FOREX Press I. J. of Electrical & Electronics Research
Support Open Access
  • Home/
  • IJEER-130325

Research Article |

Minimization of Transmission Congestion Cost using P-OPF based LSF, PSO and ANN Techniques

Author(s): Poonam B. Dhabai1, Sunil Kumar Gupta2, Neeraj Tiwari3

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 13, Issue 3

Publisher : FOREX Publication

Published : 30 September 2025

e-ISSN : 2347-470X

Page(s) : 596-601

DOI: https://doi.org/10.37391/IJEER.130325

Abstract

The inclusion of renewable energy sources (RES) into a stabilized network has opened gates to numerous optimization problems. Optimization of RES generation might not imply merely the myth of high availability but it is furthermore fenced by parameters such as transmission line power flow patterns, having the optimized location, bus nodal pricing (LMP), congestion scenario, congestion cost and reliability margins of the system (ATC,TRM). Integration of RES also drags towards the congestion episode within the transmission system. The uncertain behavior of renewable energy initiates uncertainty into the system from generation perspective. These uncertainties lead to congestion which alters the linear sensitivity factors (LSF), LMP and reliability margins of the network. The congestion scenario may jeopardize the security of transmission network hampering the limits of transmission lines. The change in marginal values reflects the occurrence of congestion with additional congestion cost. Different optimization tools have been introduced in order to optimize various objectives like optimization of generation, rescheduling generators, load curtailment etc. In this work we have presented optimization of congestion cost (i.e. Congestion Management in terms of economics) post inclusion of uncertain RES (here wind and solar source are considered) into the system. The optimization problem is resolved using Probability Optimal Power Flow (P-OPF) based Particle Swarm Optimization (PSO) technique in MATLAB-MATPOWER software with Area Based Congestion Management (ABCM).

Keywords: Available Transfer Capability, Transmission Reliability Margin, Congestion management.




Poonam B. Dhabai, Research Scholar, Department of EEE, Poornima University, Jaipur, India; Email: dhabaipoonam@gmail.com

Sunil Kumar Gupta, Professor, Department of EEE, Poornima University, Jaipur, India; Email: sunilsunel1980@gmail.com

Neeraj Tiwari, Professor, School of Engineering & Technology, Jaipur National University, Jaipur, India; Email: neeraj.tiwari@jnujaipur.ac.in

