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Monitoring Solar Home Systems With Pulse Width Modulation Charge Control

机译:通过脉宽调制电荷控制监控太阳能家庭系统

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With the high cost of grid extension and approximately 1.6 billion people still living without electrical services, the solar home system is an important technology in the alleviation of rural energy poverty across the developing world. The performance monitoring and analysis of these systems provide insights leading to improvements in system design and implementation in order to ensure high quality and robust energy supply in remote locations. Most small solar home systems now use charge controllers using pulse width modulation (PWM) to regulate the charge current to the battery. A rapid variation in current and voltage resulting from PWM creates monitoring challenges, which, if not carefully considered in the design of the monitoring system, can result in the erroneous measurement of photovoltaic (PV) power. In order to characterize and clarify the measurement process during PWM, a mathematical model was developed to reproduce and simulate measured data. The effects of matched scan and PWM frequency were studied with the model, and an algorithm was devised to select appropriate scan rates to ensure that a representative sample of measurements is acquired. Furthermore, estimation methods were developed to correct for measurement errors due to factors such as nonzero "short circuit" voltage and current/voltage peak mismatches. A more sophisticated algorithm is then discussed to more accurately measure PV power using highly programmable data loggers. The results produced by the various methods are compared and reveal a significant error in the measurement of PV power without corrective action. Estimation methods prove to be effective in certain cases but are susceptible to error during conditions of variable irradiance. The effect of the measurement error has been found to depend strongly on the duty cycle of PWM as well as the relationship between scan rate and PWM frequency. The energy measurement error over 1 day depends on insolation and system conditions as well as on system design. On a sunny day, under a daily load of about 20 A h, the net error in PV energy is found to be 1%, whereas a system with a high initial battery state of charge under similar conditions and no load produced an error of 47.6%. This study shows the importance of data logger selection and programming in monitoring accurately the energy provided by solar home systems. When appropriately considered, measurement errors can be avoided or reduced without investment in more expensive measurement equipment.
机译:由于电网扩建的高昂成本和约16亿人仍然没有电力服务,太阳能家庭系统是缓解发展中国家农村能源贫困的一项重要技术。这些系统的性能监视和分析提供了见识,可改善系统设计和实施,从而确保在偏远地区提供高质量和稳定的能源供应。现在,大多数小型太阳能家用系统都使用通过脉冲宽度调制(PWM)进行充电的控制器来调节流向电池的充电电流。 PWM导致电流和电压的快速变化会带来监视挑战,如果在监视系统的设计中未仔细考虑,则会导致光伏(PV)功率的错误测量。为了表征和阐明PWM期间的测量过程,开发了一个数学模型来重现和模拟测量数据。利用该模型研究了匹配扫描和PWM频率的影响,并设计了一种算法来选择合适的扫描速率,以确保获得代表性的测量样本。此外,开发了估计方法以校正由于诸如“零”短路电压和电流/电压峰值不匹配之类的因素引起的测量误差。然后讨论一种更复杂的算法,以使用高度可编程的数据记录器更准确地测量PV功率。比较了各种方法产生的结果,发现在没有采取纠正措施的情况下,PV功率的测量存在重大误差。估计方法在某些情况下被证明是有效的,但是在辐照度可变的情况下容易出错。发现测量误差的影响在很大程度上取决于PWM的占空比以及扫描速率和PWM频率之间的关系。 1天以上的能量测量误差取决于日射量和系统条件以及系统设计。在晴天,在每天约20 A h的负载下,发现PV能量的净误差为1%,而在类似条件下无负载的初始电池高充电状态的系统则产生47.6的误差。 %。这项研究表明,数据记录器的选择和编程对于准确监视太阳能家用系统提供的能量的重要性。如果适当考虑,就可以避免或减少测量误差,而无需投资购买更昂贵的测量设备。

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