scholarly journals Multi-Output Regression for Analyzing Power System Random States in Reliability Assessment by the Monte Carlo Method

2021 ◽  
pp. 49
Author(s):  
D. A. Boyarkin
Keyword(s):  
Machine Learning ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Power System ◽  
Electric Power ◽  
Reliability Assessment ◽  
Electric Power System ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
The Monte Carlo Method

Increasing calculation speed of the electric power system (EPS) reliability of is one of the key issues in their operational management and long-term development planning. Analytical methods to assess the EPS reliability seem to be impossible due to large size of the problem and, as a consequence, essentially the only option for assessing is to use the Monte Carlo method. When it is used both the speed and the accuracy of calculation directly depend on the number of randomly generated system states and the complexity of their calculation in the model. Methods aimed at increasing computational efficiency can relate to two directions - reducing the states under consideration and simplifying the computational model for each state. Both options are performed provided that calculation accuracy is retained.The article presents research on using the machine learning methods and, in particular, the multi-output regression method to modernize the reliability assessment technique via the Monte Carlo method. Machine learning methods are used to determine the power deficit (realization of a random variable) for each random EPS state.The use of multi-output regression enables comprehensive determining of values of all the required variables. The experimental studies are based on the two test circuits of electric power systems: three-zone and IEEE RTS-96 with 24 zones of reliability.

scholarly journals Prediction of the power shortage in the electric power system by means of regression analysis by machine learning methods

2019 ◽  
Vol 114 ◽  
pp. 03003
Author(s):  
D.A. Boyarkin ◽  
D.S. Krupenev ◽  
D.V. Iakubobsky
Keyword(s):  
Monte Carlo ◽  
Regression Analysis ◽  
Monte Carlo Method ◽  
Electric Power ◽  
Electric Power System ◽  
Alternative Methods ◽  
Support Vector ◽  
Operating Modes ◽  
The Monte Carlo Method ◽  
Random States

Modern electricity consumers place increasingly high demands on the level of reliability of power supply and, correspondingly, the reliability of electric power systems (EPS). These requirements should be directly addressed in the EPS development planning tasks. To this end, the evaluation of the level of EPS reliability is performed by employing software and computer systems that have various methods of reliability evaluation implemented therein. Among the variety of methods for identifying reliability indicators to evaluate resource adequacy the most appropriate one is the Monte Carlo method (the method of statistical tests): it enables to perform calculations within a reasonable time with the required accuracy, while the calculation of complex EPS-like systems by means of analytical methods proves impossible because of the large dimensionality of the problem. However, even when using the Monte Carlo method, the difficulties arise as well, namely the problem of the need to reproduce a large number of random states of the simulated EPS and the calculation of the operating mode of each of them. There are several ways to reduce the overall calculation time by either efficient random number generators and optimizers or alternative methods of the calculation of operating modes. The article deals with the issue of bringing up to date the method behind reliability calculation that makes use of the Monte Carlo method. We propose to use regression analysis methods when calculating operating modes of random states of the EPS. To this end, we adopt the support-vector machine and the random forest method. Experimental studies covered in the article attest to the efficiency of the new method, for the 24-node system IEEE RTS-96 the calculation speed has been increased by almost a factor of 4 while maintaining accuracy.

scholarly journals Analysis and Assessment of Operation Risk for Hybrid AC/DC Power System based on the Monte Carlo Method

2018 ◽  
Vol 38 ◽  
pp. 04010
Author(s):  
Xiaojing Hu ◽  
Qiang Li ◽  
Hao Zhang ◽  
Ziming Guo ◽  
Kun Zhao ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Power System ◽  
Power Flow ◽  
Assessment Method ◽  
Active Power ◽  
Dc Power ◽  
The Monte Carlo Method ◽  
Node Voltage ◽  
Operation Risk

Based on the Monte Carlo method, an improved risk assessment method for hybrid AC/DC power system with VSC station considering the operation status of generators, converter stations, AC lines and DC lines is proposed. According to the sequential AC/DC power flow algorithm, node voltage and line active power are solved, and then the operation risk indices of node voltage over-limit and line active power over-limit are calculated. Finally, an improved two-area IEEE RTS-96 system is taken as a case to analyze and assessment its operation risk. The results show that the proposed model and method can intuitively and directly reflect the weak nodes and weak lines of the system, which can provide some reference for the dispatching department.

Reliability Assessment for Telecommunication Channel of Electric Power System Using AHP

2014 ◽  
Vol 644-650 ◽  
pp. 4052-4060
Author(s):  
Cheng Zhi Bian ◽  
Bo Wang ◽  
Fei Tang ◽  
Yu Xi Chen ◽  
Jun Jia ◽  
...  
Keyword(s):  
Power System ◽  
Electric Power ◽  
Reliability Assessment ◽  
Past Research ◽  
Electric Power System ◽  
Failure Data ◽  
Equipment Reliability ◽  
Modification Factor ◽  
Actual Operation ◽  
Hierarchy Process

The reliability assessment is a key function that should be performed in advance of any security deployment. Since the reliability of electric power communication channel is influenced by many factors, modification factor set for telecommunication channel of electric power system is needed. According to past research, the confidence for equipment reliability would decline caused by the lack of failure data. Therefore, the paper modified each initial index calculated only by the failure data to obtain the reliability. Comprehensive modification factor is obtained according to the weight of each index calculated with Hierarchy Process whose computing standard is the importance of the modification factor in the actual operation. Finally, an instance communication network of power control system is modeling to test the validity of reliability assessment. The result supports the usefulness of the reliability assessment.

Sign in / Sign up

Export Citation Format

Share Document