使用分布式传感器进行超短期光伏电力预测的联合持久性和物理方法
Yakov Malinkovich1, Moshe Sitbon1, Simon Lineykin2
1Department of Electrical Engineering and Electronics, Ariel University, Ariel 40700, Israel.
Sensors (Basel, Switzerland)
|May 11, 2024
概括
这项研究引入了一种用于预测云层覆盖的新方法.
科学领域:
- 可再生能源系统可再生能源系统
- 电网的稳定性 电网的稳定性
- 气象预报 气象预报
背景情况:
- 对光伏 (PV) 输出功率的准确预测对于电网稳定性至关重要.
- 云层覆盖对光伏发电产生有重大影响,需要先进的预测模型.
- 整合储能系统 (ESS) 可以减轻可再生能源中间歇性问题.
研究的目的:
- 开发一种新的方法,用于现在预测云层对光伏场的影响.
- 与国家电网相比,模拟和评估具有光伏和ESS的电力网络的行为.
- 通过相当的PV + ESS模块模型来优化计算效率.
主要方法:
- 在物理和持久模型的组合中,利用光伏电池板作为传感器.
- 为PV + ESS模块开发一个相当的模型,以模拟不同天气条件下的系统行为.
- 实施一个控制系统与PID控制器全面ESS管理和网络动态响应.
主要成果:
- 拟议的预测方法,将物理和持久性模型与ESS集成相结合,在管理电网稳定性方面表现出有效性.
- 相当于PV + ESS模块准确模拟系统行为,考虑到诸如云层覆盖等天气条件.
- 模拟显示了与国家电网相比,各种场景对电网稳定性的影响.
结论:
- 集成ESS和新的预测方法为提高电网稳定性提供了一个有希望的解决方案.
- 开发的方法可以适应与太阳能围等系统的集成,突出其创新潜力.
- 精确的电力预测对于电力连续性,管理坡道速率和确保整体电网稳定性至关重要.
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