System and method for diagnosing faults of photovoltaic power generation systems in online manner

Abstract

The invention provides a system for diagnosing faults of photovoltaic power generation systems in an online manner. The system comprises an upper computer, an environment monitoring instrument, a photovoltaic monitoring terminal, header box monitoring modules, assembly monitoring modules and the like. The upper computer has analyzing and processing functions, the environment monitoring instrument and the photovoltaic monitoring terminal are connected with the upper computer, the header box monitoring modules are respectively arranged on various header boxes, and the assembly monitoring modules are respectively arranged on various photovoltaic assemblies. The system has the advantages that the system is simple and reasonable in structure, each assembly monitoring module is arranged on the corresponding photovoltaic assembly, each header box monitoring module is arranged on the corresponding header box, accordingly, voltages, currents and power on each photovoltaic assembly, each photovoltaic assembly string and the header boxes can be detected; the various monitoring modules are organized to form a network and are matched with the environment monitoring instrument and the photovoltaic monitoring terminal, monitored and acquired data of various devices of the photovoltaic power generation systems and other reference data can be uploaded to the upper computer along network nodes step by step, accordingly, running states of the photovoltaic power generation systems can be comprehensively analyzed, and the system has an online fault diagnosing function.

Description

technical field [0001] The invention relates to the field of solar power generation, in particular to an integrated, efficient and intelligent online fault diagnosis system for a photovoltaic power generation system and an online fault diagnosis method for a photovoltaic power generation system. Background technique [0002] After more than ten years of rapid development, my country's photovoltaic industry has entered the stage of large-scale development. As of 2013, the cumulative installed capacity of photovoltaics in my country was 17.16GW, and the target for newly installed photovoltaic capacity in 2014 is 14GW. In 2020, the total capacity of photovoltaic power generation will reach 180GW. The operation level of the photovoltaic power generation system is the core element that affects the system benefits. It will directly affect the operation and maintenance cost, power generation efficiency, and power generation reliability of the photovoltaic power generation system. H...

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Problems solved by technology

[0003] However, such a large-scale photovoltaic power generation system requires a huge number of devices. When a device fails, all devices are checked one by one, and the workload is huge.

Taking a 50,000-kilowatt photovoltaic power station as an example, there are more than 100 inverters, more than 800 combiner boxes, more than 190,000 battery components, and a large number of DC confluence branches. In addition, the current distribution of photovoltaic power generation systems or geographical The location is remote, the transportation is inconvenient, or it is built on the roof of the building, so it is very difficult to inspect and manage the equipment

[0004] At present, there are also data acquisition and monitoring systems for photovoltaic power generation systems, but their existing problems are: 1) The monitoring data is unacceptable and unreliable

There is no string monitoring or only simple string data collection, the monitoring measurement accuracy is not high, and the measurement data is inaccurate; 2) It is difficult to report the monitoring data

The monitoring data is uploaded through the RS-485 bus, the transmission rate is low, there are many communication failures, false alarms and false alarms are serious; 3) fault location is difficult

The number of photovoltaic modules and nodes is huge, and there is a lack of effective fault location methods. Fault detection mainly relies on manual inspection and manual measurement and comparison through multimeters. The fault processing cycle is long, affecting power generation output, low maintenance efficiency, and large investment in manpower; 4) system Management lacks digital means

Simple collection and presentation of monitoring information, manual processing of a large number of data reports through Excel, poor comprehensive data analysis capabilities, lack of quantitative means for power generation operation analysis and improvement, and unified management of multiple systems cannot be realized

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