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在COVID-19流行病下,基于风险共享的弹性可再生能源供应网络模型
Yu-Chung Tsao1,2,3,4, Vo-Van Thanh1,2, Jye-Chyi Lu5
1Department of Industrial Management, National Taiwan University of Science and Technology, Taipei, Taiwan.
概括
随着COVID-19大流行,可再生能源供应网络面临挑战. 这项研究设计了一个使用强大的模糊-随机模型的弹性网络,增强了对抗流行病风险的利和稳定性.
科学领域:
- 能源系统工程 能源系统工程
- 运营研究 运营研究
- 环境经济学环境经济学
背景情况:
- 随着COVID-19大流行,可再生能源项目受到干扰,影响了技术和金融供应链.
- 封锁导致需求下降,降低现有发电厂的效率.
- 这些干扰对可再生能源供应网络的弹性构成重大挑战.
研究的目的:
- 设计一个具有弹性可再生能源供应网络,考虑COVID-19大流行所带来的供应,需求和支付风险.
- 优化电力发电和储存,以及风险分享指数,以最大限度地提高工厂利.
- 确定最佳的价格调整以最大限度地降低消费者成本,并采用基于政府补贴的风险共享模式.
主要方法:
- 开发一个强大的模糊-随机编程模型来处理来自随机和风险事件的不确定性.
- 基于政府补贴的风险共享模式的设计,以加强在疫情期间的网络弹性.
- 在越南的可再生能源供应网络上进行的计算实验.
主要成果:
- 具有风险共享模式的弹性能源供应网络在各种COVID-19影响水平上显示稳定的总利.
- 提出的模型有效地管理了随机事件和危险事件的不确定性.
- 与强大的优化相比,该模型实现了更高的利和更短的计算时间.
结论:
- 具有弹性可再生能源供应网络设计对于减轻与流行病相关的风险至关重要.
- 强大的模糊-随机编程模型与风险共享机制增强了网络稳定性和利能力.
- 政府补贴可以在提高可再生能源基础设施的弹性方面发挥关键作用.
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