使用AC/DC微电网中的模型预测控制来模拟能源管理系统
Kawsar Nassereddine1, Marek Turzynski2, Halyna Bielokha3
1Faculty of Electrical and Control Engineering, Gdansk University of Technology, Gdansk, Poland. nassereddinejana@gmail.com.
Scientific reports
|February 13, 2025
概括
准确的可再生能源预测和战略减负是高效的微电网能源管理系统 (EMS) 的关键. 优化缩减时间表可以改善混合能源存储,减少对电网的依赖.
科学领域:
- 电气工程 电气工程
- 可再生能源系统可再生能源系统
- 能源管理 能源管理
背景情况:
- 微电网需要高效的能源管理系统 (EMS) 来实现稳定性和成本效益.
- 准确的可再生能源预测和负载管理对于集成太阳能等间歇性能源至关重要.
- 混合储能系统 (电池和超级电容器) 是现代微电网的重要组成部分.
研究的目的:
- 研究可再生能源预测准确度对微电网内减负策略的影响.
- 为了比较不同减负计划的有效性,以管理可再生能源产量的峰值.
- 分析预测和限制对混合动力储能系统性能和整体能源成本的影响.
主要方法:
- 分析不同时间地平线 (即时,一小时,几小时前) 的干扰预测的精度.
- 比较两个减负策略:案例1 (早上和下午的减负) 和案例2 (中午的减负).
- 在不同的场景下评估混合储能系统 (电池和超级电容器) 的性能.
主要成果:
- 提前一小时预测可再生能源发电比立即或长期预测更有效.
- 案例1 (早上和下午的缩减) 有效地使负载管理与峰值光伏 (PV) 能源生产保持一致,减少了对电网的依赖.
- 案例2 (中午缩减) 导致电网能源采购增加,未能利用太阳能能源的可用性.
- 准确的预测与Case 1相结合,改善了电池协调,减少了超级电容器压力,并降低了电网能源购买.
结论:
- 精确的可再生能源预测对于优化微电网负载减轻策略至关重要.
- 战略负载调度,特别是案例1,显著提高能源效率,减少对外部电网电力的依赖.
- 准确的预测和有效的负载管理之间的协同作用优化了混合能源存储,降低了成本,并提高了微电网的可靠性.
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