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

Mathematics ◽  
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.

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

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 989
Author(s):  
Wenjin Li ◽  
Bingkang Li ◽  
Rengcun Fang ◽  
Peipei You ◽  
Yuxin Zou ◽  
...  
Keyword(s):  
Electric Power ◽  
Risk Evaluation ◽  
Evaluation Method ◽  
Power Grid ◽  
Fuzzy Comprehensive Evaluation ◽  
Electricity Transmission ◽  
Electric Power Grid ◽  
Mcdm Method ◽  
Transmission And Distribution ◽  
Power Grid Enterprise

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.

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

Energies ◽  
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.

ASSiST - a Superconducting Fault Current Limiter in a Public Electric Power Grid

2021 ◽  
pp. 1-1
Author(s):  
Hans Peter Kraemer ◽  
Anne Bauer ◽  
Michael Frank ◽  
Peter Van Hasselt ◽  
Peter Kummeth ◽  
...  
Keyword(s):  
Electric Power ◽  
Power Grid ◽  
Fault Current ◽  
Fault Current Limiter ◽  
Superconducting Fault Current Limiter ◽  
Electric Power Grid ◽  
Current Limiter

FCL application issues in Korean electric power grid

2006 ◽  
Author(s):  
Soo-Hoan Lee ◽  
Kang-Wan Lee ◽  
Yong-Beum Yoon ◽  
Ok-Bae Hyun
Keyword(s):  
Electric Power ◽  
Power Grid ◽  
Electric Power Grid
Sign in / Sign up

Export Citation Format

Share Document