This paper deals with the reduction in electrical losses and the minimization of voltage deviation in electrical power grids. To this end, a novel heuristic-based approach is proposed for controlling reactive power injections along an electrical grid with distributed generation using distributed photovoltaic (PV) generation. The proposed approach consists of applying a heuristic, namely a genetic or firefly algorithm, to solve the loss and voltage deviation optimization problem by controlling PV reactive power injections. The proposed method was tested on a radial 100-bus network with an intense penetration of PV generation. The obtained results indicate that the proposed method consistently yields superior grid performance when compared to algorithms previously proposed in the literature. In fact, it led to a reduction in the active power supplied by the reference bus to the grid, thereby alleviating the burden imposed on the most upstream parts of the distribution network. As a consequence, the proposed method contributes to a power-efficient network, enhancing its loss performance and voltage stability.

— In this work, a novel maximum power point tracking algorithm (MPPT) based on Model Predictive Control (MPC) for photovoltaic systems is proposed. The considered system is composed by a photovoltaic panel connected to a load using a flyback converter. The proposed approach combines MPC with a modified Incremental Conductance algorithm with a variable step size, verified in this work to be more efficient than the Perturb and Observe algorithm in tracking maximum power point, making the PV system to generate more energy. Computational simulations are carried out to compare the performance of the considered MPPT algorithms, analyzing the output voltage and output power behavior at the photovoltaic panel. The results of the simulations show that the proposed algorithm provides better performance for the photovoltaic system than the main MPPT algorithms in the literature.

In this work, a new maximum power point tracking algorithm (MPPT) for photovoltaic systems is proposed. The considered system is composed of a photovoltaic panel charging a battery using a buck-type DC–DC converter. Computational simulations are carried out to compare the performances of the MPPT algorithms, therein analyzing the output voltage and output power behavior at the photovoltaic panel. Three evaluation scenarios are considered: with constant irradiance and temperature, randomly chosen conditions and using real data. The results of the simulations show that the proposed algorithm applied to the photovoltaic system achieves a better performance than the main MPPT algorithms in the literature.

Este artigo propõe um método adaptativo de estimação de parâmetros de painéis fotovoltaicos. A atualização dos valores dos parâmetros é realizada em função das condições ambientais (irradiância e temperatura) em que os painéis estão submetidos. O circuito elétrico equivalente utilizado para descrever o painel solar é o modelo de um diodo. Inicialmente, utiliza-se o Algoritmo Firefly para realizar a estimação dos parâmetros nas Condições Padrões de Teste. Em seguida, os valores estimados são corrigidos de acordo com os valores de irradiância e temperatura reais variantes no tempo. Por fim, calcula-se a potência gerada com os parâmetros atualizados comparando-a com a potência gerada pelos parâmetros nas Condições Padrões de Teste. Os resultados obtidos da estimação de parâmetros são comparados com outros trabalhos propostos na literatura.