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Improving the performance of time invariant maximum power point tracking methods

机译:改进时不变最大功率点跟踪方法的性能

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This paper presents an improved reinitialisation condition for time invariant maximum power point tracking (MPPT) methods used in photovoltaic (PV) systems experiencing partial shading conditions (PSC). Time invariant (MPPT) methods, such as Particle Swarm Optimisation (PSO), overcome the limitations of existing MPPT by tracking the global maximum power point (GMPP) of a PV system operating under PSC. However, due to the time invariant structure of these MPPT methods, they also require a reinitialisation condition to be defined for when a change in irradiance or temperature occurs. Testing was performed using simulations of a model built in Matlab/ Simulink, where the performance of existing and developed conditions was evaluated using test cases with changes in solar irradiance. Limitations of existing conditions were identified and a more robust reinitialisation condition developed. The developed reinitialisation condition used sentry particles to monitor the PV voltage range for changes in the measured power of any sentry. The developed condition had a 96 % rate of successful detection, as compared to as low as 68 % successful detection for existing methods, demonstrating improved performance and robustness.
机译:本文提出了用于时变最大功率点跟踪(MPPT)方法的改进的重新初始化条件,该方法用于经历部分阴影条件(PSC)的光伏(PV)系统。诸如粒子群优化(PSO)之类的时不变(MPPT)方法通过跟踪在PSC下运行的PV系统的全局最大功率点(GMPP),克服了现有MPPT的局限性。但是,由于这些MPPT方法的时间不变结构,因此它们还需要为何时发生辐照度或温度变化定义重新初始化条件。使用Matlab / Simulink中内置的模型进行仿真来进行测试,其中使用随着太阳辐照度变化的测试用例来评估现有条件和已开发条件的性能。确定了现有条件的局限性,并开发了更强大的重新初始化条件。开发的重新初始化条件使用了哨兵颗粒,以监视PV电压范围内任何哨兵的测得功率变化。与现有方法的成功检测率低至68%相比,所开发的条件的成功检测率为96%。

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