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ISSN: 2321-9653
Estd : 2013
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Ijraset Journal For Research in Applied Science and Engineering Technology

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Methodology for Assessment of Congestion Problem

Authors: Harshita Rajora, Mr. Sunil kumar Mahapatro, Dr. Parmod Sharma

DOI Link: https://doi.org/10.22214/ijraset.2022.47801

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Abstract

Due to increasing in load demand, blackout or unexpected failure in any component of power system including generator, transformer, transmission lines, lead to congestion and over loading in power system this leads the power system to reach on its verse of emergency state ,therefore there should be a proper management or control action for that condition. Several methods are there to control congestion management including Generator Rescheduling (GR),Nodal Pricing, Particle Swarm Optimizer(PSO),Genetic Algorithm (GA) ,Grey Wolf Optimizer (GWO),This paper presents proper congestion management based on Grey Wolf Optimizer (GWO) for reducing load shedding, improve voltage profile, voltage stability, active power loss, this shows optimal load shedding is effective control action for congestion management. The algorithm applied on IEEE 30 bus system considering (n-1) contingency.

Introduction

I. INTRODUCTION

The power industry in many countries is renewing and restructuring with replacement of old monolithic regulated public utilities with competitive markets [1]. In order to meet the increasing load demands around the world at affordable prices.This is the major reason of congestion in transmission lines of deregulated power systems [2] .

Congestion management techniques needed to performed immediately so congested system relieved .

There are many reasons in the technical literature for power system congestion that why congestion occurs in competitive market the congestion occurs in the system when the load demand increases beyond limit and the system unable to accommodate all required transaction due to violation of system operating limits [3] . congestion occurs when the power flow in the lines higher than the follow allowed by operating limits [4]  congestion occurs due to overloading transmission lines thermal bound and line capacities violated [5]. Physical parameters are also responsible for the congestion in the power system such as limitation of temperature, thermal limitation, voltage limitation in the node, voltage instability ,dynamic stability ,transient stability are some examples of limitation of physical system in congestion. Congestion occurs because of mismatching of generating and transmission services.It also cause due to unexpected events such as sudden rise in load demand ,generator outage, short circuit of circuit breaker or any equipment failure[7] Congestion in power system should be rectified soon in order to maintain power supply

Congestion also occurs due to regular damage of power system equipment this leads to system disturbance and further causes the outage in interconnected system  it also effects the power system quality to prevent in reduction of quality of power system the congestion system need to be corrected immediately [8]. Congestion management is the best method to restore the system into equilibrium state, it provides (1) improved efficiency of power system (2) reliable and secure operation of power system (3) effective power flow management (4) improve stability of system. There are various method of congestion management of  power system like optimal load shedding ,generation rescheduling, reactive power supply etc. Optimal load shedding is one of the best method  mentioned above ,in this method the the total amount of load required is reduced in order to maintain system stability it help in preventing blackout, voltage collapse, voltage instability. FACTS devices are also used to regulated and maintain the voltage supply during congestion. Elimination  and management of congestion in transmission lines by generation rescheduling or load shedding is determined by particle swarm optimization(PSO).congestion management by load shedding include thyristor controlled phase shifting transformer and thyristor controlled series compensator to prevent overloading and voltage instability in the system[9].improve harmony search algorithm used to maintain steady state voltage stability it also improves active power loss, instability, voltage collapse. This paper represents the Grey Wolf Optimizer technique for optimal load shedding for multiple and single objective function. This method is population based meta heuristics algorithm inspired from social headship and hunting approach of grey wolf .by following these approaches (1) reducing the value of load shedding (2) voltage deviation and improved voltage stability (3) reducing value of load shedding and power loss. Contingency analysis is done by using (n-1) .only one line is tripped and is selected by severity index and this shows the overloading of transmission lines. if the value of index is smaller the line are in working range otherwise it violates the rule [10]

II. CONTINGENCY ANALYSIS

Power system safety and security refers to capability of system to work within the safe limits when it follow all the rules and remain secure the system is not congested but when the defined limits of any power system violates the system enters into the emergency state and contingency state arises. It can be divided into two types [11]

Conclusion

This paper presents method for eliminating by optimal load shedding by GREY WOLF OPTIMIZATION(GWO) technique to maintain power system in stable, secure, and reliable state. Exact prediction against overloading is done by Severity index .Single line contingency can be obtained by tripping one line and this line is selected based on severity index. single and muti valued functions have been performed in this paper by using standard IEEE30 bus system. investigating by using grey wolf optimization it shows efficiency of optimization by reducing value of load shedding, by reducing active and reactive power losses, by reducing voltage deviation enhance voltage stability and make system more stable.

