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Improving the performance of time invariant maximum power point tracking methods

机译:提高时间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:本文介绍了在经历部分遮阳条件(PSC)的光伏(PV)系统中使用的时间不变最大功率点跟踪(MPPT)方法的改进的重新倾向条件。时间不变(MPPT)方法,例如粒子群优化(PSO),通过跟踪PSC下运行的PV系统的全局最大功率点(GMPP)来克服现有MPPT的限制。然而,由于这些MPPT方法的不变结构,它们还需要在发生辐照度或温度的变化时定义重新幂化条件。使用MATLAB / SIMULINK模型的模拟进行测试,其中使用测试用例进行了随着太阳辐照度的变化来评估现有和开发条件的性能。确定了现有条件的局限性,并开发了更强大的重新研磨条件。开发的重新倾向条件使用哨声颗粒监测PV电压范围以进行任何哨兵的测量功率的变化。发达的条件具有96 %的成功检测率,与88 %的成功检测相比,现有方法的低至68%,展示了提高的性能和鲁棒性。

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