Abstract
Distributed systematic grid-connected inverter practice needs to improve insulated gate bipolar transistor (IGBT) stability to ensure the safe operation. This study is to ensure the safety and reliability operation of the IGBT module in symmetry to meet the reliable and stable distributed systematic grid-connected inverter practice and the junction temperature is a parameter to assess its operating state. It is difficult to accurately acquire the IGBT junction temperature to be solved by a single method of combining the test and the modeling. The saturation voltage drop or collector current and module junction temperature data under different power cycles are measured by the power cycle test and the single pulse test. The improved chicken swarm optimization increases the chickens diversity and self-learning ability. The prediction model of the improved chicken swarm optimization-support vector machine is proposed to forecast the module junction temperature. The result showed to compare with the particle swarm optimization-support vector machine model and chicken swarm optimization-support vector machine model and showed the coincidence degree between the proposed model prediction value and the true value is higher. The mean absolute error ratio indicates the proposed model has a smaller error and a better prediction performance. The proposed model has a positive impact on improving the distributed systematic grid-connected inverter industrial development and promotes the new energy usage.
Highlights
The distributed photovoltaic (PV) grid-connected inverter performance directly affects the distributed PV power generation development
The common failure standard which is that the junction-to-case thermal resistance of insulated gate bipolar transistor (IGBT) increases by 20% compared with the initial value is selected in this study
Based on the data obtained by the power cycle test and the single pulse test, the 308 sets data at currents of 65 A, 70 A, 75 A and 80 A are selected to train and test chicken swarm optimization (CSO)-support vector machine (SVM) model and improved chicken swarm optimization (ICSO)-SVM
Summary
The distributed photovoltaic (PV) grid-connected inverter performance directly affects the distributed PV power generation development. As new energy technology development has promoted the exploitation and utilization of new energy. The new energy technology has a positive impact on promoting sustainable economic development and protecting the environment. With the development of society, traditional fossil energy sources cause serious environmental pollution, and are increasingly exhausted, which. Symmetry 2020, 12, 825 makes scientists strive to study new energy and seek the path of sustainable development [2,3,4]. In practices, promoting the energy transformation and achieving sustainable development are important issues for the development of mankind [5,6]. The primary goal of sustainable development is to achieve rational use of new energy and improves the energy utilization
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