As the first PV power station performance assessment application in China, Ensight Solar leverages multiple high-precision machine learning algorithms to achieve authentic intelligent operation of power stations. The application is designed with the latest achievements of Apollo Solar Silicon Valley Innovation Center.
This application automatically calculates the key performance indexes (KPIs) of PV power stations, breaks down their power generation loss in details, and automatically reports these KPIs to asset managers, O&M teams, and insurance underwriters. The application converts insights into actions by providing prioritized O&M suggestions against poor system performance and component health issues, which helps users to increase power station revenue and organize and arrange O&M more effectively and economically, thereby ensuring the long-term persistence and reliability of PV power station assets.
Provides fine-grained analysis of power generation loss reasons to to help achieve precise O&M:
∙ Provides dust, misfit, and attenuation analysis to enhance power generation productivity.
∙ Provides peak clipping and shadow analysis, leverages technical transformation to maximize ROI.
∙ Provides line loss and box transformer loss analysis to optimize power station design.
Automatic Data Cleansing
Controls data quality from their origin for reliable data and trusted results. As the first data quality inspection application in the industry, it can automatically diagnose data quality, perform multi-level data filtering, and identify exceptions for the best results.
∙ Provides regional dust impact analysis and intelligent recommendation of optimal cleaning schemes to maximize ROI.
∙ Automatically analyze the dust accumulation rates of multiple regions, comprehensively determine the loss resulted from dust and calculate the component cleansing cost, generate optimal cleansing policies by region and therefore maximize ROI.
Identifies the impacts of various types of shadows and assesses power generation loss dynamically
∙ Provides dynamic estimation of due power generation loss based on innovative model .
∙ Identifies different types of shadows with exclusive shadow detection algorithms, including vegetation shadows, between-the-lines shadows, and foreign object shielding shadows.
Supports root cause mining, discloses causes of outages, and diagnoses O&M quality analysis.
∙ Compares and analyzes converter outage loss, quickly identifies failure converters.
∙ Performs outage time analysis and provides appropriate suggestions.
∙ Identifies the causes and responsibilities for outage loss, and facilitates reasonable O&M assessment.