放松管制环境下竞价策略中的粒子群优化

Naresh Kumar Yadav, Mukesh Kumar, D. Sharma, A. Bala, Gunjan Bhargava
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引用次数: 5

摘要

随着世界各地放松管制,电力行业正在引入结构调整和竞争。在竞争激烈的电力市场中,电力生产商面临着投标进入市场以最大化其预期利润的基本问题。一般采用双层竞价策略来实现利润最大化和市场出清功能最小化。在计算上,这是复杂的,因此,研究者采用Karush-Kuhn-Tucker (KKT)最优性条件将双层模型转化为单层最大化问题,但在包含传输约束后,问题变得更加复杂[1]。本文简化了不考虑KKT最优性条件下考虑ISO市场出清函数的问题。本文将传统的双层投标问题导出为单层策略模型。利用粒子群优化技术对该模型进行求解。在ieee14总线系统上进行了实验研究。
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Implementation of particle swarm optimization in bidding strategy under deregulated environment
Restructuring and competition are being introduced into the electric power industry as deregulation takes place throughout the world. In the competitive electricity markets, the electricity producers come across fundamental problems of bidding into the market to maximize their expected profits. Generally bi-level bidding strategy is used to maximize the profit and to minimize the market clearing function. Computationally, this is complex and hence, researchers have adopted Karush-Kuhn-Tucker (KKT) optimality conditions to transform bi-level model into a single level maximization problem but after inclusion of transmission constraints the problem has become more complex[1]. This paper simplifies the problem in which ISO market clearing functions are considered with no KKT optimality conditions. This paper derives traditional bi-level bidding problem into single level strategic model. This derived model is solved using Particle Swarm Optimization (PSO) technique. Experimental investigation is carried out on IEEE 14 bus system.
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