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Photovoltaic plant operating statuses identification model based on support vector machine using loss quantity of electricity feature parameters
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Photovoltaic plant operating statuses identification model based on support vector machine using loss quantity of electricity feature parameters
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Conference Proceeding
Photovoltaic plant operating statuses identification model based on support vector machine using loss quantity of electricity feature parameters
2015
Overview
Operating Statuses Identification (OSI) can help operators to find fault timely and minimize the loss. So it is of great significance for optimal operation of photovoltaic (PV) plants. The loss quantity of electricity (LQOE) is defined as that should have been generated but actually not, which is caused by inverter fault, PV modules fault, dust stratification or combinations of them. Firstly, mathematical models of PV cells are proposed to figure out the LQOE of each PV module. Secondly, after analysing the relation between LQOE and operating statuses, an index set of LQOE describing the distinction of different operating statuses are defined including four statistical feature parameters and a user-defined index. Thirdly, Support Vector Classification models for OSI (OSI-SVC) are built with input features extracted from the index set. Lastly, simulations are carried out to verify the effectiveness and evaluate the performance of the OSI-SVC models. The results indicated that the operating statuses can be effectively recognized by the proposed model.
Publisher
The Institution of Engineering & Technology
Subject
ISBN
1785610406, 9781785610400