References

[1] Pillay, S. Prabhakar Karthikeyan, and D. P. Kothari, \"Congestion management in power systems – a review,\" International Journal of Electrical Power & Energy Systems, vol. 70, pp. 83-90, 2015. [2] V. K. Tumuluru and D. H. K. Tsang, \"A two-stage approach for network constrained unit commitment problem with demand response,\" IEEE Transactions on Smart Grid, pp. 1-9, 2016. [3] H.-M. Chung, C.-L. Su, and C.-K. Wen, \"Dispatch of generation and demand side response in regional grids,\" IEEE Transactions, pp. 1-5, 2015. [4] S. Nandini, P. Suganya, and K. M. Lakshmi, \"Congestion management in transmission lines considering demand response and facts devices,\" International Journal of Innovative Research in Science, Engineering and Technology, vol. 3(1), pp. 682-688, 2014 [5] M. Bachtiar Nappu and A. Arief. \"Network losses-based economic redispatch for optimal energy pricing in a congested power system,\" in 3rd International Conference on Power and Energy Systems Engineering (CPESE), Kitakyushu, Japan, 2016, pp. 1-4. [6] A. Yousefi, T. T. Nguyen, H. Zareipour, and O. P. Malik, \"Congestion management using demand response and facts devices,\"International Journal of Electrical Power & Energy Systems, vol. 37(1), pp. 78-85, 2012 [7] H. Emami and J. A. Sadri, \"Congestion management of transmission lines in the market environment,\" International Research Journal of Applied and Basic Sciences, vol. 3, pp. 2572-2580, 2012. [8] J. Hazra and A. K. Sinha, \"Congestion Management Using Multiobjective Particle Swarm Optimization,\" IEEE TRANSACTIONS ON POWER SYSTEMS PWRS, vol. 22, pp. 1726-1734, 2007. [9] P. Etingov, N. Voropai, A. Oudalov, A. Germond, and R. Cherkaoui, \"Congestion Management Using Coordinated Control of FACTS Devices and Load Shedding,\" in Proc. of 15th Power Systems Computation Conference (PSCC\'05), 2005, pp. 22-26. [10] R. M. Larik, M. Mustafa, S. Qazi, N. Mirjat, S. Shaikh, and A. Bhatti, Under Voltage Load Shedding Scheme to Provide Voltage Stability, 2016. [11] F. Sayed and S. Kamel, \"Optimal load shedding for voltage collapse prevention using improved harmony search algorithm,\" in Power Systems Conference (MEPCON), 2017 Nineteenth International Middle East, 2017, pp. 947-951. [12] H. I. Shaheen, G. I. Rashed, and S. Cheng, \"Optimal location and parameter setting of UPFC for enhancing power system security based on differential evolution algorithm,\" International Journal of Electrical Power & Energy Systems, vol. 33, pp. 94-105, 2011. [13] K. Sorooshian, \"Load flow and contingency analysis in power systems,\" 1984. [14] A. Samimi and P. Naderi, \"A new method for optimal placement of TCSC based on sensitivity analysis for congestion management,\" Smart Grid and Renewable Energy, vol. 3, p. 10, 2012. [15] M. Moazzami, M. J. Morshed, and A. Fekih, \"A new optimal unified power flow controller placement and load shedding coordination approach using the Hybrid Imperialist Competitive Algorithm-Pattern Search method for voltage collapse prevention in power system,\" International Journal of Electrical Power & Energy Systems, vol. 79, pp. 263-274, 2016. [16] D. Devaraj and J. P. Roselyn, \"Genetic algorithm based reactive power dispatch for voltage stability improvement,\" International Journal of Electrical Power & Energy Systems, vol. 32, pp. 1151- 1156, 2010. [17] O. Bozorg-Haddad, \"Advanced Optimization by Nature-Inspired Algorithms,\" 2018. [18] S. Mirjalili, S. M. Mirjalili, and A. Lewis, \"Grey wolf optimizer,\" Advances in engineering software, vol. 69, pp. 46-61, 2014.

Copyright

Copyright © 2022 Harshita Rajora, Mr. Sunil kumar Mahapatro, Dr. Parmod Sharma. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Authors : Harshita Rajora

Paper Id : IJRASET47801

Publish Date : 2022-11-30

ISSN : 2321-9653

Publisher Name : IJRASET

DOI Link : Click Here

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