Available transfer capacity evaluation through evolutionary algorithms

Kingsuk Majumdar, P. Roy, Subrata Baneijee
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引用次数: 2

Abstract

In deregulated environment (DE), available transfer capacity (ATC) calculation is a crucial matter in the power system operation and it is a key in view of trade of electricity. In this paper, it is emphasized to the calculation of ATC with the help of optimal power flow (OPF) method along with different soft computational techniques viz. particle swarm optimization (PSO) and biogeography-based optimization (BBO). The ATC is the deciding factor on the base of the effect of transaction on transmission to allow or disallow bilateral transmission transection. The OPF has many objectives in DE with open market situation and these calculations aid to independent system operator (ISO), to handle the congestion threat over transmission lines and assure security and reliability. The two methods of soft computing i.e. PSO and BBO have been adopted to figure out the aforesaid criteria in ATC calculation through OPF, a corrective technique, which hints new generation schedule to resist congestion and gives clues to tune the controlled parameters (e.g. tap setting, reactive power injection etc) to avoid the violation of power system constrains (bus voltage limit and reactive power injection limit etc. In this paper, PSO is implemented to evaluate ATC then BBO for the same. The proposed methods are tested on IEEE 30 bus test system and their results are compared and is it observed that BBO results is better than that of PSO.
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基于进化算法的可用传输容量评估
在解除管制的环境下,有效输电容量的计算是电力系统运行的关键问题,也是电力交易的关键。本文重点介绍了利用最优潮流(OPF)方法,结合粒子群优化(PSO)和基于生物地理的优化(BBO)等软计算技术,对ATC进行计算。ATC是基于交易对传输的影响来决定是否允许双边传输横断的决定因素。OPF在开放市场环境下有许多目标,这些计算有助于独立系统运营商(ISO)处理传输线上的拥塞威胁,确保安全性和可靠性。在ATC计算中,采用PSO和BBO两种软计算方法,通过OPF这一纠偏技术,对上述准则进行求解。OPF提示新一代调度以抵抗拥塞,并提示调整被控参数(如分接设置、无功功率注入等)以避免违反电力系统约束(母线限压、无功功率注入等)。本文采用粒子群算法对ATC和BBO进行评估。在ieee30总线测试系统上对所提出的方法进行了测试,并对其结果进行了比较,发现BBO的测试结果优于PSO。
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