开发和实施一个模型预测控制系统的太阳能抛物线槽工厂受先进的气象干扰模型的影响
K Kalanithi1, G Giftson Samuel2, M Malathi3
1Department of Biomedical Engineering, E.G.S. Pillay Engineering College, Nagapattinam, Tamil Nadu, 611002, India. kalanithi@egspec.org.
Scientific reports
|October 21, 2025
概括
模型预测控制有效地管理太阳能热系统,在调节温度和最小化干扰方面表现优于其他方法. 这种先进的控制确保了稳定和高效的太阳能发电,以确保国家安全.
科学领域:
- 可再生能源系统可再生能源系统
- 控制工程 控制工程 控制工程
- 热力工程是热力工程中的一个.
背景情况:
- 太阳能对于印度到2030年实现500吉瓦非化石燃料发电目标至关重要.
- 太阳能集成的关键在于抛物线集器,表现出非线性行为,需要先进的控制.
- 天气干扰会影响太阳能热收集器的性能,需要强大的控制策略.
研究的目的:
- 开发和评估一个天气干扰模型,用于抛物线集器.
- 为了比较三个先进的控制方案的有效性:模型预测控制 (MPC),预测功能控制 (PFC) 和比例整体导数 (PID).
- 为稳定和高效的太阳能热系统运行确定最佳控制策略.
主要方法:
- 使用印度泰米尔纳德邦的当地数据开发基于国家空间的天气干扰模型.
- 在模拟天气干扰下实施和评估MPC,PFC和PID控制方案.
- 分析关键性能指标,包括出口温度调节,峰值超标,结算时间和跟踪精度.
主要成果:
- 模型预测控制 (MPC) 展示了卓越的性能,将峰值温度超标限制在6.67%,并实现3600s的沉降时间.
- 预测功能控制 (PFC) 导致25%的超标,而比例-整数-导数 (PID) 控制显示43.33%的超标.
- 与其他方法相比,状态空间天气干扰模型提供了更准确的设置值跟踪,MPC提供了干扰拒绝和稳定性的最佳平衡.
结论:
- 模型预测控制 (MPC) 是最有效的策略,用于调节在天气干扰下抛物线低谷集热器出口温度.
- 与PFC和PID控制相比,MPC确保了稳定的稳定性和优异的干扰排斥.
- 像MPC这样的先进控制方法对于提高太阳能热发电的可靠性和效率至关重要.
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