Efficiency optimization of stand-alone photovoltaic pumping system based on MPPT and MLPT

Abstract: Solar power is a very promising global source of renewable energy, and is being used more widely throughout the world. Pumps are used for agricultural irrigation, drinking water, and other necessary pumping requirements in the vast rural area. In many places, where there is much land but few people, power is not easy to attain. In order to reach the deep groundwater, water pumps cannot rely on electric energy consumption, but instead must rely on diesel engines and traditional fuel equipment. However, we know that these regions, especially in arid areas, are rich in solar energy resources. Independent photovoltaic pump systems have emerged as a result. Although this kind of system is an application or extension currently used systems, the high cost of application and the low rate of return on investment are constraints that bottleneck the popularization of bringing independent photovoltaic pump systems to large rural areas. Therefore, the core of this paper studies the optimization of photovoltaic pump systems to enhance efficiency and to improve the rate of return on investment. Specifically, and without increasing the hardware investment, two methods are discussed. The first is the use of a Maximum Power Point Tracking (MPPT) algorithm to optimize the solar photovoltaic conversion efficiency. The second is reducing loss and enhancing the efficiency in the asynchronous motor of driving pump by using a Minimum Loss Point Tracking (MLPT) algorithm. Under different conditions, these algorithms can track motor-loss minimization real time. The study put forward anintegrated algorithm with MPPT and MLPT in a single application. MLPT is in the inner ring of integrated control system, with MPPT in the outer ring. The MPPT algorithm of the solar array, through the influence of a DC voltage inverter, output the reference frequency value, while the MLPT algorithm was based on minimizing the current control in the stator voltage to reduce asynchronous motor loss. Through a set of prototypes, first the MPPT and MLPT algorithms were tested individually. Then, according to the different light trends, the researchers tested an integrated MPPT/MLPT optimization algorithm. Using LabVIEW software, they rendered mutual relations and trend curves for each parameter. The test results show that, in a full common load case section n, the power pumping capacity increased up to 10%. This shows that photovoltaic pumping systems can effectively improve the rate of return on investment. The new system did not significantly increase investment in hardware, nor did it increase the monitoring system workload. In addition, its advantages include strong robustness, modular capabilities, and no battery storage as is commonly used in the industry. This promotes the popularity of the system as a viable long-term option. The system not only can be used in view of our poverty-stricken rural western country, but also may strengthen China's ability to develop remote rural drinking water projects in the developing country.