scholarly journals The provincial power grid monthly purchasing risk management model based on Monte-Carlo stochastic simulation technology and wind power uncertainty

Author(s):  
Junmei Wang ◽  
Lin Guo ◽  
Chao Ma ◽  
Chuncheng Gao ◽  
Dunnan Liu ◽  
...  
Author(s):  
Cunbin Li ◽  
Ding Liu ◽  
Yi Wang ◽  
Chunyan Liang

AbstractAdvanced grid technology represented by smart grid and energy internet is the core feature of the next-generation power grid. The next-generation power grid will be a large-scale cyber-physical system (CPS), which will have a higher level of risk management due to its flexibility in sensing and control. This paper explains the methods and results of a study on grid CPS’s behavior after risk. Firstly, a behavior model based on hybrid automata is built to simulate grid CPS’s risk decisions. Then, a GCPS risk transfer model based on cooperative game theory is built. The model allows decisions to ignore complex network structures. On this basis, a modified applicant-proposing algorithm to achieve risk optimum is proposed. The risk management model proposed in this paper can provide references for power generation and transmission decision after risk as well as risk aversion, an empirical study in north China verifies its validity.


2018 ◽  
Vol 24 (4) ◽  
pp. 2306-2311
Author(s):  
Hashim Ali ◽  
Nousheen Akhtar ◽  
Muhammad Younus Javed

2014 ◽  
Vol 953-954 ◽  
pp. 587-590 ◽  
Author(s):  
Shuang Yang

This paper aims to put forward a wind power plant risk management model, using bayesian networks, not only suitable for the project risk management, also useful for subsequent projects. For other construction enterprise risk management problem has great reference value.


Sign in / Sign up

Export Citation Format

Share Document