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[IEEE 2018 IEEE Industry Applications Society Annual Meeting (IAS) - Portland, OR, USA (2018.9.23-2018.9.27)] 2018 IEEE Industry Applications Society Annual Meeting (IAS) - Design and Optimization of a Solar Power Conversion System for Space Applications
摘要： This manuscript details a design method for a 500kW solar power based microgrid system for space applications. The design method utilizes multi-objective optimization with the Genetic Algorithm considering four parameters that characterize solar power based microgrids (battery voltage, PV maximum power, PV maximum power point voltage, and number of panels per string). The final optimization metric is the ratio of daily average deliverable power to total system mass (W/kg) metric. The microgrid system is composed of a number of modular DC-DC micro-converters, of which four topologies (buck, boost, buck-boost and non-inverting buck-boost) are evaluated and compared. The non-inverting buck-boost converter is determined to be the best candidate, and the optimal system characteristics are provided and analyzed. The final system design achieves a specific power of 35.56W/kg, with optimized result of 743.7V battery voltage, 439.5W PV maximum power, 182.7V PV maximum voltage, and three panels per string. Based on the optimizations results, a prototype is designed, tested, and analyzed in terms of efficiency and low temperature reliability. The converter achieved a peak efficiency of 98.4%, a power density of 3.54W/cm3, a specific power of 3.76W/g, and operated for over 267 hours of 11-minute low temperature cycles from 0oC to -140oC.
关键词： wide band gap semiconductors,microgrids,non-inverting buck-boost,maximum power point trackers,space exploration,photovoltaic systems,design optimization,DC-DC power converters,system-level design,low temperature testing
更新于2025-09-23 15:23:52
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Design and Optimization of a Solar Power Conversion System for Space Applications
摘要： This manuscript details a design method for a 500kW solar power based microgrid system for space applications. The design method utilizes multi-objective optimization with the Genetic Algorithm considering four parameters that characterize solar power based microgrids (battery voltage, PV maximum power, PV maximum power point voltage, and number of panels per string). The final optimization metric is the ratio of daily average deliverable power to total system mass (W/kg) metric. The microgrid system is composed of a number of modular DC-DC micro-converters, of which four topologies (buck, boost, buck-boost and non-inverting buck-boost) are evaluated and compared. The non-inverting buck-boost converter is determined to be the best candidate, and the optimal system characteristics are provided and analyzed. The final system design achieves a specific power of 35.56W/kg, with optimized result of 743.7V battery voltage, 439.5W PV maximum power, 182.7V PV maximum voltage, and three panels per string. Based on the optimizations results, a prototype is designed, tested, and analyzed in terms of efficiency and low temperature reliability. The converter achieved a peak efficiency of 98.4%, a power density of 3.54W/cm3, a specific power of 3.76W/g, and operated for over 267 hours of 11-minute low temperature cycles from 0oC to -140oC.
关键词： low temperature testing,photovoltaic systems,wide band gap semiconductors,maximum power point trackers,design optimization,non-inverting buck-boost,space exploration,system-level design,DC-DC power converters,microgrids
更新于2025-09-23 15:22:29