China’s electricity transmission and distribution tariff mechanism based on sustainable development

He, Yongxiu; Wang, Bing; Li, Dacheng; Du, Min; Huang, Kangren; Xia, Tian

doi:10.1016/j.ijepes.2014.08.009

Cited by 19 publications

(8 citation statements)

References 23 publications

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“…6: Calculate the Forget gate, using formula (8). 7: Calculate the Input gate, using formula (9,10,11). 8: Calculate the Output gate, using formula (12,13,14) The rating is expressed as…”

Section: Preprocessing Strategy Of Hierarchical Decision-making Based On Task Grading (Hdtg) In Ec-iot Based Smart Gridsmentioning

confidence: 99%

“…On the basis of statistics on the electricity consumptions of the whole society, the electricity consumptions vary greatly among different industries, especially between the primary industry and heavy industry. However, the present power systems cannot be deployed in real time to satisfy consumer's electricity demands [9], [10]. 3) With the emergence of an increasing number of new intelligent distributed power terminals, it is necessary to achieve the plug-and-play and interoperability among devices.…”

Section: Introductionmentioning

confidence: 99%

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Internet of Things Based Smart Grids Supported by Intelligent Edge Computing

et al. 2019

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In this paper, an edge computing system for IoT-based (Internet of Things) smart grids is proposed to overcome the drawbacks in the current cloud computing paradigm in power systems, where many problems have yet to be addressed such as fully realizing the requirements of high bandwidth with low latency. The new system mainly introduces edge computing in the traditional cloud-based power system and establishes a new hardware and software architecture. Therefore, a considerable amount of data generated in the electrical grid will be analyzed, processed, and stored at the edge of the network. Aided with edge computing paradigm, the IoT-based smart grids will realize the connection and management of substantial terminals, provide the real-time analysis and processing of massive data, and foster the digitalization of smart grids. In addition, we propose a privacy protection strategy via edge computing, data prediction strategy, and preprocessing strategy of hierarchical decision-making based on task grading (HDTG) for the IoT-based smart girds. The effectiveness of our proposed approaches has been demonstrated via the numerical simulations.INDEX TERMS Edge computing, IoT-based smart grids, data prediction, artificial intelligence, data privacy protection, cloud computing.

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“…6: Calculate the Forget gate, using formula (8). 7: Calculate the Input gate, using formula (9,10,11). 8: Calculate the Output gate, using formula (12,13,14) The rating is expressed as…”

Section: Preprocessing Strategy Of Hierarchical Decision-making Based On Task Grading (Hdtg) In Ec-iot Based Smart Gridsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Internet of Things Based Smart Grids Supported by Intelligent Edge Computing

et al. 2019

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“…The size of transmission and distribution tariff is mainly determined by grid assets and transmission and distribution costs. Therefore, grid investment and transmission and distribution tariff affect each other (He et al,2015). Transmission and distribution tariff determine the revenue of grid companies, affect the financial situation of grid companies, and affect the ability of grid companies to invest in the future (Wang et al,2019).…”

Section: Introductionmentioning

confidence: 99%

The Dynamic Input-Output Model of Distribution Network Upgrading Project Under the Background of Electric Internet of Things

Yan¹,

Li²,

et al. 2020

E3S Web Conf.

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China is promoting the construction of electric internet of things, and a large part of the fixed asset investment in the power grid is the investment in the upgrading of the distribution network. The economic benefits of investment are related to the sustainable development of power grid companies. At present, the Chinese government is reforming transmission and distribution tariff, and the economic benefits of power grid infrastructure investment are facing greater uncertainty. This paper studies the life cycle cost of the distribution network upgrading project from construction to decommissioning and the electricity revenue for the entire operation period. The dynamic input-output model of the distribution network upgrading project is established under the background of electric internet of things. An empirical analysis is conducted in combination with the case study. Through load forecasting and cost calculation, the input and output indicators of the project are obtained, which verifies the validity and accuracy of the model.

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“…In 2002, to improve the operational efficiency of electricity industry and to break the absolute monopoly of State Power Corporation (SPC), the central government of China issued No.5 Document to disclose the prolusion of the first round reform for electricity industry [1][2][3][4]. However, as the policies are not market-oriented, unfair competition constantly emerged and pricing mechanisms became distorted, which was not coordinated with the speed-up development of the society and economy [5][6][7]. Aiming at solving the above mentioned problems, a new round of electricity industry reform was started by conducting the 'No.9 Government Document' in 2015 [8].…”

Section: Introductionmentioning

confidence: 99%

Operational Efficiency of Chinese Provincial Electricity Grid Enterprises: An Evaluation Employing a Three-Stage Data Envelopment Analysis (DEA) Model

Zhao

Guo

2018

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.

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China’s electricity transmission and distribution tariff mechanism based on sustainable development

Cited by 19 publications

References 23 publications

Internet of Things Based Smart Grids Supported by Intelligent Edge Computing

Internet of Things Based Smart Grids Supported by Intelligent Edge Computing

The Dynamic Input-Output Model of Distribution Network Upgrading Project Under the Background of Electric Internet of Things

Operational Efficiency of Chinese Provincial Electricity Grid Enterprises: An Evaluation Employing a Three-Stage Data Envelopment Analysis (DEA) Model

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