus between residential electricity consumption and household characteristics: heterogeneous urban and rural panel evidences from North China. E3S Web of Conferences. 2021; 257 ():02011.

Chicago/Turabian Style

Mingliang Liang; Wenxuan Li; Jie Ji; Lili Liu; Shiying Zhang; Huiru Zhao; Sen Guo. 2021. "Nexus between residential electricity consumption and household characteristics: heterogeneous urban and rural panel evidences from North China." E3S Web of Conferences 257, no. : 02011.

Conference paper
Published: 12 May 2021 in E3S Web of Conferences
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The new round of power system reform has strengthened the supervision of transmission and distribution links, and changed the profit model of power grid enterprises by verifying the transmission and distribution price. In this context, the research on the regulatory risk faced by power grid enterprises under the electricity price regulatory policy can provide tools and decision support for power grid enterprises to accurately grasp the regulatory risk and reduce the risk loss. Firstly, combined with the transmission and distribution price supervision process faced by power grid enterprises, the possible risks faced by power grid enterprises in price supervision are analyzed. Secondly, the quantitative measurement model of electricity price regulation of power grid enterprises is constructed by using system dynamics, and the effectiveness of the model is verified. Finally, the future regulatory period is simulated and the results are analyzed, and policy recommendations are put forward.

ACS Style

Huiru Zhao; Sitong Liu; Bingkang Li; Peipei You; Rengcun Fang; Sen Guo. Risk assessment of electricity price regulation for power grid enterprises based on system dynamics model. E3S Web of Conferences 2021, 257, 02021 .

AMA Style

Huiru Zhao, Sitong Liu, Bingkang Li, Peipei You, Rengcun Fang, Sen Guo. Risk assessment of electricity price regulation for power grid enterprises based on system dynamics model. E3S Web of Conferences. 2021; 257 ():02021.

Chicago/Turabian Style

Huiru Zhao; Sitong Liu; Bingkang Li; Peipei You; Rengcun Fang; Sen Guo. 2021. "Risk assessment of electricity price regulation for power grid enterprises based on system dynamics model." E3S Web of Conferences 257, no. : 02021.

Conference paper
Published: 12 May 2021 in E3S Web of Conferences
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The electricity transmission and distribution tariff policy of the second supervision cycle in China has formulated a much better electricity transmission and distribution tariff supervision system. In this context, the research on the risk related to electricity transmission and distribution tariff regulation faced by power grid enterprises is helpful for power regulatory agencies and business operators to identify and avoid risks in time and promote the sustainable development of electric power industry. Firstly, the risk evaluation criteria system is established. Secondly, a risk evaluation model based on the best and worst method (BWM) and cloud model for electricity transmission and distribution tariff regulation is proposed. Finally, the risk level of power transmission and distribution tariff regulation faced by four provincial power grid enterprises is evaluated. The validity and practicability of the proposed model in this paper are proved by the empirical analysis.

ACS Style

Ze Qi; Peipei You; Rengcun Fang; Zhao Xu; Yuxin Zou; Sen Guo. Risk assessment of electricity transmission and distribution tariff regulation for power grid enterprises based on best-worst method and cloud model. E3S Web of Conferences 2021, 257, 01005 .

AMA Style

Ze Qi, Peipei You, Rengcun Fang, Zhao Xu, Yuxin Zou, Sen Guo. Risk assessment of electricity transmission and distribution tariff regulation for power grid enterprises based on best-worst method and cloud model. E3S Web of Conferences. 2021; 257 ():01005.

Chicago/Turabian Style

Ze Qi; Peipei You; Rengcun Fang; Zhao Xu; Yuxin Zou; Sen Guo. 2021. "Risk assessment of electricity transmission and distribution tariff regulation for power grid enterprises based on best-worst method and cloud model." E3S Web of Conferences 257, no. : 01005.

