Model Predictive Control on Thermal Stress Reduction for Grid-Connected Inverters Reliability Enhancement
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Abstract
Thermal stress has been identified as one of the major failure causes in the power module. It is generated from the mechanical strain by severely varying temperatures at different loci in the power module and the different coefficients of the thermal expansion of materials, where the varying temperatures result from the real-time power loss across the power converter. This thermal stress accelerates the degradation of semiconductor devices, downgrades the system quality and efficiency, and eventually causes catastrophic system breakdowns and extensive economic losses. Therefore, this research is dedicated to investigating both local control level methods and system level strategies to ameliorate the real-time power loss in order to reduce the thermal stress in the power module, thereby extend the component lifetime and enhance the system reliability.Prior work for local control level methods including the modulation method, and the control target method shows an effective progress on the power loss and thermal stress reductions. However, the increased control loops and complicated modulation schemes in the modulation method affect the system stability. The onefold feature of temperature rising and scalability issue in the control target method restrict the degree on the thermal stress reduction. Besides, prior work for system level strategies is still in its infancy, where a few of strategies are developed preliminarily to reduce the thermal stress and coordinate the power sharing method for the multiple inverters microgrid. However, these strategies are all power sharing oriented instead of being thermal stress oriented. They may present a limited adjustment on the thermal profile. In this research, novel local control level method and system level strategy are developed. First, a finite-control-set model predictive control (FCS-MPC) is introduced and deductively investigated from the local control level. Its variable switching frequency property is derived through the geometry analysis on the voltage vector space. It realizes the switching frequency variation autonomously by the loading power. By taking advantage of this property, the power loss is leveled in the real-time operation by FCS-MPC and a more mitigated thermal profile is acquired compared with the one by the conventional controller. Furthermore, an energy-loss-minimization secondary problem formulation in FCS-MPC is proposed to reduce the power loss in order to achieve the junction temperature mean value decreasing in the power module. This secondary problem formulation is integrated with the basic problem formulation by different weightings to achieve the power flow control and the power loss reduction simultaneously. Second, a centralized thermal stress oriented dispatch (TSOD) system level strategy is proposed for multiple paralleled distributed energy resource systems, which help to reduce the thermal stress in the power module of paralleled converters. It is thermal stress oriented and takes effect according to the real-time junction temperature variation, the health condition of the individual converter and the system operation. Two local control level methods, the switching frequency variation and the reactive power injection, are imported separately as the dispatch algorithm to generate the expected power loss. Dealing with the varying mission profile, the more mitigated thermal profiles are achieved for all converters with the assistance of the proposed TSOD strategy. The effectiveness of all methodologies from both local control level and system level is validated in the simulations, experiments, and Model-in-the-Loop testing. A long-time-scale analysis from the reliability assessment is also conducted to quantify the impacts of the relieved thermal stress on the damage and lifetime of the power module. Results justify the significant thermal stress reduction in the power module of the converter, which is the main contribution of this research.