Optimal orientation angles for maximizing energy yield for solar PV in Saudi Arabia

This paper uses research-quality, ground measurements of irradiance and temperature that are accurate to ±2% to estimate the electric energy yield of fixed solar modules for utility-scale solar power plants at 18 sites in Saudi Arabia. The calculation is performed for a range of tilt and azimuth angles and the orientation that gives the optimum annual energy yield is determined. A detailed analysis is presented for Riyadh including the impact of non-optimal tilt and azimuth angles on annual energy yield. It is also found that energy yield in March and October are higher than in April and September, due to milder operating temperatures of the modules. A similar optimization of tilt and azimuth is performed each month separately. Adjusting the orientation each month increases energy yield by 4.01% compared to the annual optimum, but requires considerable labour cost. Further analysis shows that an increase in energy yield of 3.63% can be obtained by adjusting the orientation at five selected times during the year, thus significantly reducing the labour requirement. The optimal orientation and corresponding energy yield for all 18 sites is combined with a site suitability analysis taking into account climate, topography and proximity to roads, transmission lines and protected areas. Six sites are selected as having high suitability and high energy yield: Albaha, Arar, Hail, Riyadh, Tabuk and Taif. For these cities the optimal tilt is only slightly higher than the latitude, however the optimum azimuth is from 20° to 53° west of south due to an asymmetrical daily irradiance profile

Assessment of off-shore wind turbines for application in Saudi Arabia

This paper presents models and economic analysis of ten different wind turbines for the region of Yanbu, Saudi Arabia using the hybrid optimization models for energy resources (HOMER) software. This study serves as a guide for decision makers to choose the most suitable wind turbine for Yanbu to meet the target of 58.7GW of renewable energy as part of Saudi Vision 2030. The analysis was carried out based on the turbines initial capital cost, operating cost, net present cost (NPC) and the levelized cost of energy (LCOE). Additionally, the wind turbines were compared based on their electricity production, excess energy and the size of the storage devices required. The results show that Enercon E-126 EP4 wind turbine has the least LCOE (0.0885 $/kWh) and NPC ($23.8), while WES 30 has the highest LCOE (0.142 $/kWh) and NPC ($38.3) for a typical load profile of a village in Yanbu

A Comprehensive Review of Most Competitive Maximum Power Point Tracking Techniques for Enhanced Solar Photovoltaic Power Generation

A major design challenge for a grid-integrated photovoltaic power plant is to generate maximum power under varying loads, irradiance, and outdoor climatic conditions using competitive algorithm-based controllers. The objective of this study is to review experimentally validated advanced maximum power point tracking algorithms for enhancing power generation. A comprehensive analysis of 14 of the most advanced metaheuristics and 17 hybrid homogeneous and heterogeneous metaheuristic techniques is carried out, along with a comparison of algorithm complexity, maximum power point tracking capability, tracking frequency, accuracy, and maximum power extracted from PV systems. The results show that maximum power point tracking controllers mostly use conventional algorithms; however, metaheuristic algorithms and their hybrid variants are found to be superior to conventional techniques under varying environmental conditions. The Grey Wolf Optimization, in combination with Perturb & Observe, and Jaya-Differential Evolution, is found to be the most competitive technique. The study shows that standard testing and evaluation procedures can be further developed for comparing metaheuristic algorithms and their hybrid variants for developing advanced maximum power point tracking controllers. The identified algorithms are found to enhance power generation by grid-integrated commercial solar power plants. The results are of importance to the solar industry and researchers worldwide

Left Main Coronary Artery Revascularization in Patients with Impaired Renal Function: Percutaneous Coronary Intervention versus Coronary Artery Bypass Grafting

