Estimating Optimal Location of STATCOM and Minimization of Congestion Cost by Locational Marginal Price Using Flower Pollination and Particle Swarm Optimization Techniques  

作　　者：Gagandeep Kaur Akhil Gupta 

机构地区：[1]Electrical Engineering Department,M.R.Singh Punjab Technical University,Bathinda 151001,Punjab,India [2]Electrical Engineering Department,I.K.Gujral Punjab Technical University Main Campus,Kapurthala 144603,Punjab,India

出　　处：《Journal of Harbin Institute of Technology(New Series)》2025年第1期67-75,共9页哈尔滨工业大学学报(英文版)

摘　　要：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.

关 键 词：congestion management congestion cost optimal power particle swarm flower pollination optimization 

分 类 号：TM73[电气工程—电力系统及自动化]