Congestion Management in Interconnected Power System using Water Cycle Algorithm
Main Article Content
Abstract
Nowadays, it is desirable for the power industry to transmit power between different sites of the transmission system in the most cost-effective manner. Congestion management is one of the system operator's most challenging responsibilities in a deregulated context. Congestion would increase electricity costs and transmission loss and have a negative impact on the system's stability and security, so system operators work on it to reduce congestion in deregulated power systems. In this investigation, congestion is handled by considering three objective functions. The first objective is to minimize the generation cost and the second objective is to minimize the transmission loss of the system and third objective is to minimize the total congestion expanse. A water cycle algorithm is employed to mitigate the proposed congestion management and an IEEE 30 bus and 118 bus test system is employed to demonstrate the effectiveness of the suggested approach.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.
- Creative Commons Copyright License
The journal allows readers to download and share all published articles as long as they properly cite such articles; however, they cannot change them or use them commercially. This is classified as CC BY-NC-ND for the creative commons license.
- Retention of Copyright and Publishing Rights
The journal allows the authors of the published articles to hold copyrights and publishing rights without restrictions.
References
D. K., Kumar, T. A. R., & Alla, R. K. R. (2022). Effect of Partial Shading on the Performance of Various 4×4 PV Array Configurations. ECTI Transactions on Electrical Engineering, Electronics, and Communications, 20(3), 427–437. https://doi.org/10.37936/ecti-eec.2022203.247518
Thorat, S., & Kalkhambkar, V. N. (2021). Management of a Solar-PV System with Energy Storage. ECTI Transactions on Electrical Engineering, Electronics, and Communications, 19(3), 233–245. https://doi.org/10.37936/ecti-eec.2021193.222654.
M. Pantoš, “Market-based congestion management in electric power systems with exploitation of aggregators,” International Journal of Electrical Power & Energy Systems, 121, PP. 106101, 2020.
EL-Azab, M. Omran, W. A,Mekhamer, S. F., & Talaat, H. E. A. ‘‘Congestion management of power systems by optimizing grid topology and using dynamic thermal rating’’, Electric Power Systems Research, 199, PP.107433, 2021.
S. Namilakonda & Y. Guduri, ‘‘Chaotic darwinian particle swarm optimization for real-time hierarchical congestion management of power system integrated with renewable energy sources’’, International Journal of Electrical Power & Energy Systems, 128, PP.106632, 2021.
J. R.Chintam, & M. Daniel, “Real-power rescheduling of generators for congestion management using a novel satin bowerbird optimization algorithm” Energies, 11(1), PP.183, 2018.
M. Sarwar, A. Siddiqui, S. Ghoneim, S.S, Mahmoud, K., & M. M Darwish “Effective Transmission Congestion Management via Optimal DG Capacity using Hybrid Swarm Optimization for Contemporary Power System Operations”, IEEE Access, 2022
S. Charles Raja, S. Prakash, & J. Jeslin Drusila Nesamalar, “Effective Power Congestion Management Technique Using Hybrid Nelder–Mead–Grey Wolf Optimizer (HNMGWO) in Deregulated Power System,” IETE Journal of Research, PP.1-12, 2021.
D. Asija, & P. Choudekar, “Congestion management using multi-objective hybrid DE-PSO optimization with solar-ess based distributed generation in deregulated power Market”, Renewable Energy Focus, 36, PP.32-42, 2021.
S. R. Salkuti, & S. C. Kim, “Congestion management using multi-objective glow worm swarm optimization algorithm,” Journal of Electrical Engineering & Technology, 14(4), PP.1565-1575, 2019.
S. R. Salkuti, “Congestion management using optimal transmission switching,” IEEE Systems Journal, 12(4), PP. 3555-3564, 2018.
A. Sharma, & S. K. Jain, “Gravitational search assisted algorithm for TCSC placement for congestion control in deregulated power system”. Electric Power Systems Research, 174, PP. 105874, 2019.
D. F. Farzana, & K. Mahadevan, “Performance comparison using firefly and PSO algorithms on congestion management of deregulated power market involving renewable energy sources”, Soft Computing, 24(2), PP.1473-1482, 2020.
I. Batra, & S. Ghosh, “A novel approach of congestion management in deregulated power system using an advanced and intelligently trained twin extremity chaotic map adaptive particle swarm optimization algorithm,” Arabian Journal for Science and Engineering, 44(8), PP. 6861-6886, 2019.
M. Moazzami, H. Shahinzadeh, G. B. Gharehpetian, & A. Shafiei “Optimal TCSC placement for congestion management in deregulated power systems using antlion optimization algorithm,” IAES International Journal of Robotics and Automation, 8(2),PP. 77, 2019.
P. K. Tiwari, M. K .Mishra& S. Dawn, “A two step approach for improvement of economic profit and emission with congestion management in hybrid competitive power market”, International Journal of Electrical Power & Energy Systems, 110,pp.548-564,2019.
N. K. Patel, B. N. Suthar, & J. Thakkar, “Transmission congestion management considering voltage stability margin”, SN Applied Sciences, 3(2), pp.1-12, 2021.
Semshchikov, E., & Negnevitsky, M. (2018, November). Congestion management optimization in electric transmission system. In Australasian Universities Power Engineering Conference (AUPEC),pp. 1-5,IEEE,2018
H. Eskandar, A. Sadollah, A. Bahreininejad, & M. Hamdi,“Water cycle algorithm–A novel metaheuristic optimization method for solving constrained engineering optimization problems,” Computers & Structures, 110, pp. 151-166, 2012.
SS. Reddy, AR. Abhyankar, P. Bijwe, ‘‘Faster Evolutionary Algorithm Based Optimal Power Flow Using Incremental Variables’’,International Journal of Electrical Power & Energy Systems,Vol.54 pp.198-210, 2014.
Houndjéga, M., Muriithi, C. M., & Wekesa, C. W. (2018). Active power rescheduling for congestion management based on generator sensitivity factor using ant lion optimization algorithm. Int J Eng Res Technol, 11(10), 1565-1582.
Vengadesan, A. (2021). Transmission Congestion Management through Optimal Placement and Sizing of TCSC Devices in a Deregulated Power Network. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(6), 5390-5403