According to Vision 2030, the Kingdom of Saudi Arabia (K.S.A) plans to harness 9.5 GW of energy from renewable energy sources, which includes a major part of solar PV generation. This massive implementation of solar projects requires an accurate assessment and analysis of solar resource data and PV site selection. This paper presents a detailed analysis of one-year solar radiation data and energy output of 100 kW PV systems at 44 different locations across the K.S.A. Coastal areas have a lower amount of global horizontal irradiance (GHI) as compared to inland areas. Najran University station gives the highest annual electrical output of 172,083 kWh, yield factor of 1721, and capacity utilization factor of 19.6%. Sharurah and Timma TVTC are second and third best with respect to annual PV performance. Similarly, during high load summer season (April-October), Tabuk station is the best location for a PV power plant with an electrical output of 110,250 kWh, yield factor of 1102, and capacity utilization factor of 21.46%. Overall, the northern province of Tabuk is the most feasible region for a solar PV plant. The basic approach presented in this research study compares solar resource pattern and solar PV system output pattern with the load profile of the country. The site selected based on this criterion is recommended to be economically most feasible which can reduce the stress on electricity companies during high load seasons by clipping the peak load during daytime in the hot summer period.

Summary The aim of this research is to analyze the techno‐economic performance of hybrid renewable energy system (HRES) using batteries, pumped hydro‐based, and hydrogen‐based storage units at Sharurah, Saudi Arabia. The simulations and optimization process are carried out for nine HRES scenarios to determine the optimum sizes of components for each scenario. The optimal sizing of components for each HRES scenario is determined based on the net present cost (NPC) optimization criterion. All of the nine optimized HRES scenarios are then evaluated based on NPC, levelized cost of energy, payback period, CO2 emissions, excess electricity, and renewable energy fraction. The simulation results show that the photovoltaic (PV)‐diesel‐battery scenario is economically the most viable system with the NPC of US$2.70 million and levelized cost of energy of US$0.178/kWh. Conversely, PV‐diesel‐fuel cell system is proved to be economically the least feasible system. Moreover, the wind‐diesel‐fuel cell is the most economical scenario in the hydrogen‐based storage category. PV‐wind‐diesel‐pumped hydro scenario has the highest renewable energy fraction of 89.8%. PV‐wind‐diesel‐pumped hydro scenario is the most environment‐friendly system, with an 89% reduction in CO2 emissions compared with the base‐case diesel only scenario. Overall, the systems with battery and pumped hydro storage options have shown better techno‐economic performance compared with the systems with hydrogen‐based storage.

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The fabrication and characterization of a temperature sensor on flexible poly(ethylene terephthalate) (PET) substrate is discussed. The device was printed by drop-on-demand (DOD) electrohydrodynamic (EHD) Patterning method using silver nanoparticles ink on a roll-to-roll (R2R) system on a mass scale. EHD patterning was performed at atmospheric pressure and room temperature in a single step. The ink viscosity was 300 cps and it contained 55 wt % of silver nanoparticles. The parameters for printing head speed, and DOD were optimized to create connected lines. The printed temperature sensor has the resistivity of 25.35 µΩ·cm and the temperature coefficient of resistance (TCR) is 0.0007687 °C−1. The micro sensor can be applied to many applications to measure temperature accurately of flat or curved surfaces.

Around the world, countries are integrating photovoltaic generating systems to the grid to support climate change initiatives. However, solar power generation is highly uncertain due to variations in solar irradiance level during different hours of the day. Inaccurate modelling of this variability can lead to non-optimal dispatch of system resources. Therefore, accurate characterization of solar irradiance patterns is essential for effective management of renewable energy resources in an electrical power grid. In this paper, the Weibull distribution based probabilistic model is presented for characterization of solar irradiance patterns. Firstly, Weibull distribution is utilized to model inter-temporal variations associated with reference solar irradiance data through moving window averaging technique, and then the proposed model is used for irradiance pattern generation. To achieve continuity of discrete Weibull distribution parameters calculated at different steps of moving window, Generalized Regression Neural Network (GRNN) is employed. Goodness of Fit (GOF) techniques are used to calculate the error between mean and standard deviation of generated and reference patterns. The comparison of GOF results with the literature shows that the proposed model has improved performance. The presented model can be used for power system planning studies where the uncertainty of different resources such as generation, load, network, etc., needs to be considered for their better management.

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Abstract:The Middle East is one among the areas of the world that receive high amounts of direct solar radiation. As such, the region holds a promising potential to leverage clean energy. Owing to rapid urbanization, energy demands in the region are on the rise. Along with the global push to curb undesirable outcomes such as air pollution, emissions of greenhouse gases, and climate change, an urgent need has arisen to explore and exploit the abundant renewable energy sources. This paper presents the design, performance analysis and optimization of a 100 MWe parabolic trough collector Solar Power Plant with thermal energy storage intended for use in the Middle Eastern regions. Two representative sites in the Middle East which offer an annual average direct normal irradiance (DNI) of more than 5.5 kWh/m 2 /day has been chosen for the analysis. The thermodynamic aspect and annual performance of the proposed plant design is also analyzed using the System Advisor Model (SAM) version 2017.9.5. Based on the analysis carried out on the initial design, annual power generated from the proposed concentrating solar power (CSP) plant design in Abu Dhabi amounts to 333.15 GWh whereas that in Aswan recorded a value of 369.26 GWh, with capacity factors of 38.1% and 42.19% respectively. The mean efficiency of the plants in Abu Dhabi and Aswan are found to be 14.35% and 14.98% respectively. The optimization of the initial plant design is also carried out by varying two main design parameters, namely the solar multiple and full load hours of thermal energy storage (TES). Based on the findings of the study, the proposed 100 MW parabolic trough collector solar power plant with thermal energy storage can contribute to the sustainable energy future of the Middle East with reduced dependency on fossil fuels.