首页> 外文会议>International Universities' Power Engineering Conference >A Genetic Algorithm Based Economic Dispatch (GAED) with Environmental Constraint Optimisation
【24h】

A Genetic Algorithm Based Economic Dispatch (GAED) with Environmental Constraint Optimisation

机译:基于遗传算法的环境约束优化的经济派遣(GAED)

获取原文

摘要

The role of renewable energy in power systems is becoming more significant due to the increasing cost of fossil fuels and climate change concerns. However, the inclusion of Renewable Energy Generators (REG), such as wind power, has created additional problems for power system operators due to the variability and lower predictability of output of most REGs, with the Economic Dispatch (ED) problem being particularly difficult to resolve. In previous papers we had reported on the inclusion of wind power in the ED calculations. The simulation had been performed using a system model with wind power as an intermittent source, and the results of the simulation have been compared to that of the Direct Search Method (DSM) for similar cases. In this paper we report on our continuing investigations into using Genetic Algorithms (GA) for ED for an independent power system with a significant amount of wind energy in its generator portfolio. The results demonstrate, in line with previous reports in the literature, the effectiveness of GA when measured against a benchmark technique such as DSM.
机译:由于化石燃料和气候变化的增加,可再生能源在动力系统中的作用变得越来越重要。然而,由于大多数regs的输出的可变性和降低的可预测性,包括可再生能源发生器(例如风电)为电力系统运营商的额外问题产生了额外的问题,并且经济调度(ED)问题特别难以解决。在之前的论文中,我们报告了在ED计算中包含风力。使用具有风电作为间歇源的系统模型进行了模拟,并且已经将模拟结果与直接搜索方法(DSM)进行了相似的类似情况。在本文中,我们报告了我们在发电机组合中使用大量风能的独立电力系统进行遗传算法(GA)对遗传算法(GA)。结果表明,符合先前的文献中的报告,当诸如DSM等基准技术测量时GA的有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号