COMPARATIVE ANALYSIS OF A METAHEURISTIC OPTIMIZER APPROACH FOR THE SOLUTION OF OPTIMAL POWER FLOW PROBLEM
DOI:
https://doi.org/10.11113/aej.v14.21180Keywords:
Optimal Power Flow, Teaching-Learning Based Optimization, Particle Swarm Optimization,, IEEE-30 bus test system., Optimal Power Flow, Teaching-Learning Based Optimization, Particle Swarm Optimization, IEEE-30 bus test system.Abstract
This work uses population-based particle swarm optimization (PSO) and teaching-learning- based optimization (TLBO) methodologies to solve the optimal power flow problem, and the outcomes of both methods are contrasted. One issue that needs to be addressed in power systems is financial loss. Appropriate scheduling of energy produced by different generation sources in the power network is necessary to address the aforementioned issue. This paper formulates an optimal power flow (OPF) issue and solves it to find the optimal values for the control variables. In this case study, five objective functions are developed for five distinct scenarios to verify the effectiveness of the proposed methodology in MATLAB application. The five objectives are as follows: minimizing fuel costs, improving voltage profiles, reducing active and reactive power losses on transmission lines, and improving voltage stability. The fitness function is considered as a single-objective function based on the control parameters. In order to assess the applicability of the proposed method, it has been used to the IEEE 30 bus test system to investigate the performance of the power system for certain objective functions. According to results from PSO and TLBO optimization techniques as well as results from the techniques mentioned in the literature, the Teaching-Learning-Based Optimization technique offers an effective and dependable solution when tackling the optimal power flow problem with a variety of complexities. To demonstrate how rapidly the offered technique may converge to optimal and useful global solutions and how it can handle the problem's various complexities, the achieved optimal solutions are contrasted
References
Virginijus Radziukynas, and Ingrida Radziukyniene, 2009. "Optimization methods application to optimal power flow in electric power systems," In Optimization in the Energy Industry, 409-436. Berlin, Heidelberg: Springer Berlin Heidelberg,
Salma Abd El-Sattar, Salah Kamel, Ragab A. El Sehiemy, Francisco Jurado, and Juan Yu, 2019 "Single-and multi-objective optimal power flow frameworks using Jaya optimization technique," Neural Computing and Applications 31: 8787-8806.
Gómez Expósito, Antonio, Antonio J. Conejo, and Claudio Cañizares, “Electric energy systems: analysis and operation,” CRC press, 2018.
Ion Boldea, Lucian Nicolae Tutelea, and Ana Adela Popa. 2021 "Reluctance synchronous and flux-modulation machines designs: Recent progress," IEEE Journal of Emerging and Selected Topics in Power Electronics. 10(2): 1683-1702.
Murlidhar Vinayak Deshpande, 2009. Elements of electrical power station design. PHI Learning Pvt. Ltd.
Sidhartha Panda, Binod Kumar Sahu, and Pradeep Kumar Mohanty, 2012"Design and performance analysis of PID controller for an automatic voltage regulator system using simplified particle swarm optimization," Journal of the Franklin Institute. 349(8): 2609-2625.
Russell C. Eberhart, and Yuhui Shi., 2000 "Comparing inertia weights and constriction factors in particle swarm optimization." In Proceedings of the 2000 congress on evolutionary computation, 1: 84-88.
Reyes Medina, Angelina Jane, Gregorio Toscano Pulido, and José Gabriel Ramírez-Torres, 2009."A comparative study of neighborhood topologies for particle swarm optimizers," In International conference on evolutionary computation, 2: 152-159, SciTePress.
Satyobroto Talukder, 2011. "Mathematicle modelling and applications of particle swarm optimization,"
James Crowe, G. R. Chen, R. Ferdous, D. R. Greenwood, M. J. Grimble, H. P. Huang, J. C. Jeng et al., 2005. “PID control: new identification and design methods,” Springer Verlag London Limited.
John Ziegler, and Nathaniel B. Nichols, 1942. "Optimum settings for automatic controllers," Transactions of the American society of mechanical engineers. 64(8): 759-765.
Djamel Eddine Ghouraf, and Abdellatif Naceri, 2014. "An advanced pid-pss based genetic algorithms implemented using gui-matlab." In 2014 International Renewable and Sustainable Energy Conference (IRSEC), 411-418.
Haluk Gözde, M. Cengiz Taplamacioğlu, and Murat Ari, 2017. "Simulation study for global neighborhood algorithm based optimal automatic voltage regulator (AVR) system," In 2017 5th international istanbul smart grid and cities congress and fair (ICSG), 46-50.
Baran Hekimoğlu, and Serdar Ekinci, 2018. "Grasshopper optimization algorithm for automatic voltage regulator system," In 2018 5th international conference on electrical and electronic engineering (ICEEE), 152-156.
