A Parameter Estimation of Photovoltaic Models Using a Boosting Flower Pollination Algorithm.

ABSTRACT: An accurate and reliable estimation of photovoltaic models holds immense significance within the realm of energy systems. In pursuit of this objective, a Boosting Flower Pollination Algorithm (BFPA) was introduced to facilitate the robust identification of photovoltaic model parameters and enhance the conversion efficiency of solar energy into electrical energy. The incorporation of a Gaussian distribution within the BFPA serves the dual purpose of conserving computational resources and ensuring solution stability. A population clustering strategy is implemented to steer individuals in the direction of favorable population evolution. Moreover, adaptive boundary handling strategies are deployed to mitigate the adverse effects of multiple individuals clustering near problem boundaries. To de

SUBMITTER: Liu S 

PROVIDER: S-EPMC10575107 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature