Abstract
Massive infiltration of photovoltaic (PV) systems into electric supply networks creates numerous challenges in the present era, as the PV systems become an alternative to non-renewable energy resources. Partial shading, nevertheless, is an essential problem which affects the productivity and life of PV plants. PV reconfiguration is known as a powerful technique to resolve this effect. It is achieved by rearranging the PV modules according to their temperature and levels of shade. Therefore, in this paper, we have utilized three simple population-based optimization algorithms that are known as the flow regime algorithm (FRA), the social mimic optimization algorithm (SMO), and the Rao optimization algorithm to dynamically restructure the PV array. The effectiveness of the proposed algorithms is evaluated using several metrics such as fill factor, mismatch losses, percentage of power loss, and percentage of power enhancement. Besides, the results obtained are compared with a regular total-cross-tied (TCT) connection and recently published techniques such as the competence square (CS) and genetic algorithm (GA). Furthermore, to demonstrate the suitability of proposed approaches in real-time implementation, real-time irradiation data of a particular location are considered and fed into the proposed algorithms for effective shade dispersion. After successful shade dispersion, the total energy generated using the three proposed algorithms is calculated and compared with the TCT reconfigured system for one year. The presented energy calculations and revenue generation confirm that the power produced by the proposed FRA technique is 13% higher than that generated by the TCT configuration. Furthermore, the presented PV characteristics show a reduced number of multiple peaks in the system. Thus, the proposed FRA technique can be endorsed as a technique that is superior to other existing methods.
Highlights
In the present world, renewable energy resources have gained extreme solicitude because of different key reasons, including the consumption of non-renewable energy sources, atmosphere concerns, the penchant to have a greenery and amicable atmosphere [1]
Several analysis and comparisons were performed over the proposed algorithms (Rao optimization algorithm, social mimic optimization algorithm (SMO) algorithm, and flow regime algorithm (FRA)) to evaluate and demonstrate the most robust and reliable algorithm that achieves the optimal PV reconfiguration scheme
SMO and Rao optimization reconfiguration techniques produce energy 11% and 9% higher than that of TCT-connected system, respectively. These results prove that the proposed FRA technique greatly enhances power generation
Summary
Renewable energy resources have gained extreme solicitude because of different key reasons, including the consumption of non-renewable energy sources, atmosphere concerns, the penchant to have a greenery and amicable atmosphere [1]. The authors in [23], the proposed novel method named optimized string dynamic PV array to reduce the effect of partial shading In this method, PV strings with the same irradiation level are connected to an individual converter. The three proposed algorithms are selected because they have the features of the simplicity in the implementation and requiring low number of tuned permeates To evaluate these optimization techniques, a weighted objective function has been considered and tested under various shade patterns including with real time irradiation data available over period of ten years. G and T are considered actual irradiation and temperature values, respectively, and ki indicates the current coefficient factor
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