多目标最佳功率流量解决方案使用非主导排序碰撞物体优化优化
Harish Pulluri1, Kambhampati Venkata Govardhan Rao2, Cholleti Sriram3
1Department of Electrical and Electronics Engineering, Anurag University, Hyderabad, 500088, Telangana, India.
Scientific reports
|November 4, 2024
概括
一种新的非主导排序碰撞物体优化 (NSCBO) 方法有效地解决了电网中的多目标最佳功率流量问题. 它产生多样化,非主导的解决方案,以改善电力系统的优化.
科学领域:
- 电气工程 电气工程
- 优化理论 优化理论
- 计算智能是一种计算智能.
背景情况:
- 多目标最佳功率流量 (MOOPF) 问题对于高效的电力网络运行至关重要.
- 现有的优化技术往往难以为复杂的MOOPF挑战生成多样化的非主导解决方案.
研究的目的:
- 为MOOPF问题引入一种创新的非主导排序碰撞物体优化 (NSCBO) 技术.
- 加强各种非主导解决方案的生成,并改进选择过程.
主要方法:
- 在NSCBO方法包括非主导分类和拥挤距离的解决方案多样性.
- 碰撞的身体质量是由非主导级别决定的,而不是客观的函数值.
- 使用模糊决策策略从非主导集合中选择最终解决方案.
主要成果:
- 在一次代中,NSCBO技术成功地生成了一组多样化的非主导解决方案.
- 在IEEE 30-bus系统 (双和三目标模型) 上的实验证明了可扩展性和可行性.
- 对比分析证实了NSCBO在处理约束和获得最佳解决方案方面的有效性.
结论:
- 拟议的NSCBO方法是解决复杂的MOOPF问题的有效和高效方法.
- NSCBO提供了一个强大的框架,可以在电力系统中实现解决方案多样性和计算效率之间的平衡.
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