Power System Security Assessment (PSSSA) Module Using GEORFA Technique

DOI

10.2991/978-94-6463-074-9_4How to use a DOI?

Keywords

Power system security; Golden Eagle Optimizer; Random Decision Forest; line outage contingencies

Abstract

The electrical power system network contingency evaluation and it’s ranking method is very importance in present power systems network for its secured operation under various contingencies. This paper proposes golden eagle optimizer (GEO) and random forest algorithm (RFA) to assess the online/offline power system static security assessment (PSSSA) module. To calculate the ranking of security of the system for its operational constraints, two indices are used, the first one is as active power performance index and the other one is voltage performance index. These are evaluated by using Newton–Raphson method of load flow for variable loading/fault conditions under line outage. The proposed PSSSA module is applied on power system with various operating states, load conditions and line outage contingencies, to calculate the performance indices for unknown faults and network conditions and rank them in ascending/descending order based on indices used for security assessment. This method is tested on a standard IEEE 30-bus system. The results are showing it a best way for assessing the security of power system. The results are compared obtained from the models and the load flow analysis in terms of simulation time and precision proves the proposed model is fast and robust for the assessment power system security under various contingencies. The proposed approach is implemented/simulated using the MATLAB Simulink platform and the performance is compared with the existing methods.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - A. Amarendra
AU  - L. Ravi Srinivas
AU  - R. Srinivasa Rao
PY  - 2022
DA  - 2022/12/05
TI  - Power System Security Assessment (PSSSA) Module Using GEORFA Technique
BT  - Proceedings of the International Conference on Artificial Intelligence Techniques for Electrical Engineering Systems (AITEES 2022)
PB  - Atlantis Press
SP  - 23
EP  - 32
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-074-9_4
DO  - 10.2991/978-94-6463-074-9_4
ID  - Amarendra2022
ER  -