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The photovoltaic (PV) cells are highly sensitive to temperature variations. The linear variation of PV cells with operating temperature could lead to the loss of conversion efficiency and permanent damage of PV material. To address this critical issue, while improving the performance of solar photovoltaic system (SPVS) during the operating period, the deployment of a proper cooling system is a prime requisite in the design process. Considering this, two new and cost‐effective cooling techniques are proposed in this study, which can improve efficiency and increase the life of the PV panel. The first technique is the active cooling design with water. The proposed design enhances the access to PV cells to maximize cooling. The second one is an improved passive cooling technique that uses fins mounted on the backside of PV module. This further reduces the temperature by increasing the heat dissipation. Additionally, a third PV module without any cooling system is deployed as a reference margin. The techniques have been experimentally evaluated and a recommendation is made in order to reduce the temperature variation across the PV panel. [ABSTRACT FROM AUTHOR]

In this paper, a distributed estimation algorithm using Bayesian‐based forward backward Kalman filter (KF) is proposed for stochastic singular linear systems. The method incorporates generalised versions of KF for bounded cases with complete and incomplete prior information, followed by estimation fusion of these cases. The incorporated filters remain optimal given the cross‐covariance of the local estimates. The proposed approach is validated on a coupled‐tank system. [ABSTRACT FROM AUTHOR]

In this study, an improved distributed estimation scheme for static sensor networks is developed. The scheme is developed for environmental time‐variant physical variables. The main contribution of this work is that the algorithm in Saber and Murray (2005), Carli et al. (2009) and Xiao et al. (2004) has been extended, and a filter has been designed with weights, such that the variance of the estimation errors is minimised, thereby improving the filter design considerably and characterising the performance limit of the filter, and thereby tracking a time‐varying signal. Moreover, certain parameter optimisation is alleviated with the application of a particular finite impulse response filter. Simulation results are showing the effectiveness of the developed estimation algorithm. [ABSTRACT FROM AUTHOR]

In recent years, a compelling need has arisen to understand the effects of distributed information structures on estimation and filtering. In this study, a bibliographical review on distributed Kalman filtering (DKF) is provided. The study contains a classification of different approaches and methods involved to DKF. The applications of DKF are also discussed and explained separately. A comparison of different approaches is briefly carried out. Focuses on the contemporary research are also addressed with emphasis on the practical applications of the techniques. An exhaustive list of publications, linked directly or indirectly to DKF in the open literature, is compiled to provide an overall picture of different developing aspects of this area. [ABSTRACT FROM AUTHOR]