Journal article
Published: 28 April 2021 in Mathematics
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In China, a new-round marketization reform of electricity industry is in progress, and the electricity transmission and distribution tariff reform is the core and important task. Currently, the electricity transmission and distribution tariff regulation has gone to the second round in China, and the electric power grid enterprises are facing a closed-loop regulatory system and an increasingly strict regulatory environment. Therefore, it is urgent to evaluate the risk of electric power grid enterprise that is related to electricity transmission and distribution tariff regulation, which can aid the electricity regulators and electric power grid enterprise operators to manage risk and promote the sustainable development of electric power industry. In this paper, a hybrid novel multi-criteria decision making (MCDM) method combining the fuzzy Best-Worst method (FBWM) and improved fuzzy comprehensive evaluation method based on a vague set is proposed for the risk evaluation of electric power grid enterprise related to electricity transmission and distribution tariff regulation. The risk evaluation index system is built. Subsequently, the FBWM is utilized to determine the optimal weights of electric power grid enterprise risk criteria, and the improved fuzzy comprehensive evaluation method that is based on vague set is employed to rank the comprehensive risk grade of electric power grid enterprise related to electricity transmission and distribution tariff regulation. The risk of a province-level electric power grid enterprise that is located in Northern China is empirically evaluated using the proposed MCDM method, and the result indicates that the overall risk of this province-level electric power grid enterprise belongs to ‘High’ grade, but it is very close to ‘Very High’ grade. The results indicate that the proposed hybrid novel MCDM method in this paper is effective and practical. Meanwhile, it provides a new view for the risk evaluation of electric power grid enterprise that is related to electricity transmission and distribution tariff regulation.

ACS Style

Wenjin Li; Bingkang Li; Rengcun Fang; Peipei You; Yuxin Zou; Zhao Xu; Sen Guo. Risk Evaluation of Electric Power Grid Enterprise Related to Electricity Transmission and Distribution Tariff Regulation Employing a Hybrid MCDM Model. Mathematics 2021, 9, 989 .

AMA Style

Wenjin Li, Bingkang Li, Rengcun Fang, Peipei You, Yuxin Zou, Zhao Xu, Sen Guo. Risk Evaluation of Electric Power Grid Enterprise Related to Electricity Transmission and Distribution Tariff Regulation Employing a Hybrid MCDM Model. Mathematics. 2021; 9 (9):989.

Chicago/Turabian Style

Wenjin Li; Bingkang Li; Rengcun Fang; Peipei You; Yuxin Zou; Zhao Xu; Sen Guo. 2021. "Risk Evaluation of Electric Power Grid Enterprise Related to Electricity Transmission and Distribution Tariff Regulation Employing a Hybrid MCDM Model." Mathematics 9, no. 9: 989.

Journal article
Published: 25 February 2021 in Mathematics
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Socio-economic development is undergoing changes in China, such as the recently proposed carbon peak and carbon neutral targets, new infrastructure development strategy and the Coronavirus disease 2019 (COVID-19) pandemic. Meanwhile, the new-round marketization reform of the electricity industry has been ongoing in China since 2015. Therefore, it is urgent to evaluate the risk of electric power grid investment in China under new socio-economic development situation, which can help the investors manage risk and reduce risk loss. In this paper, a hybrid novel multi-criteria decision making (MCDM) method combining the latest group MCDM method, namely, Bayesian best–worst method (BBWM) and improved matter-element extension model (IMEEM) is proposed for risk evaluation of electric power grid investment in China under new socio-economic development situation. The BBWM is used for the weights’ determination of electric power grid investment risk criteria, and the IMEEM is employed to rank risk grade of electric power grid investment. The risk evaluation index system of electric power grid investment is built, including economic, social, environmental, technical and marketable risks. The risk of electric power grid investment under new socio-economic development situation in Inner Mongolia Autonomous Region of China is empirically evaluated by using the proposed MCDM method, and the results indicate that it belongs to “Medium” grade, but closer to “High” grade. The main contributions of this paper include: (1) it proposes a hybrid novel MCDM method combining the BBWM and IMEEM for risk evaluation of electric power grid investment; and (2) it provides a new view for risk evaluation of electric power grid investment including economic, social, environmental, technical and marketable risks. The proposed hybrid novel MCDM method for the risk evaluation of electric power grid investment is effective and practical.

ACS Style

Yana Duan; Yang Sun; Yu Zhang; Xiaoqi Fan; Qinghuan Dong; Sen Guo. Risk Evaluation of Electric Power Grid Investment in China Employing a Hybrid Novel MCDM Method. Mathematics 2021, 9, 473 .

AMA Style

Yana Duan, Yang Sun, Yu Zhang, Xiaoqi Fan, Qinghuan Dong, Sen Guo. Risk Evaluation of Electric Power Grid Investment in China Employing a Hybrid Novel MCDM Method. Mathematics. 2021; 9 (5):473.

Chicago/Turabian Style

Yana Duan; Yang Sun; Yu Zhang; Xiaoqi Fan; Qinghuan Dong; Sen Guo. 2021. "Risk Evaluation of Electric Power Grid Investment in China Employing a Hybrid Novel MCDM Method." Mathematics 9, no. 5: 473.

