An Improved Evolutionary Programming (IEP) Method Under the EN 50530 Dynamic MPPT Efficiency Test

Abstract

Photovoltaic (PV) system is an attractive renewable energy source as PV systems are environmental friendly, utilize inexhaustible resource, and provide long-term economic benefits. However, PV systems suffer a common drawback which is the lack of efficiency of the maximum power point tracking (MPPT) used to extract the maximum available power from PV system. Typically, the efficiency of a PV system is evaluated using the static MPPT performance and the dynamic MPPT performance where the latter is usually analyzed using simple irradiance profiles that do not truly reflect the real environmental conditions. In order to achieve an evaluation that is more accurate and closer to the actual performance of a PV system, a dynamic MPPT efficiency test based on international standards such as the European Standard EN 50530 is deemed vital. With regard to Soft Computing (SC) MPPT methods, there are hardly any publication that analyzes the MPPT performance based on the EN 50530 standard. This paper presents the design and experimental evaluation of an improved Evolutionary Programming (EP)-based MPPT method that complies with the EN 50530 standard. The proposed concept is simulated in MATLAB/Simulink platform and is validated experimentally using a custom-designed PV array simulator (PVAS), DC-DC boost converter, and a resistive load. The results show that the proposed method achieves better performance compared to the conventional EP with improvement in efficiency of 30% and 40% for low gradient and medium/high gradient irradiance respectively.