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Conservation of declining population focuses on ways of detecting, diagnosing, and halting a population decline. The approach uses methods to prevent populations from going extinct.
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Small population sizes put a species at extreme risk of extinction due to a lack of variation, and a consequent decrease in adaptability. This weakens the chances of survival under pressures such as climate change, competition from other species, or new diseases. Large populations are more likely to survive pressures such as these, as such populations are more likely to harbor individuals that have genetic variants that are adaptive under new stresses. Small populations are much less...
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A population is composed of members of the same species that simultaneously live and interact in the same area. When individuals in a population breed, they pass down their genes to their offspring. Many of these genes are polymorphic, meaning that they occur in multiple variants. Such variations of a gene are referred to as alleles. The collective set of all the alleles within a population is known as the gene pool.
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可再生分布式发电机和电动汽车的最佳放置使用多种群进化鱼优化算法.

Rinchen Zangmo1, Suresh Kumar Sudabattula1, Sachin Mishra2

  • 1School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, 144411, Punjab, India.

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概括

可再生分布式发电机 (RDG) 的最佳放置,包括太阳能光伏,风力轮机和电动汽车 (EV),在辐射分布系统 (RDS) 中最大限度地减少电力损耗并提高电网稳定性. 多种群进化优化算法 (MEWOA) 证明了对这些复杂的优化任务的有效性.

关键词:
分布式发电机组 分布式发电机组电动汽车 电动汽车是什么电力损失 电力损失电压配置文件 电压配置文件电压稳定性指数 电压稳定性指数鱼优化算法 鱼优化算法

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科学领域:

  • 电气工程 电气工程
  • 电力系统工程 电力系统工程
  • 整合可再生能源的整合

背景情况:

  • 辐射配电系统 (RDS) 面临着电源损耗和电压稳定的挑战.
  • 整合可再生分布式发电机 (RDGs),如太阳能光伏和风力轮机,与电动汽车 (EV) 一起,提供了显著的好处,但需要战略定位.
  • 负载需求的不确定性增加了电网管理的复杂性.

研究的目的:

  • 确定 RDGs (太阳能光伏,风力轮机) 和电动汽车在RDS中的最佳位置.
  • 为了最大限度地减少功率损失 (PLoss),并改善电压配置和稳定性指数.
  • 评估负载需求不确定性对R & DG整合的影响.

主要方法:

  • 利用Beta和Weibull分布函数来建模太阳辐射和风速.
  • 采用元启发式算法来整合EV和优化RDG的放置.
  • 在印度的28个总线测试系统上测试了拟议的方法,该系统代表了一个平衡的RDS.
  • 集成的负载需求不确定性用于24小时分析.

主要成果:

  • 总局的整合大大减少了功耗损失 (PLoss),提高了系统效率.
  • 在GD集成后,观察到增强的电压配置和改善的电网稳定性.
  • 与现有方法相比,多种群进化鱼优化算法 (MEWOA) 显示出更高的性能.
  • 该研究证实了MEWOA在电力系统的非线性优化中的实际价值.

结论:

  • 优化RDG和EV的配置对于提高RDS性能至关重要.
  • MEWOA是一种高效和实用的算法,用于优化RDS中的RDG和EV集成.
  • 总局集成导致减少电力损耗,提高效率,改善环境可持续性.