SBIR Phase I: Intelligent Monitoring and Control of Revenue-Critical PV Power Plants

SBIR 第一阶段：对收入至关重要的光伏电站的智能监控

• 批准号: 1014404
• 负责人: Shahar Ben-Menahem
• 金额: $ 14.98万
• 依托单位: Wattminder - Yang Associates
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-01 至 2010-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1014404&HistoricalAwards=false
• 关键词: SBIR; Phase; Intelligent; Monitoring; Control

This Small Business Innovation Research Phase I project seeks to develop new methods and algorithms for the analysis and control of degradations in Photovoltaic (PV) systems. There currently exists widespread, and often undetected, underperformance in PV arrays. Although there are numerous site evaluation and analysis tools used in the design phase of solar cell installations, there is currently a lack of on-line monitoring and diagnostic tools to detect and estimate underperformance and associated control algorithms that can improve performance. Underperforming PV cells can result from a host of inter-related abnormalities including shading, dust build up, hot spots and component failures. To improve performance intelligent control can be used to ameliorate power output degradation via actuation at the module- or module-string-level operating points. The purpose of this proposal is to develop, and test in simulation, a hybrid MAP-MPPT estimation and control algorithm, capable of intelligently modulating the operating point to maximize The broader impact/commercial potential of this project include the enhancement of performance of large scale PV arrays and the ability to better estimate the energy payback time for commercial and residential PV systems enabling further deployment of PV worldwide. Leading revenue-critical, PV power plant owner-operators often utilize dedicated operation centers to monitor walls of computer screens, sometimes with alarm mechanisms triggered by inverters. It is often the case that ad-hoc methods are utilized and decisions are based primarily on operator experience and intuition. Although some sites utilize commercial web-based monitoring services, with industrial grade sensors, this process is far from rigorous, and has resulted in only spotty success. Furthermore, the lack of intelligently controlling the operating point has not yet been fully developed. The proposed solution, used in conjunction with the ability to monitor the state of the PV plant, will correct faults via intelligent control methods enabling optimal power production under degradations for large scale PV arrays. Potential customers are revenue critical solar power sites including: Power Purchase Agreement (PPA) contractors, and lease-holder hosts.

这个小企业创新研究第一阶段项目旨在开发新的方法和算法，用于分析和控制光伏（PV）系统的退化。 目前存在着广泛的，往往未被发现的，在光伏阵列的性能不佳。 尽管在太阳能电池装置的设计阶段使用了许多现场评估和分析工具，但目前缺乏在线监测和诊断工具来检测和估计性能不佳以及可以提高性能的相关控制算法。 表现不佳的光伏电池可能是由一系列相互关联的异常导致的，包括阴影、灰尘积聚、热点和组件故障。 为了提高性能，可以使用智能控制来通过在模块或模块串级操作点处的致动来改善功率输出降级。 该提案的目的是开发并在模拟中测试混合MAP-MPPT估计和控制算法，该算法能够智能地调节操作点以最大化该项目的更广泛的影响/商业潜力包括增强大规模光伏阵列的性能以及更好地估计商业和住宅光伏系统的能量回收时间的能力，从而能够在全球范围内进一步部署光伏。 领先的收入关键型光伏电站业主运营商通常利用专用的运营中心来监控计算机屏幕，有时还使用逆变器触发的报警机制。经常采用特别方法，主要根据操作员的经验和直觉作出决定。 虽然有些网站使用基于网络的商业监控服务，使用工业级传感器，但这一过程远非严格，而且只取得了零星的成功。 此外，智能控制工作点的不足尚未得到充分开发。 所提出的解决方案与监测光伏电站状态的能力结合使用，将通过智能控制方法纠正故障，从而在大规模光伏阵列降级的情况下实现最佳发电。 潜在客户是对收入至关重要的太阳能发电站，包括：购电协议（PPA）承包商和承租人主机。