Clustering Based Optimization and Automation of Utility Scale Solar Site Design

K. Rhee
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Abstract

EDFR has developed a series of methods for quickly drafting a set of utility scale photovoltaic plant layouts and choosing an optimized plant design from that set. The automated drafting methodology utilizes a standard clustering technique and a novel cluster equalizing post-processing algorithm to solve a problem in existing automated drafting software, which is that existing techniques cannot assign dc power in the form of trackers to inverters without human intervention. This step is crucial to create end to end automation of a PV plant layout. Without it, it is impossible to accurately determine the layout of dc wiring and associated electrical equipment. The work nearly eliminates the need for developer drafting of utility scale photovoltaic plant layouts and provides a foundation for reducing levelized cost of energy by allowing EDFR to select the most financially optimal project design without investing large amounts of time creating the feasibility space under which optimization can occur. (Abstract)
基于聚类的公用事业规模太阳能站点设计优化与自动化
EDFR开发了一系列快速起草一套公用事业规模光伏电站布局并从中选择优化的电站设计的方法。自动绘图方法利用标准的聚类技术和一种新颖的聚类均衡后处理算法,解决了现有自动绘图软件中存在的一个问题,即现有技术无法在没有人为干预的情况下以跟踪器的形式将直流功率分配给逆变器。这一步对于创建光伏电站布局的端到端自动化至关重要。没有它,就不可能准确地确定直流布线和相关电气设备的布局。这项工作几乎消除了开发商起草公用事业规模光伏电站布局的需要,并为EDFR选择最经济最优的项目设计提供了基础,而无需投入大量时间来创建优化的可行性空间。(抽象)
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