Inverted organic photovoltaics (OPVs) have gained considerable attention as they offer increased device stability and processing advantages. ZnO serves as an effective electron transport layer (ETL) in inverted OPVs while efficiently blocking holes. In this work, the sol gel precursor concentration, spin coating speed and baking conditions were used to simultaneously control the film thickness and morphology of ZnO ETLs in inverted devices using the active layer of poly thieno[3,4-b]thiophene/benzodithiophene (PTB7):[6,6]-phenyl C71-butyric acid methyl ester (PC 71 BM) bulk heterojunction (BHJ). Nano-ridged and planar structures of ZnO films were obtained simply by dynamically and statically baking the precursor films, respectively. Consistently high FF's exceeding 70% and PCEs averaging 7.65-8.01% with a maximum PCE reaching 8.32% were achieved on both nano-ridged and planar ZnO films when the active layer was maintained at ~94 nm. The effects of ZnO film thickness and morphology, along with the active layer thickness, on the device performance were further investigated using both experimental and transfer matrix optical modeling methods. The results demonstrated that high efficiency PTB7-based inverted OPVs can be achieved on both nano-ridged and planar ZnO ETLs as long as the optimal active layer thickness is maintained. devices with thinner active layers but is still within ~0.5 mA/cm 2 . The thickness of the planar ZnO films in the devices is in the range of approximately 42 to 62 nm. Within this range, Figure 4 shows the calculated J SC varies from 14.7 to 15.1 mA/cm 2 for a 94 nm active layer (i.e. the approximate PTB7:PC 71 BM thickness of devices in Fig. 3), which is close to the experimental J SC . Figure 4 shows that both the ZnO and the active layer thicknesses require simultaneous optimization to achieve maximum photocurrent.Device performance independent of film thickness for planar ZnO films was also observed in the study of inverted BHJ devices with the P3HT:PC 61 BM active layer. 14 As an ETL, the ZnO film should completely cover the ITO electrode to prevent current leakage. Once complete coverage is achieved, the thickness of the film has little effect on performance regardless of whether the active layer is P3HT:PC 61 BM or PTB7:PC 71 BM. However, the surface roughness of ZnO films affects the device performance in different ways when the active layer is P3HT:PC 61 BM versus PTB7:PC 71 BM. For P3HT:PC 61 BM BHJ devices, the increase of surface roughness from 2.86 to 4.02 nm resulted in the decrease of FF from 56 to 44%, accompanied by the increase of series resistance (R S ) from 10.7 to 31.7 Ω cm 2 . 14 It was suggested that a rougher ZnO film surface could induce more small voids between the P3HT:PC 61 BM active layer and the ZnO layer. In contrast, a consistently high FF of 72.3-73.4% was displayed in our devices regardless of the roughness variation from 2.59 to 4.16 nm among the four statically baked ZnO films. This may be due to differences in the microstructure and other properties of ...
The present paper reports the impact of the Covid-19 pandemic on the electricity peak load and power generation in the State of Kuwait during the partial and full curfews imposed in March, April and May 2020 using historic data measured data and the predictions provided by a statistical genetic algorithm model. A quantitative assessment is made of the economic and environmental impacts caused by partial and full lockdowns. Comparison of measured peak demand for 2019 and 2020 with predicted peak demand for 2020 has: (i) enabled an accurate evaluation of residential energy consumption in the state of Kuwait at nearly 18 MWh yearly the highest energy consumption per capita in the world, (ii) shown that the imposition of the curfews to reduce the spread of COVID-19 caused a fall in the demand for electrical power of 17.6% compared with the expected demand and (iii) quantified the reduction in CO2, NOx and CO pollutant emissions produced by power plants due to less fuel being consumed. A mathematical model has been developed to predict the peak electric load in the national grid according to climatic data supplied by the Meteorological Department of Civil Aviation of Kuwait and National Control Center (NCC).
Energetic and exergetic analyses are conducted using operating data for Sabiya, a combined cycle power plant (CCPP) with an advanced triple pressure reheat heat recovery steam generator (HRSG). Furthermore, a sensitivity analysis is carried out on the HRSG using a recent approach to differentiate between the sources of irreversibility. The proposed system was modelled using the IPSEpro software and further validated by the manufacturer's data. The performance of the Sabiya CCPP was examined for different climatic conditions, pressure ratios, pinch point temperatures, high-pressure steam, and condenser pressure values. The results confirmed that 60.9% of the total exergy destruction occurs in the combustion chamber, which constitutes the main source of irreversibilities within a system. The exergy destruction was significantly affected by both the pressure ratio and the high-pressure steam, where the relation between them was seen to be inversely proportional. The high-pressure stage contributes about 50% of the exergy destruction within the HRSG compared to other stages and the reheat system, due to the high temperature difference between the streams and the large number of components, which leads to high energy loss to the surroundings. Numerous possibilities for improving the CCPP's performance are introduced, based on the obtained results.
The rapidly increasing population growth and expansion of urban development are undoubtedly two of the main reasons for increasing global energy consumption. Accurate long-term forecasting of peak load is essential for saving time and money for countries’ power generation utilities. This paper introduces the first investigation into the performance of the Prophet model in the long-term peak load forecasting of Kuwait. The Prophet model is compared with the well-established Holt–Winters model to assess its feasibility and accuracy in forecasting long-term peak loads. Real data of electric load peaks from Kuwait powerplants from 2010 to 2020 were used for the electric load peaks, forecasting the peak load between 2020 and 2030. The Prophet model has shown more accurate predictions than the Holt–Winters model in five statistical performance metrics. Besides, the robustness of the two models was investigated by adding Gaussian white noise of different intensities. The Prophet model has proven to be more robust to noise than the Holt–Winters model. Furthermore, the generalizability test of the two models has shown that the Prophet model outperforms the Holt–Winters model. The reported results suggest that the forecasted maximum peak load is expected to reach 18,550 and 19,588 MW for the Prophet and Holt–Winters models by 2030 in Kuwait. The study suggests that the best months for scheduling the preventive maintenance for the year 2020 and 2021 are from November 2020 until March 2021 for both models.
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