A fast and accurate approach for power losses quantification of photovoltaic power systems under partial‐shading conditions

Abstract

Predicting the output power of partially‐shaded photovoltaic (PV) systems has a crucial role in the field of photovoltaic system studies and design. A significant number of models, circuit simulation techniques and power prediction formulations are proposed in the literature. However, several factors could limit their application such as computational burden, accuracy and their applicability to different levels of photovoltaic system. An analytical circuit‐based approach is proposed to predict the output power and power losses of partially‐shaded photovoltaic systems. The proposed approach is distinguished by high accuracy, low computational time and applicability to all photovoltaic system levels. Hence, it enables the assessment of partial shading mitigation ability of various photovoltaic system architectures. Furthermore, the proposed approach has no limitations on the size of photovoltaic system, for example, as in circuit‐based simulation analysis. An extensive simulation‐based comparison study for five partially‐shaded photovoltaic systems is conducted to compare the accuracy and computational time of the proposed approach with the detailed, well‐established single diode model. The accuracy of the proposed approach is also validated experimentally on a photovoltaic system of 12 series‐connected photovoltaic modules. Furthermore, a set of comparisons with experimental measurements from the literature is presented.

A novel technique using stretching, repulsion, and chimp optimization algorithm to find global maximum power point considering complex partial shading conditions

“…The value of "α" lies between À1 and 1 beyond which usually the value of x diverges. The value of "c" is generated between 0 and 2 as shown in (10). Each chimp agent behaves in a specific way in finding the position of x due to the values of "f" found by two different groups ChoA1 and ChoA2, the detail of which can be seen in the literature.…”

“…If that MPP or GMPP is not tracked accurately, then the power will be lost from PV modules. 10 An efficient algorithm is required to design to search and find the GMPP. It has been observed and deduced after taking real-time scenario measurements that the probability of an algorithm converging to LMPP is up to 70%.…”

A Simple Mismatch Mitigating Partial Power Processing Converter for Solar PV Modules

“…Since the duty cycle for the proposed SCL-based DPP topology is fixed at 50%, the average mismatch inductor current IL is distributed equally into IS1 and IS2 (currents flowing through Q1, Q2, Q3, and Q4). The current following through the output and switches can be found by using (5) and (6). To further explain the operational principle of the proposed topology, a shade is applied on the submodule to induce the mismatch, as shown in Figure 5.…”

“…The output power from PV modules is sensitive to non-ideal conditions such as dirt, manufacturing irregularities, thermal variations, aging, shadows, along with module placement orientations and angle of incidence. All these factors may induce a power mismatch in a PV system, which impacts the overall output and life of the PV system [4][5][6][7].…”

Hill Climbing Artificial Electric Field Algorithm for Maximum Power Point Tracking of Photovoltaics

“…Maximum power point tracking (MPPT) has attracted the attention of many studies as an effective technique to maximize the extracted power of photovoltaic (PV) systems (Al-Smadi et al, 2021). The MPPT aims to improve and optimize PV systems and maximize the efficiency of the PV plate to ensure the maximum electrical power generation with obtaining global Maximum power point (GMPP) tracking (Arabi Nowdeh et al, 2020;Nowdeh et al, 2019a).…”