Risk Evaluation of Electric Power Grid Enterprise Related to Electricity Transmission and Distribution Tariff Regulation Employing a Hybrid MCDM Model

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.

Download Full-text

Risk Evaluation of Electric Power Grid Investment in China Employing a Hybrid Novel MCDM Method

Mathematics ◽

10.3390/math9050473 ◽

2021 ◽

Vol 9 (5) ◽

pp. 473

Author(s):

Yana Duan ◽

Yang Sun ◽

Yu Zhang ◽

Xiaoqi Fan ◽

Qinghuan Dong ◽

...

Keyword(s):

Economic Development ◽

Electric Power ◽

Risk Evaluation ◽

Power Grid ◽

Infrastructure Development ◽

Electric Power Grid ◽

Socio Economic Development ◽

Mcdm Method ◽

Social Environmental ◽

Investment In China

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.

Download Full-text

Smart Grid Modernization: Opportunities and Challenges

10.5772/intechopen.97892 ◽

2021 ◽

Author(s):

Saumen Dhara ◽

Alok Kumar Shrivastav

Keyword(s):

Smart Grid ◽

Electric Power ◽

Distribution System ◽

Power Grid ◽

Green Energy ◽

Pattern Generation ◽

Control Technology ◽

Electric Power Grid ◽

Bulk Power ◽

Transmission And Distribution

Recently, there have been significant technological approaches for the bulk power grid. The customer demand is associated with conventional grid coupled large central generating stations through a high voltage transmission to a distribution system. Urban transmission systems are consistently progressing to meet the increasing needs for power and to replace old-pattern generation with native renewable generation and power provisions from outward green energy resources. Power grid is undergoing remarkable modernization towards advanced consistency, greater efficiency, and less cost by the incorporation of renewable energy and developed control technology. Quick developing nature of grid, consumer needs, and industrial invention situates substation modernization at the leading of grid transformation. Smart grid is essential to accomplish all the fastest technological reformations occurring in generation, transmission and distribution (T&D) of electric power, with growing application of sensors, computers and communications. In this study the recent trend and application of electric power grid is briefly enunciated.

Download Full-text

Research on Project Risk Management of Power Engineering Based on Fuzzy Comprehensive Evaluation Method

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.415.287 ◽

2013 ◽

Vol 415 ◽

pp. 287-293

Author(s):

Li Xin Zheng

Keyword(s):

Risk Management ◽

Electric Power ◽

Risk Evaluation ◽

Large Scale ◽

Evaluation Method ◽

Comprehensive Evaluation ◽

Fuzzy Comprehensive Evaluation ◽

Power Engineering ◽

Engineering Project ◽

Electric Power Engineering

The electric power engineering project has many characteristics like large scale, long construction period, complex technology, many units involved and so on. In order to avoid risk and improve the risk management efficiency of electric power engineering project, this article established a risk evaluation index system from the perspective of environmental risk, economic risk, technical risk, management risk, and market risk. According to the characteristics of the risk evaluation indicators, it built a multi-level fuzzy comprehensive evaluation model and took a power construction projects as an example to analyze the application of the model.

Download Full-text

A combined fuzzy and probability risk evaluation model for electric power grid investments

2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies ◽

10.1109/drpt.2008.4523454 ◽

2008 ◽

Author(s):

Chengwen Wang ◽

Zhongfu Tan ◽

Li Li

Keyword(s):

Electric Power ◽

Risk Evaluation ◽

Evaluation Model ◽

Power Grid ◽

Electric Power Grid ◽

Risk Evaluation Model

Download Full-text

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 ◽

10.1051/e3sconf/202125701005 ◽

2021 ◽

Vol 257 ◽

pp. 01005

Author(s):

Ze Qi ◽

Peipei You ◽

Rengcun Fang ◽

Zhao Xu ◽

Yuxin Zou ◽

...

Keyword(s):

Risk Evaluation ◽

Power Transmission ◽

Cloud Model ◽

Evaluation Model ◽

Power Grid ◽

Evaluation Criteria ◽

Electric Power Industry ◽

Risk Level ◽

Electricity Transmission ◽

Transmission And Distribution

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.

Download Full-text

Optimal Allocation of Large-Capacity Distributed Generation with the Volt/Var Control Capability Using Particle Swarm Optimization

Energies ◽

10.3390/en14113112 ◽

2021 ◽

Vol 14 (11) ◽

pp. 3112

Author(s):

Donghyeon Lee ◽

Seungwan Son ◽

Insu Kim

Keyword(s):

Particle Swarm Optimization ◽

Electric Power ◽

Distributed Generation ◽

Optimal Allocation ◽

Power Grid ◽

Particle Swarm ◽

Renewable Energy Resources ◽

Swarm Optimization ◽

Large Capacity ◽

Electric Power Grid

Widespread interest in environmental issues is growing. Many studies have examined the effect of distributed generation (DG) from renewable energy resources on the electric power grid. For example, various studies efficiently connect growing DG to the current electric power grid. Accordingly, the objective of this study is to present an algorithm that determines DG location and capacity. For this purpose, this study combines particle swarm optimization (PSO) and the Volt/Var control (VVC) of DG while regulating the voltage magnitude within the allowable variation (e.g., ±5%). For practical optimization, the PSO algorithm is enhanced by applying load profile data (e.g., 24-h data). The objective function (OF) in the proposed PSO method considers voltage variations, line losses, and economic aspects of deploying large-capacity DG (e.g., installation costs) to transmission networks. The case studies validate the proposed method (i.e., optimal allocation of DG with the capability of VVC with PSO) by applying the proposed OF to the PSO that finds the optimal DG capacity and location in various scenarios (e.g., the IEEE 14- and 30-bus test feeders). This study then uses VVC to compare the voltage profile, loss, and installation cost improved by DG to a grid without DG.

Download Full-text