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• A novel grey wolf optimization (GWO) algorithm is proposed to estimate three unknown parameters of the PV module. • The proposed method is compared with another popular method named as particle swarm optimization (PSO) algorithm. • Three different PV modules are successfully tested via single diode model. • Different statistical errors are calculated, and it is found the minimum for the proposed method. This paper proposes a novel parameter estimation technique for photovoltaic (PV) module considering grey wolf optimization (GWO). Manufacturer data sheet of PV module does not provide all essential parameters of PV module for modelling. Therefore for accurate modelling of PV module, an efficient parameter estimation technique is necessary to estimate the unknown parameters of the PV module. Since conventional estimation methods do not estimate PV parameters with high accuracy, therefore bio-inspired techniques have drawn considerable attention toward it. GWO is a new optimization technique which exhibits high efficiency for optimizing nonlinear equations. Therefore GWO technique is explored here for parameter estimation of PV module under changing weather conditions. The proposed GWO technique is employed for parameter estimation of different PV modules under different test conditions. GWO technique is compared with another popular optimization technique named as particle swarm optimization (PSO) and found having better fitness value compared to PSO. The proposed model is validated through experimental data under different weather conditions and found matching accurately with measured values. Considering different statistical errors, the discussed model has been compared with other well-known models found in the literature. The results show the superiority of the proposed model with a minimum error for both current-voltage and power-voltage characteristics. [ABSTRACT FROM AUTHOR]

In conventional design method, the parameters of an active filter cannot be selected based on manufactured parameters such as E series. However, this can be feasibly obtained using optimization technique through an exhaustive search on all possible combination of preferred values of E series by providing the coding system. The exhaustive search for low pass second order filter is carried out through Meta-heuristic optimization Algorithms. The cost function for error minimization including compatible to E series and gain adaptive are used here as objective function for finding out minima through well known algorithms. The inclusion of gain constrained concept eliminates the extra op-amp cascading to state variable filter circuit which reduces the noise and dimension of cost function; in addition, improves the stability of the system. The performances of Grey Wolf Optimization (GWO), Whale Optimization Algorithm (WOA) and Sine-Cosine Algorithm (SCA), nature and physics-inspired artificial intelligence techniques are evaluated for state variable filter design considering gain constrained. Each of above algorithms is applied to filter structure and performances of them are also evaluated when filter design is realized with components selected from different manufactured E series. [ABSTRACT FROM AUTHOR]

The component value selection for active analogue filter design is an important issue to improve the performances and to make compatible with existing parameters value. The Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) are efficient intelligent evolutionary algorithms for solving optimization problems. Both techniques are used to minimize the total design error of a 4th order Butterworth low pass active filter. This would be realized with component values which are compatible with E12 series. In addition, stability of filter is guaranteed by minimization of gain sensitivity product. By considering the minimization of Gain Sensitivity Product (GSP), the sixteen variables of objective function are reduced to eight variables which speed up the iteration process. The simulation results prove the efficiency of algorithms for the design of analogue active filter by optimizing the component values based on E12 compatible with minimization of GSP by minimising the design error. [ABSTRACT FROM AUTHOR]

This paper presents a concise and an organized review of various maximum power point tracking (MPPT) algorithms implemented in the photovoltaic (PV) generation system useable under partial shading condition. Various algorithms, PV modeling techniques, PV array configurations and controller topologies have been widely explored till date. But, every technique always has its advantages as well as disadvantages simultaneously; as a result, a proper literature review is essential while designing a PV generation system (PGS) under partial shading condition. In this paper, the detailed review of MPPT algorithms has been done. The review on MPPT techniques has been classified into mainly four essential groups. The first among them includes all the new MPPT optimization algorithms, the second group includes the hybrid MPPT algorithms, the third category includes new modeling approach, and the fourth category includes the various converter topologies. This paper provides an accessible reference to undertake mass research works in PV systems in the near future under partial shading condition. [ABSTRACT FROM AUTHOR]

The increased power demand needs the installation of more power-generating units. Apart from conventional power generating stations based on fossil fuel combustion, recently solar power generating stations have attracted a large stake due to various advantages. However, the increased power generation also needs to be focused on various factors like stability, and reliability of the grid system leading to putting more emphasis on active power control techniques. This article reviews different active power control methods including conventional and flexible horizons. The focus of this article is to analyze the reliability factor while extracting power from solar plants. Maximum power point tracking (MPPT) is a well-known strategy for the maximum utilization of solar energy. However, as the dependency on solar energy rises the conventional control strategy needs to be modified for active grid participation of the PV systems. This can be performed by incorporating Flexible Power Point Tracking (FPPT) control strategies instead of MPPT. In this article, a comparison of the two techniques has been performed to choose the best method based on the requirement. Further, the impact of both systems on the grid system has been briefed in this article. Also, benchmarking has been proposed from the analysis to switch over between the modes depending on the power availability. [ABSTRACT FROM AUTHOR]