Journal article
Published: 10 November 2020 in Energies
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As a component of China’s strategic emerging industries, green lighting is an important industry supporting the high-quality and high-efficiency development of China’s economy, and is also an important way to achieve energy conservation and emission reduction. At present, China has basically established a policy framework to promote the development of green lighting industry, but there is no empirical evidence on the performance of existing policies on energy conservation and emission reduction. Based on the development status of China’s green lighting industry, this paper sorts out the milestones of China’s green lighting industry policy and the current status of the framework of the existing green lighting industry development policies, constructs a policy performance evaluation model for China’s green lighting industry based on the difference-in-difference (DID) model, and evaluates the implementation effects of green lighting industry policies in China from the perspective of energy conservation and emission reduction. The empirical results of China’s 85 cities show that the implementation of green lighting industry policies has significantly promoted regional energy conservation and emission reduction. Finally, this paper puts forward targeted policy recommendations to provide policy support for the transformation of China’s green lighting industry from “large” to “strong”.

ACS Style

Kan Wang; Li Lei; Shuai Qiu; Sen Guo. Policy Performance of Green Lighting Industry in China: A DID Analysis from the Perspective of Energy Conservation and Emission Reduction. Energies 2020, 13, 5855 .

AMA Style

Kan Wang, Li Lei, Shuai Qiu, Sen Guo. Policy Performance of Green Lighting Industry in China: A DID Analysis from the Perspective of Energy Conservation and Emission Reduction. Energies. 2020; 13 (22):5855.

Chicago/Turabian Style

Kan Wang; Li Lei; Shuai Qiu; Sen Guo. 2020. "Policy Performance of Green Lighting Industry in China: A DID Analysis from the Perspective of Energy Conservation and Emission Reduction." Energies 13, no. 22: 5855.

Journal article
Published: 06 March 2020 in Sustainability
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Electricity retail marketization reform is in progress in China, and many electricity retail companies (ERC) have been founded. The comprehensive evaluation of business risk for ERC can help effectively manage business risk and reduce risk loss, which is vital for its healthy and sustainable development. In this paper, a new hybrid multi-criteria decision making (MCDM) method integrating the Bayesian best-worst method (BBWM) and improved matter-element extension model (IMEEM) is proposed for business risk evaluation for an ERC. The latest group MCDM method, namely the BBWM is employed to determine risk criteria weights, and the IMEEM is used to rank the business risk of ERC. The evaluation index system is built including three aspects of economic operation risk, marketable risk and political risk. The business risk of ERC in China is evaluated by using the proposed MCDM method, and the result shows the current business risk belongs to ‘High’ grade and closer to ‘Very High’ grade more. The proposed MCDM method for business risk evaluation of ERC is effective and practical, which can provide references for risk management and sustainable development of ERC.

ACS Style

Sen Guo; Wenyue Zhang; Xiao Gao. Business Risk Evaluation of Electricity Retail Company in China Using a Hybrid MCDM Method. Sustainability 2020, 12, 2040 .

AMA Style

Sen Guo, Wenyue Zhang, Xiao Gao. Business Risk Evaluation of Electricity Retail Company in China Using a Hybrid MCDM Method. Sustainability. 2020; 12 (5):2040.

Chicago/Turabian Style

Sen Guo; Wenyue Zhang; Xiao Gao. 2020. "Business Risk Evaluation of Electricity Retail Company in China Using a Hybrid MCDM Method." Sustainability 12, no. 5: 2040.

Journal article
Published: 19 February 2020 in Energies
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Electrochemical energy storage (EES) is a promising kind of energy storage and has developed rapidly in recent years in many countries. EES planning is an important topic that can impact the earnings of EES investors and sustainable industrial development. Current studies only consider the profit or cost of the EES planning program, without considering other economic criteria such as payback period and return on investment (ROI), which are also important for determining an optimal EES planning program. In this paper, a new hybrid multi-criteria decision-making (MCDM) method integrating the Bayesian best-worst method (BBWM), the entropy weighting approach, and grey cumulative prospect theory is proposed for the optimal EES planning program selection with the consideration of multiple economic criteria. The BBWM and entropy weighting approach are jointly employed for determining the weightings of criteria, and the grey cumulative prospect theory was utilized for the performance rankings of different EES planning programs. Five EES planning programs were selected for empirical analysis, including 9MW PbC battery EES, 2MW LiFePO lithium ion battery EES, 3MW LiFePO lithium ion battery EES, 2MW vanadium redox flow battery EES, and 3MW vanadium redox flow battery EES. The empirical results indicate the 2MW LiFePO lithium ion battery EES is the optimal one. The sensitivity analysis related to different risk preferences of decision-makers also shows the 2MW LiFePO lithium ion battery EES is always the optimal EES planning program. The proposed MCDM method for the optimal EES planning program selection in this paper is effective and robust, and can provide certain references for EES investors and decision-makers.

