水力发电站调度与船只到达预测和能源储存
Enjiang Zhou1, Xiao Liu1, Zhihang Meng2,3
1Guizhou Wujiang River Navigation Authority, Tongren, 565100, China.
Scientific reports
|November 4, 2023
概括
本研究介绍了水力发电站的实时调度模型,集成能源储存和船舶抵达预测,以增强发电和导航. 优化的模型平衡了电网负载需求与改进的航行性,证明了水电运营的实际好处.
科学领域:
- 工程 工程师 工程师 工程师
- 优化优化 优化优化
- 可再生能源系统可再生能源系统
背景情况:
- 连接到电网的水电站面临着不稳定的发电和不准确的船只到达时间的挑战.
- 这些问题影响了电力供应和导航的整体效率和可靠性.
研究的目的:
- 为水电站提出一个多目标实时调度模型.
- 通过集成的能源存储和船舶抵达预测,提高发电稳定性和航行保证.
主要方法:
- 开发了一种多目标实时调度模型,包括储能和预测船只到达.
- 使用了非主导排序白优化 (NSBWO) 算法,结合了NSGA-II和BWO.
- 采用XGBoost来准确预测船只到达时间.
主要成果:
- 该NSBWO算法有效优化了实时排放流程调度.
- XGBoost 模型实现了超过 0.9.9 的船舶抵达时间预测准确度.
- 该调度模型成功地满足了电网负载需求,同时改善了导航效益.
结论:
- 拟议的模型在预测船只到达时间和优化水电排放流量方面提供了显著的优势.
- 这种方法为现实世界水电计划问题提供了实际的解决方案,平衡能源和导航目标.
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