Cleaning cycle optimization and cost evaluation of module dust for photovoltaic power plants

Cleaning cycle optimization and cost evaluation of module dust for photovoltaic power plants in China 

Bo Zhao1 · Shuwei Zhang1 · Shengxian Cao1 · Qi Zhao2 

Published online: 26 July 2019 

Abstract 

The photovoltaic (PV) power plants installed in the northwest and northeast areas of China have a serious dust pollution problem. In this paper, a model for optimizing the cleaning cycle of module dust and evaluating the cost for the PV power plants in China was proposed by the use of dust deposition monitoring with image recognition and two cleaning technologies. Outdoor experimental results showed that the degradation of power conversion efficiency changed linearly with increasing the image gray value and the dust deposition density had an asymptotic relationship with dust deposition time. Based on the proposed model and corresponding dry and wet cleaning technologies, the optimal cleaning cycles for a PV power plant in northeast China were approximately 10.1 and 22.8 days when the power conversion efficiency was reduced by 4.5% and 10.2%, respectively. The annual cost resulting from dust on the PV power modules in China was estimated to be $0.0161– 0.0222 million per MW with current fixed cleaning cycle and wet cleaning technology. However, the annual cost could be reduced to 36.5–50.3% by using the optimized cleaning cycle and applying dry cleaning technology.


Comentarios

Publicar un comentario

Entradas populares de este blog

What is Data Lake?

Imagen
What is Data Lake? A Data Lake is a storage repository that can store large amount of structured, semi-structured, and unstructured data. It is a place to store every type of data in its native format with no fixed limits on account size or file. It offers high data quantity to increase analytic performance and native integration. Data Lake is like a large container which is very similar to real lake and rivers. Just like in a lake you have multiple tributaries coming in, a data lake has structured data, unstructured data, machine to machine, logs flowing through in real-time. The Data Lake democratizes data and is a cost-effective way to store all data of an organization for later processing. Research Analyst can focus on finding meaning patterns in data and not data itself. Unlike a hierarchal Dataware house where data is stored in Files and Folder, Data lake has a flat architecture. Every data elements in a Data Lake is given a unique identifier and tagged with a set of metadata inf
Leer más

Field Testing of Mars™ Soiling Sensor

Field Testing of Mars™ Soiling Sensor June 2020 with 21 Reads  Conference: 47th IEEE Photovoltaic Specialists Conference Michael Gostein Ben Bourne Fabrizio Farina Bill Stueve Abstract We report on an ongoing field evaluation of the Mars™ optical soiling sensor technology. The Mars™ soiling sensor was developed to provide a compact, low-cost, water-free and maintenance-free method to measure soiling at PV power plants, especially for small utility or commercial-scale sites where more complex solutions can be prohibitive. In this study, a Mars™ soiling sensor was deployed at a test site in California starting in February 2019. The site also includes a reference soiling measurement system employing a washed/unwashed PV reference cell pair. We review the correlation between the Mars™ and reference cell pair soiling results over a 13-month period.
Leer más