Shen Wentao

Bio: Shen Wentao is an academic researcher. The author has contributed to research in topics: Fault (power engineering) & Photovoltaic power station. The author has an hindex of 1, co-authored 4 publications receiving 2 citations.

Photovoltaic Power System Fault Warning based on State Assessment

Abstract: The stability of photovoltaic power system is very important. A small fault in one component can cause a large damage on the whole power system. This paper aims to propose a method to evaluate the stability of photovoltaic power system so that we could take measures in advance to avoid greater losses. This paper studies how we assess the status of a power grid. To assess the status of power grid, we select some fault which is often occur in photovoltaic power system. Then we build a fault tree based on the photovoltaic power plant network. Finally, we substitute the probability of various faults into the fault tree for analysis and prediction. According to probability of failure at this moment and coefficient, we can calculate how the system running at this moment. In this paper, the early fault warning of photovoltaic power system: firstly use machine learning methods to pre-process the original data, eliminate redundancy and noise, then run regression analysis on pre-processed data and get the failure rate of a certain time. Take the example of a photovoltaic power system in China, through learning and verification of fault data, our method can effectively realize the early fault warning of photovoltaic power system.

Method and device for determining fault type of photovoltaic power grid

Abstract: The invention discloses a method and device for determining the fault type of a photovoltaic power grid, belongs to the technical field of electric power, and aims at solving the problem of low faulttype judgment accuracy of a traditional expert system based on an artificial rule in the prior art. The method of the invention comprises the following steps that: a determining device acquires firstpower data, wherein the first power data is power data of the photovoltaic power grid in a first time period; and the determining device inputs the first power data into a current fault type diagnosismodel to determine the first fault type of the photovoltaic power grid corresponding to the first power data, wherein the first fault type is a fault type of the photovoltaic power grid which is corresponding to the first power data and is determined by the fault type diagnosis model.

Distributed photovoltaic power station fault monitoring method and device based on edge computing

Abstract: The application provides a distributed photovoltaic power station fault monitoring method and device based on edge computing, which are applied to an edge computing device. The method comprises the steps of: obtaining meteorological and environmental parameters of an area where a target distributed photovoltaic power station is located, cloud block image data and field equipment image data above the target distributed photovoltaic power station; predicting the power generation power of the target distributed photovoltaic power station in a set time period by using the meteorological and environmental parameters, the cloud block image data above and the field equipment image data to serve as predicted power generation power; acquiring actual power generation power of the target distributedphotovoltaic power station within the set time period; and monitoring whether the target distributed photovoltaic power station has abnormity or faults or not by comparing the predicted power generation power with the actual power generation power. In the application, the abnormity or fault monitoring of the target distributed photovoltaic power station can be achieved through the mode, and the monitoring reliability is improved.

Abnormal data detection method and device for photovoltaic power station and electronic equipment

Abstract: The invention provides an abnormal data detection method and device for a photovoltaic power station and electronic equipment. The method comprises the steps of after obtaining photovoltaic residual data corresponding to a power station, determining a clustering center point of the photovoltaic residual data based on the photovoltaic residual data; clustering the photovoltaic residual error data on the basis of the clustering center point to obtain a clustering result; determining the photovoltaic residual data which does not belong to any clustering cluster as abnormal data. According to themethod and the device, the abnormal data can be determined, so that when the abnormal data occurs, the fault handling is carried out in time, and the stability and the safety of an electric power system are ensured. Furthermore, the clustering center point is determined through the density value dimension data and the distance value dimension data, so that the determined clustering center point ismore accurate, the clustering result obtained by using the clustering center point is more accurate, and the determined abnormal data is more accurate.

Converter station fault report automatic generation method and device, electronic equipment and storage medium

Abstract: The invention belongs to the technical field of power equipment, and relates to a converter station fault report automatic generation method, which comprises the steps of obtaining a fault alarm signal; collecting fault data according to the fault alarm signal; identifying a fault type according to the fault data and a preset fault case feature library; selecting a fault report template accordingto the fault type; and automatically generating a fault report according to the selected fault report template, the fault data and the fault type. The fault alarm information is automatically acquired, the fault type is identified according to the preset fault case column feature library and the acquired fault data, and the fault report is generated according to the matching relationship between the fault type and the report, so that the invention is efficient and high in accuracy.

Distributed power supply scheduling control method based on edge calculation

Abstract: The invention relates to the technical field of power distribution networks, in particular to a distributed power supply scheduling control method based on edge calculation. The method comprises the following steps: A) obtaining a topological structure and scheduling data of a target distribution network, and listing a transformer, energy storage equipment and a wind-solar power station in the target distribution network; B) reading an active power prediction value and a reactive power prediction value of the load in the next time period, and predicting the output of the wind-solar power station; C) calculating a characteristic value, and if the characteristic value is smaller than a set threshold value, entering a step E); D) only outputting active power by the wind-solar power station, and returning to the step B); E) calculating the ratio of active power to reactive power output by the wind-solar power station; and F) respectively outputting the real-time output of the wind-solar power station as active power and reactive power according to the ratio, and returning to the step B. The method has the substantive effects of reducing the influence on the power distribution network when the renewable energy power station with unstable output is accessed to the power distribution network, being beneficial to expanding the access of renewable energy, and being suitable for the power distribution network with high permeability.