通过定日镜最优瞄准策略用例演示SolarPILOT的Python API

William T. Hamilton, M. Wagner, Alexander J. Zolan
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引用次数: 2

摘要

SolarPILOT是一个软件包,可以生成太阳能场布局,并描述聚光太阳能(CSP)塔系统的光学性能。SolarPILOT是由国家可再生能源实验室(NREL)作为一个独立的桌面应用程序开发的,但也以简化的格式被纳入NREL的1系统顾问模型(SAM)。先前用户与SolarPILOT交互的方法包括应用程序的图形界面,具有有限可配置性的SAM例程,以及通过称为“LK”的内置脚本语言。本文为SolarPILOT提供了一个新的,全功能的,基于python的应用程序可编程接口(API),我们将其称为CoPylot。CoPylot提供访问SolarPILOT的所有功能,通过Python无缝地生成和表征电力塔CSP系统。支持的功能包括(i)使用消息报告工具创建和销毁模型实例;(ii)访问和设置任何SolarPILOT变量,包括用于现场布局的自定义陆地边界;(iii)为具有多个接收器或定日镜类型的系统,以程序方式管理具有不同属性的接收器和定日镜对象;(iv)生成、分配和修改太阳能场布局,包括设置单个定日镜位置、瞄准点、污染率和反射率水平的能力;(v)模拟太阳场性能;(vi)返回详细的结果,说明单个定日镜的性能、总视场和接收光通量分布;(vii)将基于python的模型实例导出为多种文件格式。CoPylot使Python用户能够使用Hermite扩展技术(分析)或SolTrace光线追踪引擎执行详细的CSP塔分析。除了CoPylot的功能,Python用户还可以访问超过100,000个开源库来开发,分析,优化和可视化电力塔CSP研究。这使得CSP研究人员能够执行以前无法通过SolarPILOT现有接口进行的分析。本文讨论了CoPylot的功能,并提出了一个用例,其中我们演示了最佳的太阳能场瞄准策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Demonstrating SolarPILOT’s Python API Through Heliostat Optimal Aimpoint Strategy Use Case
SolarPILOT is a software package that generates solar field layouts and characterizes the optical performance of concentrating solar power (CSP) tower systems. SolarPILOT was developed by the National Renewable Energy Laboratory (NREL) as a stand-alone desktop application but has also been incorporated into NREL’s1 System Advisor Model (SAM) in a simplified format. Prior means for user interaction with SolarPILOT have included the application’s graphical interface, the SAM routines with limited configurability, and through a built-in scripting language called “LK.” This paper presents a new, full-featured, Python-based application programmable interface (API) for SolarPILOT, which we hereafter refer to as CoPylot. CoPylot provides access to all SolarPILOT’s capabilities to generate and characterize power tower CSP systems seamlessly through Python. Supported capabilities include (i) creating and destroying a model instance with message reporting tools; (ii) accessing and setting any SolarPILOT variable including custom land boundaries for field layouts; (iii) programmatically managing receiver and heliostat objects with varied attributes for systems with multiple receiver or heliostat types; (iv) generating, assigning, and modifying solar field layouts including the ability to set individual heliostat locations, aimpoints, soiling rates, and reflectivity levels; (v) simulating solar field performance; (vi) returning detailed results describing performance of individual heliostats, the aggregate field, and receiver flux distribution; and, (vii) exporting Python-based model instances to multiple file formats. CoPylot enables Python users to perform detailed CSP tower analysis utilizing either the Hermite expansion technique (analytical) or the SolTrace ray-tracing engine. In addition to CoPylot’s functionality, Python users have access to the over 100,000 open-source libraries to develop, analyze, optimize, and visualize power tower CSP research. This enables CSP researchers to perform analysis that was previously not possible through SolarPILOT’s existing interfaces. This paper discusses the capabilities of CoPylot and presents a use case wherein we demonstrate optimal solar field aiming strategies.
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