Introduction: The evidence about the optimal revascularization strategy in patients with left main coronary artery (LMCA) disease and impaired renal function is limited. Thus, we aimed to compare the outcomes of LMCA disease revascularization (percutaneous coronary intervention [PCI] vs. coronary artery bypass grafting [CABG]) in patients with and without impaired renal function. Methods: This retrospective cohort study included 2,138 patients recruited from 14 centers between 2015 and 2,019. We compared patients with impaired renal function who had PCI (n= 316) to those who had CABG (n = 121) and compared patients with normal renal function who had PCI (n = 906) to those who had CABG (n = 795). The study outcomes were in-hospital and follow-up major adverse cardiovascular and cerebrovascular events (MACCE). Results: Multivariable logistic regression analysis showed that the risk of in-hospital MACCE was significantly higher in CABG compared to PCI in patients with impaired renal function (odds ratio [OR]: 8.13 [95% CI: 4.19–15.76], p < 0.001) and normal renal function (OR: 2.59 [95% CI: 1.79–3.73]; p < 0.001). There were no differences in follow-up MACCE between CABG and PCI in patients with impaired renal function (HR: 1.14 [95% CI: 0.71–1.81], p = 0.585) and normal renal function (HR: 1.12 [0.90–1.39], p = 0.312). Conclusions: PCI could have an advantage over CABG in revascularization of LMCA disease in patients with impaired renal function regarding in-hospital MACCE. The follow-up MACCE was comparable between PCI and CABG in patients with impaired and normal renal function

The Impact of Soiling on PV Module Performance in Saudi Arabia

Solar photovoltaic (PV) deployment is rapidly expanding around the world. However, the soiling factor has an impact on its performance. Saudi Arabia has high solar irradiation and plans to diversify its energy mix for electricity generation by deploying more solar PV across the country. However, it is located in an arid and desert environment, making it a challenging project due to dust accumulation on solar modules. The soiling and PV performance in Saudi Arabia are examined in this paper. Furthermore, it highlights several mitigation techniques that can be used to maintain PV performance through preventive and restorative measures. Furthermore, this study looks into the size and characterization of dust in Saudi Arabia, as well as the entire life cycle of dust accumulation on PV modules. In this review study, the performance of solar PV systems is evaluated under soiling in different regions of Saudi Arabia. Depending on the local environment and other factors, the PV performance has been reduced by somewhere between 2% and 50%. A single sandstorm reduced the module power output by 20%. As revealed in Dhahran, the PV module was exposed to an outdoor environment and not cleaned for 6 months resulting in a power drop of more than 50%. It is strongly advised to clean PV panels once a month or fewer to maintain a high-performance system. However, in the event of a dust storm, it is advised to clean the system immediately to avoid a major decline in PV performance. The bi-facial PV solar panels technology associated with solar trackers and utilizing robotic cleaning systems have maximized the received solar irradiation and minimized the soiling loss efficiently. The most common elements found in dust particles are primarily derived from the natural desert. It has been noted that the composition and sizes of dust particles depend heavily on the location of the PV module. It is concluded that dust accumulation and cleaning costs are not a significant barrier to large-scale, cost-effective solar PV deployments in Saudi Arabia, particularly in the central region, which is considered a high-suitable region for utility-size PV plants due to many factors. The results of this study are essential for enlightening the PV engineering community, investors, and the research community about how soiling may affect regions with significant solar potential, such as Saudi Arabia, and what potential soiling mitigation strategies may be considered to maintain high-performance solar PV projects

A High Speed MPPT Control Utilizing a Hybrid PSO-PID Controller under Partially Shaded Photovoltaic Battery Chargers