Sheikh Abid Hossain, Sourav Roy, Animesh Karmaker, and Md Rafiqul Islam, 2015. "Performance improvement of PID controller for AVR system using Particle Swarm Optimization," In 2015 International Conference on Advances in Electrical Engineering (ICAEE), 243-246.
Kiyong Kim, Pranesh Rao, and Jeff Burnworth, 2008."Application of swarm intelligence to a digital excitation control system," In 2008 IEEE Swarm Intelligence Symposium, 1-8,
Rouani Lahcene, Sebbane Abdeldjalil, and Kheldoun Aissa, 2017. "Optimal tuning of fractional order PID controller for AVR system using simulated annealing optimization algorithm," In 2017 5th international conference on electrical engineering-boumerdes (ICEE-B), 1-6,
Kuppuraju Elumalai, and S. Sumathi, 2017. "Behavior modification of PID controller for AVR system using particle swarm optimization," In 2017 Conference on Emerging Devices and Smart Systems (ICEDSS), 190-195.
Naeim Farouk Mohammed, Enzhe Song, Xiuzhen Ma, and Qaisar Hayat, 2014. "Tuning of PID controller of synchronous generators using genetic algorithm," In 2014 IEEE International Conference on Mechatronics and Automation, 1544-1548,
Niranjan Nayak, Sangram Keshari Routray, and Soumya Pradhan, 2015"Optimal design of PID controller for AVR in a multi machine power system using modified PSO and fire fly optimization technique," In 2015 IEEE Power, Communication and Information Technology Conference (PCITC), 768-775,
Avinash Sahu, and L. B. Prasad, 2017. "Load frequency control of interconnected five-area power system with PID controller." In 2017 International Conference on Information, Communication, Instrumentation and Control (ICICIC). 1-8,
Lal Bahadur Prasad, Barjeev Tyagi, and Hari Om Gupta, 2017. "Fuzzy-PI based automatic generation control of two-area interconnected nonlinear power system," International Journal of System Control and Information Processing, 2(2): 127-141.
Durlav Hazarika, and Mr. Ranjay Das, 2012. "An Algorithm for Determining the Load Margin of an Interconnected Power System," International Journal of Energy Science, 2(5): 169-174.
Mohammad Sulaiman Redoy, and Ruma, 2022. "Load Frequency Control of an Inter Connected Power System Using PSO Based PID Controller," In 2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE), 1-5.
Solomon Feleke, Raavi Satish, Surender Reddy Salkuti, and Almoataz Y. Abdelaziz, 2023."Load Frequency Control in Two-Area Interconnected Systems Using DE-PID and PSO-PID," In Power Quality in Microgrids: Issues, Challenges and Mitigation Techniques, 391-407, Singapore: Springer Nature Singapore.
Vincent N. Ogar, Sajjad Hussain, and Kelum AA Gamage, 2023 "Load frequency control using the particle swarm optimization algorithm and pid controller for effective monitoring of transmission line," Energies. 16(15): 5748-5764.
Hiramani Shukla, Srete Nikolovski, More Raju, Ankur Singh Rana, and Pawan Kumar, 2022."A particle swarm optimization technique tuned TID controller for frequency and voltage regulation with penetration of electric vehicles and distributed generations," Energies 15(21): 8225.
Emre Celik, Nihat Öztürk, and Essam H. Houssein, 2023."Improved load frequency control of interconnected power systems using energy storage devices and a new cost function," Neural Computing and Applications. 35(1): 681-697.
Deepak Kumar Gupta, Geetanjali Dei, Ankit Kumar Soni, Amitkumar V. Jha, Bhargav Appasani, Nicu Bizon, Avireni Srinivasulu, and Philibert Nsengiyumva, 2024."Fractional order PID controller for load frequency control in a deregulated hybrid power system using Aquila Optimization," Results in Engineering. 102442.
Gotte Vikram Raju, and Nandiraju Venkata Srikanth, 2024."Frequency control of an islanded microgrid with multi-stage PID control approach using moth-flame optimization algorithm," Electrical Engineering. 1-18.
Khaizaran Al Sumarmad, Nasri Sulaiman, Noor Izzri Abdul Wahab, and Hashim Hizam, 2023."Implementation of hybrid optimized battery controller and advanced power management control strategy in a renewable energy integrated DC microgrid," Plos one. 18(6): e0287136.
Rafiq Asghar, Francesco Riganti Fulginei, Hamid Wadood, and Sarmad Saeed, 2023."A review of load frequency control schemes deployed for wind-integrated power systems," Sustainability. 15(10): 8380.
Shreekanta Kumar Ojha, and Chinna Obaiah Maddela, 2024."Load frequency control of a two-area power system with renewable energy sources using brown bear optimization technique," Electrical Engineering 106(3): 3589-3613.
