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Supervised by Ministry of Industry and Information Technology of The People's Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

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Related citation:Gagandeep Kaur,Akhil Gupta.Estimating Optimal Location of STATCOM and Minimization of Congestion Cost by Locational Marginal Price Using FlowerPollination and Particle Swarm Optimization Techniques[J].Journal of Harbin Institute Of Technology(New Series),2025,32(1):67-75.DOI:10.11916/j.issn.1005-9113.2023125.
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Estimating Optimal Location of STATCOM and Minimization of Congestion Cost by Locational Marginal Price Using FlowerPollination and Particle Swarm Optimization Techniques
Author NameAffiliation
Gagandeep Kaur Electrical Engineering Department, M.R.Singh Punjab Technical University, Bathinda 151001, Punjab, India 
Akhil Gupta Electrical Engineering Department, I.K.Gujral Punjab Technical University Main Campus, Kapurthala 144603, Punjab, India 
Abstract:
Restructuring of power market not only introduces competition but also brings complexity which increases overloading of Transmission Lines (TL). To obviate this complexity, this paper aims to mitigate the overloading and estimate the optimal location of Static Synchronous Compensator (STATCOM) by reducing congestion for a deregulated power system. The proposed method is based on the use of Locational Marginal Price (LMP) difference technique and congestion cost. LMPs are obtained as a by-product of Optimal Power Flow (OPF), whereas Congestion Cost (CC) is a function of difference in LMP and power flows. The effiectiveness of this approach is demonstrated by reducing the CC and solution space which can identify the TLs more suitable for placement of STATCOM. Importantly, total real power loss, reactive power loss and total CC are the three main objective functions in this optimization process. The process is implemented by developing an IEEE-69 bus test system which verifies and validates the effectiveness of proposed optimization technique. Additionally, a comparative analysis is enumerated by implementing two optimization techniques: Flower Pollination Algorithm (FPA) and Particle Swarm Optimization (PSO). The comparative analysis is sufficient to demonstrate the superiority of FPA technique over PSO technique in estimating an optimal placement of a STATCOM. The results from the load-flow analysis illustrate the reduction in CC, total real and reactive power loss using FPA technique compared to PSO technique. Overall, satisfactory results are obtained without using complex calculations which verify the effectiveness of optimization techniques.
Key words:  congestion management  congestion cost  optimal power  particle swarm  flower pollination  optimization
DOI:10.11916/j.issn.1005-9113.2023125
Clc Number:TM73
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