首页> 外文会议>International Conference on Intelligent Green Building and Smart Grid >Reliability evaluation of generation system with micro-grid based on glowworm swarm optimization
【24h】

Reliability evaluation of generation system with micro-grid based on glowworm swarm optimization

机译:基于萤火虫群优化的微网发电系统可靠性评估

获取原文

摘要

Because of emissions of carbon dioxide from consumption of fossil fuels and consideration of the security of energy supply, renewable energy sources such as wind power generation and solar power generation have increased significantly in recent years and are expected to play more important role in electric power system in the near future. However, their drawbacks such as intermittence and unpredictable variability are likely to result in negative effects on the reliability of the power system. This study proposed a hybrid power generation system (HPGS) composed of wind power generation and solar power generation systems and established its model based on Monte Carlo sampling. In order to demonstrate the reliability promotion resulted from the HPGS, with introduction of Glowworm Swarm Optimization (GSO) algorithm, indices including loss of load expectation, loss of energy expectation, and loss of load probability of the micro grid are evaluated. Simulation results based on proposed method indicated that the proposed HPGS can effectively improve the adequacy of the micro grid. Compared with the results that generated by sequential Monte Carlo, the GSO algorithm outperforms with less computation time and higher convergence accuracy.
机译:由于消耗化石燃料会排放二氧化碳,并考虑到能源供应的安全性,近年来,风力发电和太阳能发电等可再生能源显着增加,并有望在电力系统中发挥更重要的作用。在不远的将来。但是,它们的诸如间歇性和不可预测的可变性之类的缺点可能会对电力系统的可靠性造成负面影响。本研究提出了一种由风力发电和太阳能发电系统组成的混合发电系统(HPGS),并建立了基于蒙特卡洛采样的混合发电系统模型。为了证明HPGS带来的可靠性提升,通过引入萤火虫群优化(GSO)算法,评估了包括预期负荷损失,预期能量损失和微电网负荷概率在内的指标。基于所提出方法的仿真结果表明,所提出的HPGS可以有效地提高微电网的适用性。与顺序蒙特卡洛方法生成的结果相比,GSO算法的性能要好于更少的计算时间和更高的收敛精度。

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