综合能源系统在多重稳定性条件下的双层优化模型
1School of Economics and Management, Shanghai University of Electric Power, Shanghai, China.
PloS one
|September 26, 2023
概括
优化可再生能源系统可以降低成本,提高效率,尽管输出变化. 强大的双层编程和火虫算法解决了分布式能量输出和负载的不确定性.
科学领域:
- 可再生能源系统可再生能源系统
- 优化理论 优化理论
- 能源经济学 能源经济学
背景情况:
- 可再生能源的整合受到输出不稳定性和随机性的阻碍.
- 综合能源系统提高了效率,但面临着间歇性能源的挑战.
- 分布式能源输出和负载的不确定性会影响系统的可靠性和成本.
研究的目的:
- 为全面的能源系统开发一个强大的优化模型.
- 解决分布式可再生能源输出和负载的不确定性.
- 尽量减少系统运营成本,同时确保可靠性.
主要方法:
- 制定一个包含强度的双层编程优化模型.
- 利用火虫算法来解决复杂的优化问题.
- 在不同分布式风力发电输出间隔下分析系统性能.
主要成果:
- 优化不确定性大大降低了实际系统运营成本,最大降低14.43%.
- 在特定的分布式风力发电输出范围 ([0,190]) 中,成本和消耗率之间的动态平衡是可以实现的.
- 拟议的模型证明了强大的优化在管理可再生能源整合方面的有效性.
结论:
- 强大的优化是减轻可再生能源不确定性的经济影响的可行策略.
- 火算法为复杂的综合能源系统优化问题提供了有效的解决方案.
- 实现成本和消费之间的平衡对于成功大规模部署可再生能源至关重要.
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