Improving photovoltaic systems in terms of temporal responsiveness, lowering steady-state ripples, high efficiency, low complexity, and decreased tracking time under various circumstances is becoming increasingly important. A particle-swarm optimizer (PSO) is frequently used for maximum power-point tracking (MPPT) of photovoltaic (PV) energy systems. However, during partial-shadowing circumstances (PSCs), this technique has three major drawbacks. The first problem is that it slowly converges toward the maximum power point (MPP). The second issue is that the PSO is a time-invariant optimizer; therefore, when there is a time-variable shadow pattern (SP), it adheres to the first global peak instead of following the dynamic global peak (GP). The third problem is the high oscillation around the steady state. Therefore, this article proposes a hybrid PSO-PID algorithm for solving the PSO’s three challenges described above and improving the PV system’s performance under uniform irradiance and PSCs. The PID is designed to work with the PSO algorithm to observe the maximum voltage that is calculated by subtracting from the output voltage of the DC-DC boost converter and sending the variation to a PID controller, which reduces the error percentage obtained by conventional PSO and increases system efficiency by providing the precise converter-duty cycle value. The proposed hybrid PSO-PID approach is compared with a conventional PSO and bat algorithms (BAs) to show its superiority, which has the highest tracking efficiency (99.97%), the lowest power ripples (5.9 W), and the fastest response time (0.002 s). The three aforementioned issues can be successfully solved using the hybrid PSO-PID technique; it also offers good performance with shorter times and faster convergence to the dynamic GP. The results show that the developed PID is useful in enhancing the conventional PSO algorithm and solar-system performance

Fault Location in Distribution Network by Solving the Optimization Problem Based on Power System Status Estimation Using the PMU

Fault location is one of the main challenges in the distribution network due to its expanse and complexity. Today, with the advent of phasor measurement units (PMU), various techniques for fault location using these devices have been proposed. In this research, distribution network fault location is defined as an optimization problem, and the network fault location is determined by solving it. This is done by combining PMU data before and after the fault with the power system status estimation (PSSE) problem. Two new objective functions are designed to identify the faulty section and fault location based on calculating the voltage difference between the two ends of the grid lines. In the proposed algorithm, the purpose of combining the PMU in the PSSE problem is to estimate the voltage and current quantities at the branch point and the total network nodes after the fault occurs. Branch point quantities are calculated using the PMU and the governing equations of the π line model for each network section, and the faulty section is identified based on a comparison of the resulting values. The advantages of the proposed algorithm include simplicity, step-by-step implementation, efficiency in conditions of different branch specifications, application for various types of faults including short-circuit and series, and its optimal accuracy compared to other methods. Finally, the proposed algorithm has been implemented on the IEEE 123-node distribution feeder and its performance has been evaluated for changes in various factors including fault resistance, type of fault, angle of occurrence of a fault, uncertainty in loading states, and PMU measurement error. The results show the appropriate accuracy of the proposed algorithm showing that it was able to determine the location of the fault with a maximum error of 1.21% at a maximum time of 23.87 s

Impact of the International Nosocomial Infection Control Consortium (INICC)’s multidimensional approach on rates of ventilator-associated pneumonia in intensive care units in 22 hospitals of 14 cities of the Kingdom of Saudi Arabia

To analyze the impact of the International Nosocomial Infection Control Consortium (INICC) Multidimensional Approach (IMA) and use of INICC Surveillance Online System (ISOS) on ventilator-associated pneumonia (VAP) rates in Saudi Arabia from September 2013 to February 2017. A multicenter, prospective, before–after surveillance study on 14,961 patients in 37 intensive care units (ICUs) of 22 hospitals. During baseline, we performed outcome surveillance of VAP applying the definitions of the CDC/NHSN. During intervention, we implemented the IMA and the ISOS, which included: (1) a bundle of infection prevention practice interventions, (2) education, (3) outcome surveillance, (4) process surveillance, (5) feedback on VAP rates and consequences and (6) performance feedback of process surveillance. Bivariate and multivariate regression analyses were performed using generalized linear mixed models to estimate the effect of intervention. The baseline rate of 7.84 VAPs per 1000 mechanical-ventilator (MV)-days―with 20,927 MV-days and 164 VAPs―, was reduced to 4.74 VAPs per 1000 MV-days―with 118,929 MV-days and 771 VAPs―, accounting for a 39% rate reduction (IDR 0.61; 95% CI 0.5–0.7; P 0.001). Implementing the IMA was associated with significant reductions in VAP rates in ICUs of Saudi Arabia