ACS Style

Nan Li; Haining Zhang; Xiangcheng Zhang; Xue Ma; And Sen Guo. How to Select the Optimal Electrochemical Energy Storage Planning Program? A Hybrid MCDM Method. Energies 2020, 13, 931 .

AMA Style

Nan Li, Haining Zhang, Xiangcheng Zhang, Xue Ma, And Sen Guo. How to Select the Optimal Electrochemical Energy Storage Planning Program? A Hybrid MCDM Method. Energies. 2020; 13 (4):931.

Chicago/Turabian Style

Nan Li; Haining Zhang; Xiangcheng Zhang; Xue Ma; And Sen Guo. 2020. "How to Select the Optimal Electrochemical Energy Storage Planning Program? A Hybrid MCDM Method." Energies 13, no. 4: 931.

Journal article
Published: 15 August 2019 in International Journal of Environmental Research and Public Health
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With the rapid development of China’s economy, the environmental problems are becoming increasingly prominent, especially the PM2.5 (particulate matter with diameter smaller than 2.5 μm) concentrations that have exerted adverse influences on human health. Considering the fact that PM2.5 concentrations are mainly caused by anthropogenic activities, this paper selected economic growth, economic structure, urbanization, and the number of civil vehicles as the primary factors and then explored the nexus between those variables and PM2.5 concentrations by employing a panel data model for 31 Chinese provinces. The estimated model showed that: (1) the coefficients of the variables for provinces located in North, Central, and East China were larger than that of other provinces; (2) GDP per capita made the largest contribution to PM2.5 concentrations, while the number of civil vehicles made the least contribution; and (3) the higher the development level of a factor, the greater the contribution it makes to PM2.5 concentrations. It was also found that a bi-directional Granger causal nexus exists between PM2.5 concentrations and economic progress as well as between PM2.5 concentrations and the urbanization process for all provinces. Policy recommendations were finally obtained through empirical discussions, which include that provincial governments should adjust the economic and industrial development patterns, restrict immigration to intensive urban areas, decrease the successful proportion of vehicle licenses, and promote electric vehicles as a substitute to petrol vehicles.

ACS Style

Haoran Zhao; Sen Guo; Huiru Zhao. Quantifying the Impacts of Economic Progress, Economic Structure, Urbanization Process, and Number of Vehicles on PM2.5 Concentration: A Provincial Panel Data Model Analysis of China. International Journal of Environmental Research and Public Health 2019, 16, 2926 .

AMA Style

Haoran Zhao, Sen Guo, Huiru Zhao. Quantifying the Impacts of Economic Progress, Economic Structure, Urbanization Process, and Number of Vehicles on PM2.5 Concentration: A Provincial Panel Data Model Analysis of China. International Journal of Environmental Research and Public Health. 2019; 16 (16):2926.

Chicago/Turabian Style

Haoran Zhao; Sen Guo; Huiru Zhao. 2019. "Quantifying the Impacts of Economic Progress, Economic Structure, Urbanization Process, and Number of Vehicles on PM2.5 Concentration: A Provincial Panel Data Model Analysis of China." International Journal of Environmental Research and Public Health 16, no. 16: 2926.

Journal article
Published: 25 May 2019 in Sustainability
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Since 2013, a series of air pollution prevention and control (APPC) measures have been promulgated in China for reducing the level of air pollution, which can affect regional short-term electricity power demand by changing the behavior of power users electricity consumption. This paper analyzes the policy system of the APPC measures and its impact on regional short-term electricity demand, and determines the regional short-term load impact factors considering the impact of APPC measures. On this basis, this paper proposes a similar day selection method based on the best and worst method and grey relational analysis (BWM-GRA) in order to construct the training sample set, which considers the difference in the influence degree of characteristic indicators on daily power load. Further, a short-term load forecasting method based on least squares support vector machine (LSSVM) optimized by salp swarm algorithm (SSA) is developed. By forecasting the load of a city affected by air pollution in Northern China, and comparing the results with several selected models, it reveals that the impact of APPC measures on regional short-term load is significant. Moreover, by considering the influence of APPC measures and avoiding the subjectivity of model parameter settings, the proposed load forecasting model can improve the accuracy of, and provide an effective tool for short-term load forecasting. Finally, some limitations of this paper are discussed.

ACS Style

Xueliang Li; Bingkang Li; Long Zhao; Huiru Zhao; Wanlei Xue; Sen Guo. Forecasting the Short-Term Electric Load Considering the Influence of Air Pollution Prevention and Control Policy via a Hybrid Model. Sustainability 2019, 11, 2983 .

AMA Style

Xueliang Li, Bingkang Li, Long Zhao, Huiru Zhao, Wanlei Xue, Sen Guo. Forecasting the Short-Term Electric Load Considering the Influence of Air Pollution Prevention and Control Policy via a Hybrid Model. Sustainability. 2019; 11 (10):2983.

Chicago/Turabian Style

Xueliang Li; Bingkang Li; Long Zhao; Huiru Zhao; Wanlei Xue; Sen Guo. 2019. "Forecasting the Short-Term Electric Load Considering the Influence of Air Pollution Prevention and Control Policy via a Hybrid Model." Sustainability 11, no. 10: 2983.

Remediation treatment
Published: 04 April 2019 in Environmental Progress & Sustainable Energy
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Urban planning and energy consumption management gradually play an increasingly significant role in carbon dioxide (CO2) emissions reduction. However, the current studies related to the nexus among them are insufficient, which need to be explored. This article focuses on quantifying the nexus among CO2 emissions, economic development, energy consumption, and urbanization according to data collected from top six provinces (Shanxi, Shaanxi, Shandong, Hebei, Jiangsu, and Inner Mongolia) of CO2 emissions in China between 1997 and 2015 using multi‐variate panel data model (PDM). According to the coefficients in PDM, the energy consumption of Shanxi, Inner Mongolia, Hebei, and Shaanxi make the greatest contribution to CO2 emissions and the economic development of Jiangsu and Shandong are deemed as the greatest contributor to CO2 emissions. The Granger causality results illustrate a bi‐directional causality exists between economic progress and CO2 emissions and between energy consumption and CO2 emissions for six provinces. Finally, the pathways to handle with the contradictions between economic development and CO2 mitigation of top six provinces are proposed, namely decreasing fossil fuels based energy consumption, giving impetus to renewable energy development, exploring a new evaluation system to judge low carbon economy progress, and increasing investment on equipments to improve energy efficiency.

ACS Style

Haoran Zhao; Sen Guo; Huiru Zhao. A panel co‐integration analysis for economic development, energy consumption, urbanization, and carbon dioxide emissions in China's six provinces. Environmental Progress & Sustainable Energy 2019, 38, 1 .

AMA Style

Haoran Zhao, Sen Guo, Huiru Zhao. A panel co‐integration analysis for economic development, energy consumption, urbanization, and carbon dioxide emissions in China's six provinces. Environmental Progress & Sustainable Energy. 2019; 38 (6):1.

Chicago/Turabian Style

Haoran Zhao; Sen Guo; Huiru Zhao. 2019. "A panel co‐integration analysis for economic development, energy consumption, urbanization, and carbon dioxide emissions in China's six provinces." Environmental Progress & Sustainable Energy 38, no. 6: 1.

Journal article
Published: 28 November 2018 in Energy
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Under the context of low-carbon economy development, the utilization of renewable energy is deemed as an effective way for energy conservation and emission reduction. Considering about the intermittent and volatile characteristics of renewable energy, the selection of the optimal energy storage system (ESS) among various kinds of alternatives is of critical significance for giving impetus to the development of renewable energy. Therefore, it is essential to develop a comprehensive assessment technique for prioritizing various battery energy storage systems and selecting the optimal one. This paper proposed an integrated fuzzy-MCDM (multi-criteria decision making) model combining Fuzzy-Delphi approach, the Best-Worst method (BWM), and fuzzy-cumulative prospect theory (CPT) for the comprehensive assessment of battery energy storage systems. The comprehensive assessment index system consists of 15 sub-criteria from the perspectives of technology, economy, environment, performance, and sociality based on Fuzzy-Delphi method. The optimal weights are determined by the BWM based on experts’ judgments which emphasized the importance of technology and environment impacts. Fuzzy theory is employed to convert interval values and crisp values to triangular fuzzy numbers (TFNs) to maximize the use of objective data information, and then the CPT model is utilized to prioritize the rankings of various alternatives considering risk preferences of decision makers and investors. The empirical result shows that the Li-ion battery is the priority selection for micro-grid demonstration projects, followed by NaS battery and NiMH battery. Sensitivity analysis discusses the influences of risk preferences on alternatives rankings. Results demonstrate that even if decision makers and investors have various risk preferences, considering about the technological, environmental, economic, social, and performance criteria, the Li-ion battery is still the optimal, followed by NaS battery.

ACS Style

Haoran Zhao; Sen Guo; Huiru Zhao. Comprehensive assessment for battery energy storage systems based on fuzzy-MCDM considering risk preferences. Energy 2018, 168, 450 -461.

AMA Style

Haoran Zhao, Sen Guo, Huiru Zhao. Comprehensive assessment for battery energy storage systems based on fuzzy-MCDM considering risk preferences. Energy. 2018; 168 ():450-461.

Chicago/Turabian Style

Haoran Zhao; Sen Guo; Huiru Zhao. 2018. "Comprehensive assessment for battery energy storage systems based on fuzzy-MCDM considering risk preferences." Energy 168, no. : 450-461.

Journal article
Published: 20 October 2018 in Energies
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With the increasing development of renewable resources-based electricity generation and the construction of wind-photovoltaic-energy storage combination exemplary projects, the intermittent and fluctuating nature of renewable resources exert great challenges for the power grid to supply electricity reliably and stably. An energy storage system (ESS) is deemed to be the most valid solution to deal with these challenges. Considering the various types of ESSs, it is necessary to develop a comprehensive assessment framework for selecting appropriate energy storage techniques in establishing exemplary projects combining renewable resources-based electricity generation and an ESS. This paper proposes a multi-criteria decision making (MCDM) model combining a fuzzy-Delphi approach to establish the comprehensive assessment indicator system, the entropy weight determination method, and the best-worst method (BWM) to calculate weights of all sub-criteria, and a Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) comprehensive evaluation model to choose the optimal battery ESS. In accordance with the comprehensive evaluation results, the Li-ion battery is the optimal battery ESS to apply to wind-photovoltaic-energy storage combination exemplary projects. Based on the discussion on the comprehensive evaluation results, policy implications are suggested to improve the applicability of battery ESSs and provide some references for decision makers in related fields.

ACS Style

Haoran Zhao; Sen Guo; Huiru Zhao. Comprehensive Performance Assessment on Various Battery Energy Storage Systems. Energies 2018, 11, 2841 .

AMA Style

Haoran Zhao, Sen Guo, Huiru Zhao. Comprehensive Performance Assessment on Various Battery Energy Storage Systems. Energies. 2018; 11 (10):2841.

Chicago/Turabian Style

Haoran Zhao; Sen Guo; Huiru Zhao. 2018. "Comprehensive Performance Assessment on Various Battery Energy Storage Systems." Energies 11, no. 10: 2841.

Journal article
Published: 11 October 2018 in Energy
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The current society is confronting with the crisis of fossil energy resources scarcity and environment deterioration caused by the accelerating development of economy in China. Since the improvement of energy efficiency has been deemed as the most effective way to decrease energy consumption and pollutant emissions, energy efficiency evaluation has been attached great importance in policy formulating. This investigation employed three-stage data envelopment analysis model to evaluate China’s provincial energy efficiency during 2008-2016 excluding the impacts of exterior environmental factors. The empirical results illustrate that the provincial energy efficiencies in China are significantly affected by economic and energy consumption structure, urbanization process, and technical innovation level. Generally, the exterior environmental values and statistical noises result in the underestimation of China’s provincial energy efficiencies. The exclusion of exterior environmental factors has provincial-specific impacts. Additionally, energy efficiency can be disintegrated into scale efficiency and pure energy efficiency, which is mainly dominated by scale efficiency. Based on empirical results, provincial specific strategies can be provided to enhance energy efficiency, such as taking the influences of exterior environmental factors into consideration when formulating policies, optimizing the exterior environment to improve provincial energy efficiency, and pertinently improving scale efficiency or pure energy efficiency according to their categorizations.

ACS Style

Haoran Zhao; Sen Guo; Huiru Zhao. Provincial energy efficiency of China quantified by three-stage data envelopment analysis. Energy 2018, 166, 96 -107.

AMA Style

Haoran Zhao, Sen Guo, Huiru Zhao. Provincial energy efficiency of China quantified by three-stage data envelopment analysis. Energy. 2018; 166 ():96-107.

