Non-iterative MPPT Method: A Comparative Study

The presented work is a contribution to maximum power point tracking problem with improved performance. The analysed and discussed method is based on mathematical model of a PV panel. The output power of PV panel is dependent on the load as well as the almost unpredictable behaviour of the environment. It has a non-linear implicit behaviour on the load due to the weather parameters dependency. Due to different conditions of PV curve, it may have several local maxima. Existing MPPT techniques are mainly based on iterative method which are more time consuming and complex in nature considering the sense of comparative techniques. The most used approach is based on P&O algorithm with gradient comparison. The proposed technique improves the performance on the basis of time and computational complexity. During a low changing environmental condition this method achieves good result on the way to reach the overall point for maximum power. Taking into account the data sheet values of the panel along with the usage of existing knowledge from the datasheets, this technique is possible to implement and flexible for digital signal processing platform. An experimental setup is also done to verify the accuracy, robustness and simplicity of the introduced algorithm. It is found that the proposed technique is less complex and can be coupled with other method too

A maximum power point tracking method for PV system with improved gravitational search algorithm

Photovoltaic (PV) system has gradually become research focus in the field of renewable energy power generation, and the output efficiency of PV system is the major concern of researchers. There are obvious non-linear characteristics in the output of PV system, and it will be greatly affected by external environment. For achieving the maximum output power, PV system must operate under the guidance of maximum power point tracking (MPPT) methods The tracking time and accuracy of these methods need to be improved. Therefore, this study contributes to increase output efficiency of PV system by improving the tracking time and accuracy of existing MPPT methods Specifically, a MPPT method with improved gravitational search algorithm (IGSA-MPPT) was proposed. The dynamic weight was added in the change factor of the gravity constant and the related factors of memory and population information exchange were added into the updating formula of particle velocity. IGSA-MPPT not only reduced the tracking time, but also improved the tracking accuracy and mitigated the fluctuations of the reference voltage. Finally, simulation results are compared with the of MPPT methods with particle swarm Optimization (PSO-MPPT) and gravitational search algorithm (GSA-MPPT). The average tracking time of IGSA-MPPT was reduced by 0.023 s and 0.0116s, and the average increase rates of maximum power were increased by 1.7071% and 0.7001% compared with PSO-MPPT and GSA-MPPT. In the simulations of PV system under the varying irradiance and temperature, the tracking speed and tracking accuracy of IGSA-MPPT were higher than those of PSO-MPPT, GSA-MPPT, GWO-MPPT, ICO-MPPT, and FCGSA-MPPT. In summary, IGSA-MPPT has better performance in tracking time and accuracy than other comparison algorithms. It can improve output efficiency of PV system in practical application

A review of recent advances in metaheuristic maximum power point tracking algorithms for solar photovoltaic systems under the partial-shading conditions

Several maximum power point (MPP) tracking algorithms for solar power or photovoltaic (PV) systems concerning partial-shading conditions have been studied and reviewed using conventional or advanced methods. The standard MPPT algorithms for partial-shading conditions are: (i) conventional; (ii) mathematics-based; (iii) artificial intelligence; (iv) metaheuristic. The main problems of the conventional methods are poor power harvesting and low efficiency due to many local maximum appearances and difficulty in determining the global maximum tracking. This paper presents MPPT algorithms for partial-shading conditions, mainly metaheuristics algorithms. Firstly, the four classification algorithms will be reviewed. Secondly, an in-depth review of the metaheuristic algorithms is presented. Remarkably, 40 metaheuristic algorithms are classified into four classes for a more detailed discussion; physics-based, biology-based, sociology-based, and human behavior-based are presented and evaluated comprehensively. Furthermore, the performance comparison of the 40 metaheuristic algorithms in terms of complexity level, converter type, sensor requirement, steady-state oscillation, tracking capability, cost, and grid connection are synthesized. Generally, readers can choose the most appropriate algorithms according to application necessities and system conditions. This study can be considered a valuable reference for in-depth works on current related issues

Modelagem para avaliação da viabilidade econômica e gerenciamento de riscos em contratos de construção e locação para geração de energia fotovoltaica distribuída na Unifei – Universidade Federal de Itajubá

Gastos públicos com contas de energia elétrica em universidades representam 11,4% do gasto total do governo federal brasileiro com as universidades. A literatura mostra que geração de energia renovável vem tomando espaço nas matrizes energéticas no mundo e, especificamente, a geração fotovoltaica vem crescendo, inclusive nas universidades. No Brasil a geração de energia fotovoltaica cresceu muito nos últimos anos e ainda existe muito espaço para crescimento. Nesta pesquisa, é apresentada uma modelagem para avaliação da viabilidade econômica e gerenciamento de riscos em contratos de construção e locação para geração de energia fotovoltaica distribuída na Universidade Federal de Itajubá (UNIFEI). No método proposto neste trabalho, são elaboradas quatro configurações técnicas em que são realizadas as simulações para a geração de energia fotovoltaica na Universidade. A partir dos resultados destas simulações, são realizadas comparações entre dois modelos de contrato propostos: Modelo de Construção, no qual a Universidade faz o investimento em um sistema de geração fotovoltaica e, em contrapartida, reduz seus gastos com energia elétrica e Modelo de Locação, em que uma empresa locadora faz o investimento no sistema fotovoltaico, o instala na UNIFEI, e passa a receber um aluguel da Universidade, cujo valor é equivalente à sua conta de energia, reduzida por um desconto percentual. Por fim, é feita uma comparação entre os resultados dos modelos de contrato visando encontrar a melhor solução para a Universidade