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Combined Economic Emission Dispatch based Transmission congestion management under deregulated electricity market

机译:电力市场管制下基于组合经济排放调度的输电拥堵管理

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This paper proposes an optimal congestion management approach in a deregulated electricity market using Particle swarm optimization (PSO) under Combined Economic and Emission dispatch (CEED) environment. CEED problem has been formulated as a multi-objective problem by considering both economy and emission simultaneously. This bi-objective CEED problem is converted into single objective function using price penalty factor approach. The aim of the proposed work is to minimize deviations from preferred transaction schedules and hence the congestion cost. Generator reactive power support is considered to lower the congestion cost. The values of Transmission Congestion Distribution factors (TCDFs) are used to select redispatch of generators. Numerical results on test systems namely IEEE 30 Bus and IEEE 118 bus systems are presented for illustration purpose and the results are compared with Economic Load Dispatch (ELD) and Economic Emission Dispatch (EED). The comprehensive experimental results prove that the PSO is one among the challenging optimization methods which is indeed capable of obtaining higher quality solutions for the proposed problem.
机译:本文提出了在经济与排放调度(CEED)相结合的环境下,采用粒子群算法(PSO)的电力市场放松管制的最优拥塞管理方法。通过同时考虑经济和排放,CEED问题已被表述为多目标问题。使用价格惩罚因子方法将此双目标CEED问题转换为单目标函数。拟议工作的目的是最大程度地减少与首选交易时间表的偏离,从而减少拥塞成本。发电机无功功率支持被认为可以降低拥塞成本。传输拥塞分布因子(TCDF)的值用于选择发电机的重新分配。出于说明目的,给出了在测试系统(即IEEE 30总线和IEEE 118总线系统)上的数值结果,并将结果与​​经济负荷调度(ELD)和经济排放调度(EED)进行了比较。综合的实验结果证明,粒子群优化算法是具有挑战性的优化方法之一,它确实能够为提出的问题获得更高质量的解决方案。

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