Abstract
The development of highly efficient models of Photovoltaic (PV) cells and modules is essential for optimized performance, evaluation and control of solar PV systems. The accurate estimation of PV cells parameters is a challenging task because of their non-linear characteristics. In this paper, an improved variant of Flower Pollination Algorithm (FPA) is proposed for accurate estimation of PV cells and modules parameters. The proposed algorithm involves double exponential based dynamic switch probability and a dynamic step size function that mitigate the limitations of conventional FPA. The dynamic switch probability improves the overall performance of algorithm by maintaining a balance between local and global search, while dynamic step function controls the search speed which avoids premature convergence and local optima stagnation. Moreover, Newton Raphson Method is utilized for accurate computation of estimated current for optimum set of estimated parameters. The proposed methodology is evaluated using seven benchmark functions and three case studies; 1- RTC France silicon PV cell, 2- Photo-watt PWP-201 PV module and 3- a practical solar PV system (EAGLE PERC 60M 310W monocrystalline PV module) under different environmental conditions by estimating parameters for single and double diode models. The analysis of results indicates that, the proposed approach improves the convergence speed, precision, avoids premature convergence and stagnation in local optima of conventional FPA. Furthermore, comparative analysis of results illustrates that, the proposed approach is more reliable and efficient than many other techniques in literature.
Highlights
Depleting conventional energy resources, increasing prices of fossil fuels and environmental threats have reduced the production of electrical energy
Afterwards, the proposed Flower Pollination Algorithm (FPA) is applied on three case studies 1) RTC France silicon PV cell, 2) Photo-watt PWP201 module and 3) a practical system EAGLE PERC 60M 310W monocrystalline PV module of parameter estimation problem to validate the robustness of proposed technique
The results presented proved the efficiency and accuracy of proposed approach than other techniques available in literature
Summary
Depleting conventional energy resources, increasing prices of fossil fuels and environmental threats have reduced the production of electrical energy. The comprehensive review of literature shows that many researchers [36]–[41] have put their efforts in avoiding premature convergence, slow convergence rate and local optima stagnation problems of conventional FPA but they failed to prove efficient for parameter estimation problem because it is very sensitive due to minor changings in RMSE All these variants improve performance of FPA with different search strategies but still FPA has a room for further improvements. This paper proposes a double exponential weight dynamic switch probability with exponential step size function FPA for parameter estimation of single and double diode models of PV cell, module and a practical system. An improved variant of FPA is proposed to have fast convergence rate, avoids premature convergence and trapping in local optima providing accurate and optimal results for parameter estimation problem.
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