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Solution of wind integrated thermal generation system for environmental optimal power flow using hybrid algorithm

机译:基于混合算法的风能热发电系统环境最优潮流解决方案

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A new evolutionary hybrid algorithm (HA) has been proposed in this work for environmental optimal power flow (EOPF) problem. The EOPF problem has been formulated in a nonlinear constrained multi objective optimization framework. Considering the intermittency of available wind power a cost model of the wind and thermal generation system is developed. Suitably formed objective function considering the operational cost, cost of emission, real power loss and cost of installation of FACTS devices for maintaining a stable voltage in the system has been optimized with HA and compared with particle swarm optimization algorithm (PSOA) to prove its effectiveness. All the simulations are carried out in MATLAB/SIMULINK environment taking IEEE30 bus as the test system.
机译:针对环境最优潮流(EOPF)问题,本文提出了一种新的进化混合算法(HA)。 EOPF问题已在非线性约束的多目标优化框架中提出。考虑到可用风力的间歇性,开发了风力发电系统的成本模型。考虑到运行成本,发射成本,实际功率损耗和FACTS装置的安装成本以保持系统中的稳定电压,已适当地形成目标函数,并使用HA对其进行了优化,并与粒子群优化算法(PSOA)进行了比较,以证明其有效性。所有的仿真都是在MATLAB / SIMULINK环境下进行的,以IEEE30总线为测试系统。

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