Chicago/Turabian Style

Haoran Zhao; Sen Guo; Huiru Zhao. 2018. "Provincial energy efficiency of China quantified by three-stage data envelopment analysis." Energy 166, no. : 96-107.

Journal article
Published: 05 September 2018 in Sustainability
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With the implementation of new round electricity system reform in China, the provincial electricity grid enterprises (EGEs) of China should focus on improving their operational efficiency to adapt to the increasingly fierce market competition and satisfy the requirements of the electricity industry reform. Therefore, it is essential to conduct operational efficiency evaluation on provincial EGEs. While considering the influences of exterior environmental variables on the operational efficiency of provincial EGEs, a three-stage data envelopment analysis (DEA) methodology is first utilized to accurately assess the real operational efficiency of provincial EGEs excluding the exterior environmental values and statistical noise. The three-stage DEA model takes the amount of employees, the fixed assets investment, the 110 kV and below distribution line length, and the 110 kV and below transformer capacity as input variables and the electricity sales amount, the amount of consumers, and the line loss rate as output variables. The regression results of the stochastic frontier analysis model indicate that the operational efficiencies of provincial EGEs are significantly affected by exterior environmental variables. Results of the three-stage DEA model imply that the exterior environmental values and statistical noise result in the overestimation of operational efficiency of provincial EGEs, and the exclusion of exterior environmental values and statistical noise has provincial-EGE-specific influences. Furthermore, 26 provincial EGEs are divided into four categories to better understand the differences of operational efficiencies before and after the exclusion of exterior environmental values and statistical noise.

ACS Style

Haoran Zhao; Huiru Zhao; Sen Guo. Operational Efficiency of Chinese Provincial Electricity Grid Enterprises: An Evaluation Employing a Three-Stage Data Envelopment Analysis (DEA) Model. Sustainability 2018, 10, 3168 .

AMA Style

Haoran Zhao, Huiru Zhao, Sen Guo. Operational Efficiency of Chinese Provincial Electricity Grid Enterprises: An Evaluation Employing a Three-Stage Data Envelopment Analysis (DEA) Model. Sustainability. 2018; 10 (9):3168.

Chicago/Turabian Style

Haoran Zhao; Huiru Zhao; Sen Guo. 2018. "Operational Efficiency of Chinese Provincial Electricity Grid Enterprises: An Evaluation Employing a Three-Stage Data Envelopment Analysis (DEA) Model." Sustainability 10, no. 9: 3168.

Journal article
Published: 23 July 2018 in Sustainability
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The speeding-up of economic development and industrialization processes in China have brought about serious atmospheric pollution issues, especially in terms of particulate matter harmful to health. However, impact mechanisms of socio-economic forces on PM2.5 (the particle matter with diameter less than 2.5 μm) have rarely been further investigated. This paper selected GDP (gross domestic product) per capita, energy consumption, urbanization process, industrialization structure, and the amount of possession of civil vehicles as the significant factors, and researched the relationship between these factors and PM2.5 concentrations from 1998 to 2016, employing auto-regressive distributed lag (ARDL) methodology and environmental Kuznets curve (EKC) theory. Empirical results illustrated that a long-term equilibrium nexus exists among these variables. Granger causality results indicate that bi-directional causality exist between PM2.5 concentrations and GDP per capita, the squared component of GDP per capita, energy consumption and urbanization process. An inverse U-shape nexus exists between PM2.5 concentrations and GDP per capita. When the real GDP per capita reaches 5942.44 dollars, PM2.5 concentrations achieve the peak. Results indicate that Chinese governments should explore a novel pathway to resolve the close relationship between socio-economic factors and PM2.5, such as accelerating the adjustment of economic development mode, converting the critical industrial development driving forces, and adjusting the economic structure.

ACS Style

Haoran Zhao; Sen Guo; Huiru Zhao. Characterizing the Influences of Economic Development, Energy Consumption, Urbanization, Industrialization, and Vehicles Amount on PM2.5 Concentrations of China. Sustainability 2018, 10, 2574 .

AMA Style

Haoran Zhao, Sen Guo, Huiru Zhao. Characterizing the Influences of Economic Development, Energy Consumption, Urbanization, Industrialization, and Vehicles Amount on PM2.5 Concentrations of China. Sustainability. 2018; 10 (7):2574.

