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This is the second in a two-part paper series dealing with sea salt transportation and deposition mechanisms, and discussing the serious issue of degradation of outdoor insulators resulting from various environmental stresses and severe saline contaminant accumulation near the shoreline. The deterioration rate of outdoor insulators near the shoreline depends on the concentration of saline in the atmosphere, influence of wind speed on the production of saline water droplets, moisture diffusion and saline penetration on the insulator surface. This paper comprises two parts. The first part, deals with the impact of different environmental stresses on insulator surface degradation, including wind speed and direction, cold fog and rainfall. The second part concerns the flashover process related to saline contamination of the surface under constant and variable cold fog wetting rates and equivalent salt deposit density (ESDD). The experiments were performed on high voltage insulators based on the model presented in Part-I. Based on the proposed model, the influence of wind speed and direction on the pollution accumulation rate and impact of wetting rate on discharge current and surface flashover process were investigated. The equations S=S 0 e (Vdep0/αh) [e (αx/v)-1 ] and D=D 0 e (Vdep0/αh) [e (-αx/v)-1 ] are derived from the model for saline concentration and deposition show good reliability and well represent the results obtained. Test results also show that due to the different wetting and contamination deposition rate, surface discharge current characteristics of tested insulator in rain are different with that in cold fog, which lead to different surface flashover voltages. An experimental setup was mounted for artificial saline contamination deposition. The proposed model can be therefore used to investigate insulator flashover near coastal areas and for mitigating saline flashover incidents.

Incorporating solar energy into a grid necessitates an accurate power production forecast for photovoltaic (PV) facilities. In this research, output PV power was predicted at an hour ahead on yearly basis for three different PV plants based on polycrystalline (p-si), monocrystalline (m-si), and thin-film (a-si) technologies over a four-year period. Wind speed, module temperature, ambiance, and solar irradiation were among the input characteristics taken into account. Each PV plant power output was the output parameter. A deep learning method (RNN-LSTM) was developed and evaluated against existing techniques to forecast the PV output power of the selected PV plant. The proposed technique was compared with regression (GPR, GPR (PCA)), hybrid ANFIS (grid partitioning, subtractive clustering and FCM) and machine learning (ANN, SVR, SVR (PCA)) methods. Furthermore, different LSTM structures were also investigated, with recurrent neural networks (RNN) based on 2019 data to determine the best structure. The following parameters of prediction accuracy measure were considered: RMSE, MSE, MAE, correlation (r) and determination (R2) coefficients. In comparison to all other approaches, RNN-LSTM had higher prediction accuracy on the basis of minimum (RMSE and MSE) and maximum (r and R2). The p-si, m-si and a-si PV plants showed the lowest RMSE values of 26.85 W/m2, 19.78 W/m2 and 39.2 W/m2 respectively. Moreover, the proposed method was found to be robust and flexible in forecasting the output power of the three considered different photovoltaic plants.

Abstract:The aim of this paper is to investigate the various effects of climate conditions on outdoor insulators in coastal areas as a result of saline contamination under acidic and normal cold fog, determining significant electrical and physico-chemical changes on the insulator surface and considering the effect of discharge current, electric field distribution and surface roughness. To replicate similar conditions near the shoreline, experimental investigations have been carried out on insulation materials with the combined application of saline contamination and acidic or normal cold fog. The test samples included silicone rubber (SiR), ethylene propylene diene monomer (EPDM) and high-density polyethylene (HDPE), which were used as reference. The materials are of the same composition as those used in real-life outdoor high voltage insulators. All samples were aged separately in an environmental chamber for 150 h for various saline contaminations combined with acidic and normal cold fog, and were generated by means of the adopted experimental setup. This analysis represented conditions similar to those existing near the shoreline exposed to saline and acid spray during winter and early spring. Electric field and discharge current along polymeric samples were examined under acidic and normal cold fog. Fourier transform infrared (FTIR) spectroscopy and scanning electron microscopic (SEM) were used to probe the physico-chemical changes on the samples surface and investigate the hydrophobicity recovery property after aging tests. Finally, a comparative study was carried out on polymeric samples before and after being exposed to the acidic and normal cold fog based on the results obtained from the experiment. Research data may provide references for the better prediction of surface degradation as well as for the better material coating and design of external insulation.

The purpose of this paper is to investigate the impact of risk and competition on the profitability of the Pakistani banking industry. Data are retrieved from the annual statements of banks, the Ministry of finance Pakistan and the World Bank covering the period of (2007–2017). Two steps Generalized Method of Moments (GMM) with the collapse command is used as an estimation technique to overcome endogeneity, unobserved heterogeneity and autocorrelation problems. The results of the study showed that the liquidity risk has positive while credit risk, insolvency risk and competition hurt negatively the profitability of Pakistani banks. The results of the study also revealed that capitalization, size, taxation and GDP growth rate positively affect the Banks’ profits while banking sector development and infrastructure negatively affect banking profitability in Pakistan. The operational cost management positively affects net interest margins but negatively affects ROA and PBT in the Pakistani banking industry.