Sing Hsia Yeoh, Kah Haur Yiauw, Sook Yee Yip, and Zhi Hong Kwan, 2024."Optimizing Frequency Stability in Power Systems through Particle Swarm Optimization-Based Control Strategies," In 2024 20th IEEE International Colloquium on Signal Processing & Its Applications (CSPA), 79-84.
Santosh Kumari, and Pawan Kumar Pathak, 2024. "A state-of-the-art review on recent load frequency control architectures of various power system configurations," Electric Power Components and Systems 52(5): 722-765.
Arti Saxena, Y. M. Dubey, Manish Kumar, and Abneesh Saxena, 2023."Performance comparison of ANFIS, FOPID-PSO and FOPID-fuzzy tuning methodology for optimizing response of high-performance drilling machine," IETE Journal of Research 69(6): 3497-3510.
Sanjeev Kumar Bhagat, Lalit Chandra Saikia, and Naladi Ram Babu, 2024 "Application of an optimal tilt controller in a partial loading schedule of multi-area power system considering HVDC link and virtual inertia," ISA transactions. 146: 437-450.
Basma, Hany M. Hasanien Salah, Fadia MA Ghali, Yasser M. Alsayed, Shady HE Abdel Aleem, and Adel El-Shahat, 2022."African vulture optimization-based optimal control strategy for voltage control of islanded DC microgrids," Sustainability. 14(19): 11800.
Masoud Alilou, Hatef Azami, Arman Oshnoei, Behnam Mohammadi-Ivatloo, and Remus Teodorescu, 2023 "Fractional-order control techniques for renewable energy and energy-storage-integrated power systems: A review," Fractal and Fractional. 7(5): 391.
Sindhura Gupta, Susovan Mukhopadhyay, Ambarnath Banerji, Prasun Sanki, Pampa Sinha, Sujit K. Biswas, Baseem Khan, Ahmed Ali, and Pitshou Bokor, 2024 "Student psychology-based optimization-tuned cascaded controller for frequency regulation of a microgrid," Frontiers in Energy Research 12: 1355608.
Yan Zhang, Ya-Jun Wang, Yong Zhang, and Tong Yu, 2022 "Photovoltaic fuzzy logical control MPPT based on adaptive genetic simulated annealing algorithm-optimized BP neural network," Processes 10(7): 1411.
Arpit Yadav, and Ranjay Das, 2023, “Survey of Optimization Techniques in Interconnected Two Area Power System for the Application of AGC,” Journal of Energy Engineering and Thermodynamics (JEET) 2815-0945 4 (01):19-29.
Arpit Yadav, and Ranjay Das, 2024."Intelligent Power System Control and Healthcare Data Analysis: A PSO-Based PID Approach," In Revolutionizing Healthcare Treatment With Sensor Technology, 223-237. IGI Global,
Ahmed M. Nassef, Mohammad Ali Abdelkareem, Hussein M. Maghrabie, and Ahmad Baroutaji, 2023. "Review of metaheuristic optimization algorithms for power systems problems," Sustainability 15(12): 9434
Ditao Duan, and Roza Poursoleiman, "Modified teaching-learning-based optimization by orthogonal learning for optimal design of an electric vehicle charging station," Utilities Policy 72: 101253, 2021.
Ali Maroosi, and Ravie Chandren Muniyandi, 2023. "A novel membrane‐inspired multiverse optimizer algorithm for quality of service‐aware cloud web service composition with service level agreements," International Journal of Communication Systems 36(9): e5483.
Usman Mussadiq, Saeed Ahmed, Muhammad Sajid, Dalia H. Elkamchouch, Lal Hussain, Abdulbaset Gaddah, Fahd N. Al-Wesabi, and Anwer Mustafa Hilal, 2023 "The intelligent modelling and optimization of an economic and ecosystem-friendly model for grid connected prosumer community," Plos one 18(1): e0276510.
Marcos Tostado-Véliz, Ahmad Rezaee Jordehi, Daniel Icaza, Seyed Amir Mansouri, and Francisco Jurado, 2023. "Optimal participation of prosumers in energy communities through a novel stochastic-robust day-ahead scheduling model," International Journal of Electrical Power & Energy Systems 147: 108854.
Mahmoud Zadehbagheri, Saeed Masoumi, and Vahdat Nazerian, 2024."Coordinating the participation of energy sources and wind units in micro-grid frequency control by delaying micro-grid parameter measurement systems," International Journal of Smart Grid-ijSmartGrid 8(2): 81-97.
Madhab Chandra Das, Sarat Chandra Swain, Pritam Patel, Chinmay Kumar Nayak, Binay Kumar Nayak, and Rosalin Pradhan, 2023."Benefit maximization of prosumer with grid-connected PV-BESS system using Social Group Optimization," In 2023 IEEE 2nd International Conference on Industrial Electronics: Developments & Applications (ICIDeA). 88-94.