Chicago/Turabian Style

Haoran Zhao; Sen Guo; Huiru Zhao. 2018. "Characterizing the Influences of Economic Development, Energy Consumption, Urbanization, Industrialization, and Vehicles Amount on PM2.5 Concentrations of China." Sustainability 10, no. 7: 2574.

Journal article
Published: 13 July 2018 in Energies
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As useful supplements and effective support for large-scale electric power networks, micro-grid systems are the development tendency of future electric power systems. The planning performance of a micro-grid not only affects its security, reliability and economy, but also has a profound influence on the stable operation of large-scale electric power networks with the increasing penetration of micro-grids. Hence, studies related to micro-grid planning program evaluation are of great significance. This paper established a novel multi-criteria decision making (MCDM) model combining the best-worst method (BWM), the entropy weighting approach, and grey cumulative prospect theory for optimum selection of micro-grid planning programs. Firstly, an evaluation index system containing 18 sub-criteria was built from the perspectives of economy, electricity supply reliability and environmental protection. Secondly, the weights of sub-criteria were calculated integrating the subjective weights judged by the BWM and the objective weights computed by the entropy weighting method. Then, the cumulative prospect theory (CPT) combined with grey theory was employed to select the optimal micro-grid planning program. The empirical result indicates that the program with 100 kWp photovoltaic power generation unit, 200 kW wind power generation unit and 600 kWh NaS battery energy storage system is the optimal micro-grid planning program. To verify the robustness of obtained result, a sensitivity analysis related to values change of parameters under different risk preferences was conducted, and the result indicates that the selected optimal micro-grid planning program will not be influenced by various risk preferences of decision makers (DMs) and investors. The novel MCDM proposed in this paper is applicable and feasible in the micro-grid planning programs evaluation and selection.

ACS Style

Haoran Zhao; Sen Guo; Huiru Zhao. Selecting the Optimal Micro-Grid Planning Program Using a Novel Multi-Criteria Decision Making Model Based on Grey Cumulative Prospect Theory. Energies 2018, 11, 1840 .

AMA Style

Haoran Zhao, Sen Guo, Huiru Zhao. Selecting the Optimal Micro-Grid Planning Program Using a Novel Multi-Criteria Decision Making Model Based on Grey Cumulative Prospect Theory. Energies. 2018; 11 (7):1840.

Chicago/Turabian Style

Haoran Zhao; Sen Guo; Huiru Zhao. 2018. "Selecting the Optimal Micro-Grid Planning Program Using a Novel Multi-Criteria Decision Making Model Based on Grey Cumulative Prospect Theory." Energies 11, no. 7: 1840.

Journal article
Published: 22 June 2018 in Sustainability
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Under the new round reform of electricity market in China, a large amount of electricity sales companies has emerged in some provinces, and the reform of transmission and distribution tariffs is also in progress. Electricity grid corporations are required to update their operational strategies and improve comprehensive performance to adapt to the fierce competition in the electricity market. Considering this, a novel MCDM (multi-criteria decision making) model integrating Fuzzy-Delphi, the best-worst method (BWM), the entropy weight calculation approach, and the VIKOR method is established in this investigation to assess the comprehensive performances of five selected provincial electricity grid corporations. The comprehensive performance assessment indicator system is constructed in accordance with Fuzzy-Delphi approach, composed of 21 significant sub-criteria from the aspects of profitability capacity, development capacity, safety production capacity, electricity supply reliability, outstanding service provision, energy conservation, and environmental protection. The sub-criteria weights are computed by combining subjective weights determined by BWM and objective weights computed by the entropy weight calculation approach. The comprehensive performance evaluation model is established based on VIKOR. As the electricity grid corporation A is superior in profitability capacity (especially in electricity sales amount) and safety production capacity criterion, it is superior over other four electricity grid corporations. The established novel MCDM is practical and rational, which is applicable for electricity grid corporations’ comprehensive performance evaluation.

ACS Style

Haoran Zhao; Huiru Zhao; Sen Guo. Comprehensive Performance Evaluation of Electricity Grid Corporations Employing a Novel MCDM Model. Sustainability 2018, 10, 2130 .

AMA Style

Haoran Zhao, Huiru Zhao, Sen Guo. Comprehensive Performance Evaluation of Electricity Grid Corporations Employing a Novel MCDM Model. Sustainability. 2018; 10 (7):2130.

Chicago/Turabian Style

Haoran Zhao; Huiru Zhao; Sen Guo. 2018. "Comprehensive Performance Evaluation of Electricity Grid Corporations Employing a Novel MCDM Model." Sustainability 10, no. 7: 2130.