SECURITY CONSTRAINED OPTIMAL POWER FLOW BASED ON AN ARTIFICIAL INTELLIGENCE TECHNIQUE
In the past, artificial intelligence techniques were successfully adopted for obtaining optimal power flow in a power system. However, this optimality is limited to the economic aspects of the system's operating conditions. The other aspects of the operation, like security conditions, have bee...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | Arabic |
| Published: |
Mustansiriyah University/College of Engineering
2023-11-01
|
| Series: | Journal of Engineering and Sustainable Development |
| Subjects: | |
| Online Access: | https://jeasd.uomustansiriyah.edu.iq/index.php/jeasd/article/view/1904 |
| _version_ | 1827777304882839552 |
|---|---|
| author | Ayman Almansory Kassim Al-Anbarri |
| author_facet | Ayman Almansory Kassim Al-Anbarri |
| author_sort | Ayman Almansory |
| collection | DOAJ |
| description |
In the past, artificial intelligence techniques were successfully adopted for obtaining optimal power flow in a power system. However, this optimality is limited to the economic aspects of the system's operating conditions. The other aspects of the operation, like security conditions, have been given limited attention. Hence, this paper presents an attempt to dispatch the power generation in electrical power systems optimally by taking into consideration both economic and secure operations, so that modern power systems can operate reliably and effectively. Security-constrained optimal power flow is addressed in this paper as a multi-objective optimization problem, consisting of four objective functions: minimizing power generation costs; minimizing voltage deviation; minimizing power losses; and alleviating the overloading on transmission lines. A detailed steady-state generator model is adopted in the present formulation. A metaheuristic optimization technique, namely, differential evolution, is used to obtain the security constraint optimal power dispatch. Additionally, the operating states of a power system have been addressed in this paper. The identification of the operating states is vital to the assessment of the security of the EPS. Improvements and appropriate security assessments have been made in some cases. The proposed algorithm is applied to a typical power system with different operating strategies. The obtained results are compared to those obtained from previous studies in the literature to demonstrate the suggested method's validity and effectiveness.
|
| first_indexed | 2024-03-11T14:16:27Z |
| format | Article |
| id | doaj.art-a5fa28c7dc304d1d92dc8d3bd84b3304 |
| institution | Directory Open Access Journal |
| issn | 2520-0917 2520-0925 |
| language | Arabic |
| last_indexed | 2024-03-11T14:16:27Z |
| publishDate | 2023-11-01 |
| publisher | Mustansiriyah University/College of Engineering |
| record_format | Article |
| series | Journal of Engineering and Sustainable Development |
| spelling | doaj.art-a5fa28c7dc304d1d92dc8d3bd84b33042023-11-01T05:01:21ZaraMustansiriyah University/College of EngineeringJournal of Engineering and Sustainable Development2520-09172520-09252023-11-0127610.31272/jeasd.27.6.5SECURITY CONSTRAINED OPTIMAL POWER FLOW BASED ON AN ARTIFICIAL INTELLIGENCE TECHNIQUEAyman Almansory0Kassim Al-Anbarri1Electrical Engineering Department, Collage of Engineering, Mustansiriayh University, Baghdad, IraqElectrical Engineering Department, Collage of Engineering, Mustansiriayah University, Baghdad, Iraq In the past, artificial intelligence techniques were successfully adopted for obtaining optimal power flow in a power system. However, this optimality is limited to the economic aspects of the system's operating conditions. The other aspects of the operation, like security conditions, have been given limited attention. Hence, this paper presents an attempt to dispatch the power generation in electrical power systems optimally by taking into consideration both economic and secure operations, so that modern power systems can operate reliably and effectively. Security-constrained optimal power flow is addressed in this paper as a multi-objective optimization problem, consisting of four objective functions: minimizing power generation costs; minimizing voltage deviation; minimizing power losses; and alleviating the overloading on transmission lines. A detailed steady-state generator model is adopted in the present formulation. A metaheuristic optimization technique, namely, differential evolution, is used to obtain the security constraint optimal power dispatch. Additionally, the operating states of a power system have been addressed in this paper. The identification of the operating states is vital to the assessment of the security of the EPS. Improvements and appropriate security assessments have been made in some cases. The proposed algorithm is applied to a typical power system with different operating strategies. The obtained results are compared to those obtained from previous studies in the literature to demonstrate the suggested method's validity and effectiveness. https://jeasd.uomustansiriyah.edu.iq/index.php/jeasd/article/view/1904power system securitydifferential evolutioneconomic dispatchmulti-objective optimization |
| spellingShingle | Ayman Almansory Kassim Al-Anbarri SECURITY CONSTRAINED OPTIMAL POWER FLOW BASED ON AN ARTIFICIAL INTELLIGENCE TECHNIQUE Journal of Engineering and Sustainable Development power system security differential evolution economic dispatch multi-objective optimization |
| title | SECURITY CONSTRAINED OPTIMAL POWER FLOW BASED ON AN ARTIFICIAL INTELLIGENCE TECHNIQUE |
| title_full | SECURITY CONSTRAINED OPTIMAL POWER FLOW BASED ON AN ARTIFICIAL INTELLIGENCE TECHNIQUE |
| title_fullStr | SECURITY CONSTRAINED OPTIMAL POWER FLOW BASED ON AN ARTIFICIAL INTELLIGENCE TECHNIQUE |
| title_full_unstemmed | SECURITY CONSTRAINED OPTIMAL POWER FLOW BASED ON AN ARTIFICIAL INTELLIGENCE TECHNIQUE |
| title_short | SECURITY CONSTRAINED OPTIMAL POWER FLOW BASED ON AN ARTIFICIAL INTELLIGENCE TECHNIQUE |
| title_sort | security constrained optimal power flow based on an artificial intelligence technique |
| topic | power system security differential evolution economic dispatch multi-objective optimization |
| url | https://jeasd.uomustansiriyah.edu.iq/index.php/jeasd/article/view/1904 |
| work_keys_str_mv | AT aymanalmansory securityconstrainedoptimalpowerflowbasedonanartificialintelligencetechnique AT kassimalanbarri securityconstrainedoptimalpowerflowbasedonanartificialintelligencetechnique |