    [1] Tang, G.T., Bui, N.D.H. and Long, D.T. 2024. Congestion Management using the Circulatory System Based Optimization Algorithm. Engineering, Technology & Applied Science Research. 14, 3 (Jun. 2024), 14361–14366. DOI:https://doi.org/10.48084/etasr.7204.
    [2] Dhabai, P.B., Tiwari, N, (2021) “Analysis of Variation in Locational Marginal Pricing under Influence of Stochastic Wind Generation” for AI and IOT in Renewable Energy. Studies in Infrastructure and Control. Springer.
    [3] Poonam B. Dhabai, Neeraj Tiwari, (2021) “Optimization of hybrid energy generation” for Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies, Elsevier, Pages 21-47,2022.
    [4] Riyaz, S., Upputuri, R., Kumar, N. (2021). Congestion Management in Power System—A Review. In: Gupta, O.H., Sood, V.K. (eds) Recent Advances in Power Systems. Lecture Notes in Electrical Engineering, vol 699. Springer, Singapore. https://doi.org/10.1007/978-981-15-7994-3_39
    [5] Maede Zakaryaseraji, Ali Ghasemi-Marzbali, "Evaluating Congestion Management of Power System considering the Demand Response Program and Distributed Generation", International Transactions on Electrical Energy Systems, vol. 2022, Article ID 5818757, 13 pages, 2022. https://doi.org/10.1155/2022/5818757.
    [6] P. B. Dhabai and N. Tiwari, (2020) "Computation of Locational Marginal Pricing in the Presence of Uncertainty of Solar Generation" for 5th IEEE International Conference on Recent Advances andInnovations in Engineering (ICRAIE) , pp. 1-5,doi:10.1109/ICRAIE51050.2020.9358291.
    [7] P. Dhabai and N. Tiwari, (2020) "Analysis of Variation in Power Flows due to Uncertain Solar Farm Power Output and its Location in Network" for IEEE International Conference for Innovation in Technology (INOCON), pp. 1-4,doi:10.1109/INOCON50539.2020.9298308.
    [8] Dhabai, P. B., Tiwari, N., & Gupta, S. K. (2024). Comparative analysis of congestion management methods with integrated renewable energy generation. International Journal of Electrical and Electronics Research, 12(3), 1087–1093.
    [9] Jamil, I., Zhao, J., Zhang, L., Rafique, & Jamil, (2019) “Uncertainty Analysis of Energy Production for a 3×50MW AC Photovoltaic Project Based on Solar Resources” for International Journal of Photo-energy.
    [10] Debra Lew, Lori Bird, Michael Milligan, Bethany Speer, “Wind and Solar Curtailment”, International Workshop on Large-Scale Integration of Wind Power Into Power Systems as Well as on Transmission Networks for Offshore Wind Power Plants London, England, pp.22-25, 2018.
    [11] C.-N. Yu.et.al, (2018) “Congestion clusters-based markets for transmission management” for Proceedings of IEEE PES, Winter Meeting, New York, NY, pp. 821–832.
    [12] Farzaneh Haghighat Nia1, Hossein Niavand, “Impact of Renewable Energy Consumption on Economics in India”, International Journal of Energy Engineering, Vol.1, pp. 32-38, 2017.
    [13] Line Roald, Sidhant Misra, Michael Chertkov, Scott Backhaus, Göran Andersson,(2016) “Chance Constrained Optimal Power Flow with Curtailment and Reserves from Wind Power Plants” for Mathematics optimization and control.
    [14] Li, Y., Li, W., Yan, W., Yu, J., & Zhao, X, (2014) “Probabilistic Optimal Power Flow Considering Correlations of Wind Speeds Following Different Distributions” for IEEE Transactions on Power Systems, 29(4),1847–1854. https://doi.org/10.1109/TPWRS.2013.2296505
    [15] Rajnikant, H., Bhesdadiya, Dr, Rajesh, M., & Patel, (2014) “Available Transfer Capability Calculation Methods: A Review” for International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 3.
    [16] Lowery, C., & O’Malley, M, (2014) “Optimizing wind farm locations to reduce variability and increase generation” for International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Conference Proceedings, Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/PMAPS.2014.6960661
    [17] Weng, Z. X., Shi, L. B., Xu, Z., Yao, L. Z., Ni, Y. X., & Bazargan, M, (2012), “Effects of wind power variability and intermittency on power flow” for IEEE Power and Energy Society GeneralMeeting. https://doi.org/10.1109/PESGM.2012.6344727
    [18] Banerjee, B., Jayaweera, D., & Islam, S. M, (2012) “Probabilistic optimization of generation scheduling considering wind power output and stochastic line capacity” for 22nd Australasian Universities Power Engineering Conference: \Green Smart Grid Systems\, AUPEC.
    [19] Song, Y. H.et.al, (October 2012) “Congestion management considering voltage security constraints” for International Conference on Power System Technology, Vol. 3, pp. 13-17.
    [20] Sjodin, E., Gayme, D. F., & Topcu, U, (2012) “Risk-mitigated optimal power flow for wind powered grids” for Proceedings of the American Control Conference, pp. 4431–4437. Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/acc.2012.6315377
    [21] Attia, A.-F., Al-Turki, Y. A., & Abusorrah, A. M, (2012) “Optimal Power Flow Using Adapted Genetic Algorithm with Adjusting Population Size” for Electric Power Components and Systems, 40(11), 1285–1299. https://doi.org/10.1080/15325008.2012.689417
    [22] Daneshi, H., & Srivastava, A. K, (2011) “ERCOT electricity market: Transition from zonal to nodal market operation” for IEEE Power and Energy Society General Meeting. https://doi.org/10.1109/PES.2011.6039830
    [23] S. Z. Moussavi, A. Badri, & F. Rastegar Kashkooli, (2011) “Probabilistic Method of Wind Generation Placement for Congestion Management” for World Academy of Science, Engineering and Technology 56.
    [24] Morales, J. M., Conejo, A. J., & Pérez-Ruiz, J, (2011) “Simulating the impact of wind production on locational marginal prices” for IEEE Transactions on Power Systems, 26(2), 820–828. https://doi.org/10.1109/TPWRS.2010.2052374
    [25] Ahmadi, H., & Ghasemi, H, (2011) “Probabilistic optimal power flow incorporating wind power using point estimate methods” for 10th International Conference on Environment and Electrical Engineering, EEEIC.EU Conference Proceedings. https://doi.org/10.1109/EEEIC.2011.5874815
    [26] Othman, M. M., & Musirin, I, (2011) “A novel approach to determine transmission reliability margin using parametric bootstrap technique” for International Journal of Electrical Power and Energy Systems, 33(10),1666–1674. https://doi.org/10.1016/j.ijepes.2011.08.003
    [27] Neuhoff1, K., Boyd1, R., & Grau, T, (2011) “Renewable Electric Energy Integration: Quantifying the Value of Design of Markets for International Transmission Capacity” for IEEE Transactions, 2, 107–114.
    [28] A. Vergnol, V. Rious, J. Sprooten, B. Robyns, “Integration of Renewable Energy in the European Power Grid: Market Mechanism for Congestion Management”, IEEE Transaction, Vol.978, pp.42-47, 2010.

Poonam B. Dhabai, Sunil Kumar Gupta, Neeraj Tiwari(2025), Minimization of Transmission Congestion Cost using P-OPF based LSF, PSO and ANN Techniques. IJEER 13(3), 596-601. DOI: 10.37391/IJEER.130325.